<p><strong>This study evaluates an immobilized enzyme reactor (IMER) containing peptide N-glycosidase from </strong><i><strong>Rudaea cellulosilytica</strong></i><strong> (PNGase Rc) for rapid online deglycosylation of intact glycoproteins. Human glycoproteins and therapeutic antibodies were used as model substrates to assess reactor performance.</strong></p><p>The PNGase Rc IMER efficiently removed complex sialylated and core-fucosylated glycans, simplifying protein characterization and glycosylation-site analysis. The approach offers a fast and effective solution for bioanalytical workflows, biopharmaceutical quality control, and stability testing of therapeutic proteins.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c00577"><strong>Online Deglycosylation of Monomeric Intact Proteins Using the PNGase Rc Immobilized-Enzyme Reactor</strong></a></h4><p>Katarína Molnárová, Petr Novák, Jana Nováková, and Petr Pompach*</p><p>ACS Omega 2026, 11, 17, 25724–25729</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.6c00577">https://doi.org/10.1021/acsomega.6c00577</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Protein glycosylation, in which monosaccharide units are attached to a protein backbone through enzymatic pathways, is involved in many important biochemical processes and is considered one of the most important post-translational modifications. <a href="javascript:void(0);">(1)</a> It affects not only the stability and secretion of proteins, cell–cell interactions, and receptor–ligand recognition mechanisms but also the biological activity, plasma half-life, immunogenicity, pharmacodynamics, and pharmacokinetics of biotherapeutics. <a href="javascript:void(0);">(2−5)</a> Therapeutical monoclonal antibodies (mAbs) are among the best known pharmaceuticals that are based on glycoproteins. <a href="javascript:void(0);">(6)</a> Over 90% of the mAbs are derived from immunoglobulin G (IgG), in which <i>N</i>-glycosylation occurs at Asn297 of the Fc region and is responsible for modulating immune responses and interactions with other proteins. <a href="javascript:void(0);">(7,8)</a> In cancer treatment, mAbs are used to increase the response of the immune system against the tumor cell, thus inhibiting the cancerous cell growth and helping with the destruction and elimination. <a href="javascript:void(0);">(9)</a> Among the most commonly used mAbs are trastuzumab, bevacizumab, cetuximab, or margetuximab, which are used as an additional treatment for breast, colorectal, prostate, or lung cancer. <a href="javascript:void(0);">(10)</a></p><p>Mass spectrometry (MS)-based methods have become a method of choice in the analysis of mAbs that can provide information on sequence, post-translational modifications, and glycosylation profiles. <a href="javascript:void(0);">(11)</a> The enzymatic removal of the attached glycans from the protein backbone can reduce the complexity of the MS analysis, which can lead to a better understanding of the protein structure and modifications. In glycoproteomics, peptide-<i>N</i>-glycosidase F (PNGase F) is most used for glycan removal. It cleaves the linkage between the Asn residue and the <i>N</i>-acetylglucosamine (GlcNAc). <a href="javascript:void(0);">(12)</a> Jmeian et al. developed a monolithic PNGase F enzyme reactor fabricated in fused silica using a glycidyl methacrylate-<i>co</i>-ethylene dimethacrylate polymer and integrated it into an LC–MS workflow. The authors demonstrated the applicability of this system for the characterization of released neutral and acidic <i>N</i>-glycans by LC–MS analysis. <a href="javascript:void(0);">(13)</a> In another study, oriented immobilization of PNGase F onto a methacrylate-based monolithic support via glutathione-<i>S</i>-transferase–glutathione affinity coupling was employed to release <i>N</i>-glycans from denatured ribonuclease B and fetuin, as well as from native IgG. The released glycans and the corresponding deglycosylated proteins were subsequently analyzed by MALDI-MS. <a href="javascript:void(0);">(14)</a></p><p>Gramlich et al. showed the potential of PNGase Rc for <i>N</i>-glycan hydrolysis from both tryptic peptides and native glycoproteins at a low pH. The favorable properties of PNGase Rc, including activity at acidic pH and compatibility with reducing agents such as <i>tris</i>(2-carboxyethyl)phosphine hydrochloride (TCEP) and denaturants like urea, make this enzyme well suited for online intact protein deglycosylation workflows. <a href="javascript:void(0);">(15,16)</a></p><p>In this report, we demonstrate the potential of the PNGase Rc IMER for rapid online deglycosylation of reduced monomeric glycoproteins, including human haptoglobin (Hp), human transferrin, <i>anti</i>-hHD6, and the therapeutic monoclonal antibodies trastuzumab and bevacizumab. The column retained its activity over more than 150 consecutive measurements, highlighting its robustness, suitability for repeated use in bioanalytical workflows, and applicability to pharmaceutical research and development.</p><h4><strong>Experimental Section</strong></h4><h5><strong>Instrumentation and Experimental Conditions</strong></h5><p>Automated sample handling and online deglycosylation were carried out using the HDX workstation (AffiPro, Czech Republic). The scheme of the system is shown on <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c00577#fig1">Figure 1</a>. Samples of 50 mM ammonium bicarbonate buffer (pH 8.2) and 40 mM TCEP were placed in a sample tray at 4 °C. Ten microliters of the protein sample at a concentration of 0.03 mg/mL (0.3 μg per injection) were added to 40 μL of 50 mM ammonium bicarbonate and then transferred to 50 μL of 40 mM TCEP, pH 2.3. The disulfide bond reduction was carried at 40 °C for 5 min. The automated sample handling system injected 100 μL of the reaction mixture into the sample loop and switched the injection valve. Online deglycosylation was performed at room temperature using a PNGase Rc IMER (2.1 × 20 mm, AffiPro, Czech Republic) at a flow rate of 50 μL/min, followed by protein desalting on an OPTI-TRAP (0.5 × 2 mm) trap column (Optimize Technologies Inc., Oregon City, Oregon, USA) heated to 55 °C for 10 min with 0.2% formic acid delivered by an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1260+Infinity+III+isocratic+pump"><strong>Agilent 1260 Infinity III isocratic pump</strong></a><strong> </strong>(Agilent Technologies, Santa Clara, California, USA). By switching the trap valve, the protein was eluted by an acetonitrile gradient [(min)/% B] 0/10-9/10-16/70-16.5/90-17/90-18/10-23/10] delivered by the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+II+LC"><strong>Agilent 1290 Infinity II HPLC</strong></a> system (Agilent Technologies, Santa Clara, California, USA) at a flow rate of 20 μL/min. The mobile phase A consisted of 5% acetonitrile with 1% propan-2-ol and 0.1% formic acid, and the mobile phase B consisted of 95% acetonitrile with 1% propan-2-ol and 0.1% formic acid. The <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=8&amp;search=maXis+Q-TOF"><strong>maXis Q-TOF mass spectrometer</strong></a> (Bruker Daltonics, Bremen, Germany) was operated in the survey MS mode in a mass range of <i>m</i>/z 50–3000. The acquired data were analyzed and processed by <strong>DataAnalysis 4.4</strong> (Bruker Daltonics) and deconvoluted by UniDec <a href="javascript:void(0);">(17)</a> with the following parameters: data processing range, <i>m</i>/z 500–3000; charge range, 1–80; allowed mass range, 1,000–80,000; sampling rate, 10 Da; peak detection range, 500 Da; and peak detection threshold, 0.1.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_17_25724_25729_Figure_1_Schematic_of_the_automated_sample_handling_system_for_online_protein_deglycosylation_and_desalting_d4ee48b627.jpg" alt="ACS Omega 2026, 11, 17, 25724–25729: Figure 1. Schematic of the automated sample handling system for online protein deglycosylation and desalting. Protein samples, along with 50 mM ammonium bicarbonate and 40 mM TCEP stock solutions were placed in a sample tray chilled to 4 °C, while a second tray heated to 40 °C was used for disulfide bond reduction with TCEP buffer." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_17_25724_25729_Figure_1_Schematic_of_the_automated_sample_handling_system_for_online_protein_deglycosylation_and_desalting_d4ee48b627.jpg 245w," sizes="100vw" width="1287" height="386"></p><h4><strong>Results and Discussion</strong></h4><p>The performance of the PNGase Rc IMER for the removal of complex <i>N</i>-glycans from intact proteins was tested using heavily glycosylated human Hp with four glycosylation sites (Asn184, Asn207, Asn211, and Asn241) <a href="javascript:void(0);">(18)</a> located at the β-chain and occupied by complex <i>N</i>-glycans terminated with sialic acid. Haptoglobin phenotype 2-1, used in this study, forms multimers consisting of β-chain and disulfide linked α1 and α2 chains. <a href="javascript:void(0);">(19)</a> The detection of glycosylated Hp β-chain requires reduction of the disulfide bonds by incubating the protein with a reducing reagent. TCEP is a common reducing reagent used for fast reduction of disulfide bonds at various pH levels. Forty degrees Celsius, the maximum temperature of the PAL tray, and 5 min of incubation were sufficient for complete reduction of Hp disulfide bonds. Individual signals corresponding to the glycosylated β-chain were observed in the <i>m</i>/<i>z</i> range of 35,800–37,400 (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c00577#fig2">Figure 2</a>a). The limited resolution of the mass spectrometer did not allow assigning the different glycoforms of the haptoglobin β-chain, which is occupied by biantennary, triantennary, or tetraantennary glycans with various amounts of sialic acid and fucose. <a href="javascript:void(0);">(20,21)</a> The nonglycosylated α1 and α2 chains were observed at <i>m</i>/<i>z</i> 9190 and 15,940. When the PNGase Rc IMER was integrated into the flow system, a signal at <i>m</i>/<i>z</i> 27,270 was detected, demonstrating complete deglycosylation of the haptoglobin β-chain (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c00577#fig2">Figure 2</a>b).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_17_25724_25729_Figure_2_A_Mass_spectrum_of_human_Hp_without_the_PN_Gase_Rc_IMER_implemented_in_the_system_0ecca84ed4.jpg" alt="ACS Omega 2026, 11, 17, 25724–25729: Figure 2. (A) Mass spectrum of human Hp without the PNGase Rc IMER implemented in the system. The base peak signals of the spectrum correspond to both α1 and α2 chains. The signal of the β chain is spread across its different glycoforms. (B) Mass spectrum of human Hp with the PNGase Rc IMER implemented in the system. The signal of the deglycosylated β chain is higher compared to its glycosylated form and observed only at m/z 27,270. This indicates complete removal of glycans from the Hp β chain." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_17_25724_25729_Figure_2_A_Mass_spectrum_of_human_Hp_without_the_PN_Gase_Rc_IMER_implemented_in_the_system_0ecca84ed4.jpg 245w," sizes="100vw" width="2015" height="913"></p><p>In a previous study by Krenkova et al., the PNGase F IMER was used for deglycosylation of IgG, RNase B, and bovine fetuin with follow-up mass spectrometry detection of both released glycans and intact proteins using MALDI-TOF MS. <a href="javascript:void(0);">(14)</a> The authors demonstrated an effective method for rapid protein deglycosylation, which, however, requires additional sample handling prior to mass spectrometry measurement. The other study by Jmeian et al., which focused on released <i>N</i>-glycans, implemented a PNGase F IMER with online LC–MS detection. <a href="javascript:void(0);">(13)</a> The authors show the effectiveness of the method by identifying many different glycans released from a single protein or from a complex plasma mixture. Our approach is not directly intended for released <i>N</i>-glycan analysis; instead, it demonstrates the ability to measure intact proteins after rapid online deglycosylation using PNGase Rc at low pH. Samples prepared immediately prior to mass spectrometry analysis using the automated sample-handling platform can reduce variability associated with autosampler residence time, as some proteins may undergo degradation or precipitation during storage in the autosampler.</p><p>Although all glycoproteins in this study were effectively deglycosylated, the method’s efficiency depends on the characteristics of the individual glycoprotein. Therefore, optimizing method parameters─including the isocratic flow rate, glycoprotein incubation time with TCEP, and/or the addition of denaturing reagent─may improve the overall efficiency of the deglycosylation process.</p><p>The PNGase Rc IMER stability over a series of injections was tested by using the trastuzumab antibody. The measurements were carried out with the enzyme column kept at the laboratory temperature. As shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.6c00577#fig5">Figure 5</a>, the results indicate that the column performance remained stable over the course of the 150 measurements, and no glycosylated form of the trastuzumab antibody heavy chain was detected. The activity of PNGase Rc in the presence of 5% acetonitrile and 5% propan-2-ol was evaluated using a bottom-up approach with human 2–1 haptoglobin, which was online-digested by a coimmobilized nepenthesin-2/pepsin IMER. In the absence of an organic solvent, the peptide IEKVVLHPNYSQVD remained fully deglycosylated throughout 30 injections. In contrast, in the presence of organic solvent, a marked loss of enzymatic activity was observed after only a few injections (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.6c00577/suppl_file/ao6c00577_si_001.pdf">Figure 2</a>).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_17_25724_25729_Figure_5_Monitoring_the_stability_and_performance_of_PN_Gase_Rc_IMER_4a9b5a9c53.jpg" alt="ACS Omega 2026, 11, 17, 25724–25729: Figure 5. Monitoring the stability and performance of PNGase Rc IMER. Trastuzumab heavy chain was completely deglycosylated after 150 injections." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_17_25724_25729_Figure_5_Monitoring_the_stability_and_performance_of_PN_Gase_Rc_IMER_4a9b5a9c53.jpg 170w," sizes="100vw" width="996" height="918"></p><h4><strong>Conclusions</strong></h4><p>Here, we demonstrate the potential of the PNGase Rc IMER for the online removal of <i>N</i>-glycans from intact monomeric glycoproteins reduced with TCEP. The column showed high sensitivity toward Hp, which has multiple glycosylation sites with various glycan structures, confirming its suitability for the profiling of complex glycoproteins. Bevacizumab and trastuzumab exhibited similar glycosylation profiles, with core-fucosylated biantennary glycans being the most abundant. Online deglycosylation with the PNGase Rc column resulted in a complete removal of the glycans from the heavy chains of both antibodies, proving that the column can be used for the rapid online deglycosylation of intact therapeutic mAbs. Moreover, the column remained stable over 150 measurements without any loss of activity, even when it was maintained at laboratory temperature. The significantly reduced reaction time, together with full automation and the absence of manual handling steps, substantially improves analytical throughput compared to conventional off-line deglycosylation workflows. These findings highlight the potential of the PNGase Rc IMER in the development of glycoprotein-based biopharmaceuticals, where detailed structural characterization of the protein part is critical for quality control, monitoring batch-to-batch variability, and stability testing.</p></div>

Online Deglycosylation of Monomeric Intact Proteins Using the PNGase Rc Immobilized-Enzyme Reactor

<p><strong>In the week of June 29, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Thermo Fisher Scientific: Insights from an IC specialist: To be suppressed or not suppressed?</strong></h5><ul><li>Tu, 30.6.2026 09:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6310">Registration</a></li></ul><p>Join Thermo Fisher’s Ask the Experts session to learn how suppressor technology impacts ion chromatography performance, sensitivity, reliability, maintenance, and troubleshooting.</p><h5><strong>2. SCIEX: Advancing Proteomics with ZenoTOF: From Single-Cell Analysis to Plasma Biomarker Discovery</strong></h5><ul><li>Tu, 30.6.2026 11:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6311">Registration</a></li></ul><p>Discover how ZenoTOF high-resolution mass spectrometry is accelerating single-cell proteomics and plasma biomarker discovery through enhanced sensitivity, throughput, and automation.</p><h5><strong>3. Agilent Technologies: Measuring Diverse Samples with UV/VIS Spectrometers and Integrating Spheres</strong></h5><ul><li>Tu, 30.6.2026 20:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6052">Registration</a></li></ul><p>This webinar will discuss diffuse transmission and reflection UV/VIS measurements, including how to perform measurements with Agilent’s Cary 60 UV/VIS Spectrometer.</p><h5><strong>4. Waters Corporation: Informatics series #33 Tips, Tricks and Best Practices</strong></h5><ul><li>Th, 2.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6315">Registration</a></li></ul><p>This interactive session revisits essential features, shortcuts, and practical techniques in Empower software that can streamline everyday laboratory work and reduce unnecessary effort.</p><h5><strong>5. Waters Corporation: Unlocking Therapeutic Peptide Characterisation (GLP-1RAs) with Cyclic IMS</strong></h5><ul><li>Th, 2.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6313">Registration</a></li></ul><p>Discover how cyclic ion mobility spectrometry (cyclic IMS) improves characterization of GLP-1 analogues and therapeutic peptides, supporting development, quality control, and regulatory submissions.</p><h5><strong>6. Agilent Technologies: Spectral Flow Cytometry Masterclass - Session 1</strong></h5><ul><li>Fr, 3.7.2026 07:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6316">Registration</a></li></ul><p>Learn how full-spectrum flow cytometry enables high-dimensional cell analysis. Explore spectral flow technology, experimental design, and applications in immunology, oncology, and vaccine research.</p>

Webinars LabRulezLCMS Week 27/2026

News from LabRulezLCMS Library - Week 27, 2026

<p><strong>This study compares a commercial ELISA assay with a validated UHPLC-MS/MS method for determining total ergot alkaloids in wheat and durum samples. In addition to method performance, the authors investigated cross-reactivity and matrix effects to explain differences between immunoassay and chromatographic results.</strong></p><p>While ELISA demonstrated good repeatability and is well suited for high-throughput screening, systematic biases were observed due to compound- and matrix-dependent cross-reactivity. The findings support ELISA as an effective screening tool, whereas UHPLC-MS/MS remains the preferred method for accurate quantification and regulatory confirmation of ergot alkaloids.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.jafc.6c05234"><strong>Comparative Evaluation of Total Ergot Alkaloids Determination by ELISA and UHPLC-MS/MS in Wheat: Implications of Cross-Reactivity and Matrix Effects</strong></a></h4><p>Chamali Kodikara*, Dainna Drul, Nandika Bandara, and Sheryl A. Tittlemier*</p><p>J. Agric. Food Chem. 2026, 74, 25, 20015–20027</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.jafc.6c05234">https://doi.org/10.1021/acs.jafc.6c05234</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Ergot alkaloids (EAs) are a structurally diverse group of indole-derived mycotoxins produced primarily by phytopathogenic fungi of the genus <i>Claviceps</i>, most notably <i>Claviceps purpurea</i>. These fungi infect the flowering heads of cereal crops, replacing the developing grain with hardened fungal structures (sclerotia) that contain ergot alkaloids. Cereals such as rye, wheat, barley, oats, and triticale are particularly susceptible, with infection severity strongly influenced by environmental conditions during flowering, including rainfall and humidity. <a href="javascript:void(0);">(1−3)</a> Although improvements in agronomic practices and grain cleaning have reduced the prevalence of visible ergot sclerotia, ergot alkaloids can persist in cereals and cereal-based foods even in the absence of detectable sclerotia. This may occur because sclerotia can fragment during harvesting, handling, cleaning, or milling, producing small particles that are not visually detected but may still contribute ergot alkaloids to grain or processed products, continuing to pose food and feed safety concerns. <a href="javascript:void(0);">(4)</a> <a href="javascript:void(0);">(5)</a> Ergot alkaloids share a common tetracyclic ergoline backbone and occur as structurally related compounds, including ergometrine, ergotamine, ergosine, ergocristine, ergocryptine, and ergocornine, together with their corresponding C-8 epimers. These epimers occur as <i>R-</i> and <i>S-</i>configurations, commonly referred to as -ine and -inine forms, respectively. Epimerization at the C-8 position can occur during fungal metabolism and during sample extraction, storage, and analysis, complicating accurate quantification. <a href="javascript:void(0);">(6,7)</a> Although S-epimers were historically considered biologically inactive, recent evidence indicates that they may contribute to overall exposure and toxicity, supporting their inclusion in analytical and regulatory frameworks. <a href="javascript:void(0);">(3)</a></p><p>Dietary exposure to elevated levels of ergot alkaloids has been associated with a range of adverse health effects, collectively referred to as ergotism, including vasoconstriction, ischemia, neurological disturbances, and hallucinations. <a href="javascript:void(0);">(3)</a> These effects arise primarily from interactions with adrenergic, serotonergic, and dopaminergic receptors. <a href="javascript:void(0);">(8−10)</a> In response, regulatory limits for ergot alkaloids in food have been introduced or revised in several jurisdictions. In the European Union, maximum levels have been established for the sum of 12 ergot alkaloids in cereal milling products under Regulation (EU) 2021/1399, which was subsequently consolidated under Regulation (EU) 2023/915. This sum includes ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, and ergocristine together with their corresponding -inine epimers, increasing the demand for reliable analytical methods to support routine monitoring and enforcement. <a href="javascript:void(0);">(1,11)</a></p><p>Liquid chromatography-tandem mass spectrometry (LC-MS/MS), particularly ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), is widely regarded as the reference technique for confirmatory determination of ergot alkaloids due to its sensitivity, selectivity, and ability to resolve epimeric forms. Recent methods routinely achieve low microgram-per-kilogram limits of quantification across a range of cereal matrices. <a href="javascript:void(0);">(12−17)</a> However, LC-MS/MS approaches are resource-intensive and typically confined to centralized laboratories, limiting their suitability for high-throughput screening or rapid decision-making in grain-handling and quality-control settings. Consequently, rapid screening methods, most notably enzyme-linked immunosorbent assays (ELISAs), are commonly employed as complementary tools to chromatographic analysis. <a href="javascript:void(0);">(18−21)</a> ELISAs offer reduced analysis time, simplified workflows, and lower per-sample costs, making them attractive for preliminary screening and sample triage. <a href="javascript:void(0);">(22−24)</a></p><p>In contrast to other regulated mycotoxins, however, the commercial availability of ELISAs for ergot alkaloids is limited. While multiple kits have been evaluated, performance has varied substantially across assays and matrices. <a href="javascript:void(0);">(1)</a> At present, the Randox Food Diagnostics Ergot Alkaloids ELISA is the only widely marketed microplate ELISA that quantifies the sum of 12 major ergot alkaloids, comprising ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, and ergocristine together with their corresponding -inine epimers, consistent with the analyte scope used for EU maximum levels for ergot alkaloids in specified cereal products. <a href="javascript:void(0);">(25)</a></p><p>In addition, cereal matrix effects may influence antibody binding and signal generation, potentially resulting in biased quantification relative to LC-MS/MS reference methods. These limitations are particularly relevant given the compositional variability of ergot alkaloids across cereal species, geographic regions, and growing conditions. <a href="javascript:void(0);">(12)</a> Recent reviews emphasize the need for systematic, matrix-specific evaluation of immunoassay performance before such methods can be confidently integrated into regulatory or industrial monitoring programs. <a href="javascript:void(0);">(1,6,11)</a> However, independent evaluations of commercially available ergot alkaloid ELISAs, particularly those benchmarked against validated UHPLC-MS/MS methods using naturally infested wheat samples, remain limited.</p><p>In this context, we hypothesized that measurements of total ergot alkaloids obtained using a commercially available ELISA are influenced by matrix effects and antibody cross-reactivity, resulting in systematic differences compared to UHPLC-MS/MS, which provides compound-specific quantification. To test this, the objective of the present study was to conduct a comprehensive performance evaluation of a commercially available ELISA for the detection of ergot alkaloids in wheat, using UHPLC-MS/MS as a reference method. Specific aims included assessment of repeatability and intermediate precision, extraction efficiency and extract stability, the influence of test portion mass, method accuracy relative to UHPLC-MS/MS, and characterization of antibody cross-reactivity toward individual ergot alkaloids in both solvent and wheat matrix. The results provide data-driven guidance on the appropriate use of ELISA-based screening within tiered analytical strategies for regulatory monitoring and food safety decision-making.</p><h4><strong>2. Materials and Methods</strong></h4><h5><strong>2.3. UHPLC-MS/MS Reference Method</strong></h5><p>UHPLC-MS/MS analysis of ergot alkaloids was performed using the validated Canadian Grain Commission (CGC) method described by Tittlemier et al. (2015). Briefly, ground grain (10 g) was extracted with 50 mL of acetonitrile/aqueous ammonium carbonate (84:16, v/v; 3.03 mM ammonium carbonate) to provide alkaline extraction conditions, then shaken for 30 min and centrifuged at 2450<i>g</i> for 10 min at room temperature. An aliquot of extract (464 μL) was combined with internal standard solution (dihydroergotamine; 20 μL of 4 ng/μL) and aqueous ammonium carbonate (1536 μL), vortex-mixed, and filtered through a 0.45 μm polytetrafluoroethylene syringe filter before injection into the UHPLC-MS/MS system. As in the validated reference method, dihydroergotamine was added after extraction to correct for postextraction analytical variability; extraction recovery was evaluated during method validation. Chromatographic separation was achieved using a reversed-phase <strong>BEH C18 column</strong> (2.1 × 100 mm, 1.7 μm; Waters, Milford, MA, USA) with the autosampler maintained at 15 °C and the column at 30 °C. Mobile phases consisted of (A) 3.03 mM aqueous ammonium carbonate and (B) acetonitrile. The gradient program was as follows: initial, 75% A/25% B; 1.00 min, 60% A/40% B; 5.00 min, 40% A/60% B; 8.00 min, 22% A/78% B; 10.50–11.00 min, 10% A/90% B; and 13.00–16.00 min, 75% A/25% B, with a total run time of 16 min. Detection was performed using positive electrospray ionization in multiple reaction monitoring mode on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/554"><strong>Waters Xevo triple quadrupole mass spectrometer</strong></a> (Waters, Milford, MA, USA). Under the validated chromatographic conditions, dihydroergotamine did not coelute with ergotamine, ergotaminine, or the other target ergot alkaloids. Identification and quantification were based on retention-time criteria and compound-specific MRM transitions, thereby minimizing potential isotopic or coelution interference. Precautions to minimize epimerization, including controlled handling of standards and extracts and reduced light exposure, were followed as described in the reference method. UHPLC-MS/MS quantification was performed using analyte-specific, matrix-matched calibration curves prepared according to the validated CGC reference method, with calibration levels of 0.046, 0.2, 1, 2, 10, and 20 μg/kg. Dihydroergotamine was used as the internal standard, and concentrations were calculated from internal-standard-normalized analyte responses with method dilution factors applied. Total ergot alkaloid concentration was calculated as the arithmetic sum of all quantified ergot alkaloids and epimers included in the validated method. <a href="javascript:void(0);">(26)</a></p><h4><strong>3. Results and Discussion</strong></h4><h5><strong>3.4. Comparison of ELISA and UHPLC-MS/MS Results</strong></h5><p>For method comparison, UHPLC-MS/MS was used as the chemical reference method, providing compound-specific quantification of individual ergot alkaloids and their epimers. A total ergot alkaloid concentration was calculated as the arithmetic sum of all quantified alkaloids included in the method. This summed value represents a chemically defined total based on compound-specific quantification of each analyte, rather than an immunoreactivity-weighted response governed by antibody affinity. As such, the UHPLC-MS/MS total serves as a chemically defined comparator against which the immunoreactivity-weighted ELISA response can be interpreted. Agreement between the commercial ELISA and the validated UHPLC-MS/MS reference method was evaluated using wheat and durum wheat cargo samples (<i>n</i> = 102) collected over multiple crop years (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.jafc.6c05234#fig5">Figure 5</a>). Linear regression analysis demonstrated a positive association between ELISA and UHPLC-MS/MS results across the full concentration range, indicating that the ELISA was responsive to increasing ergot alkaloid levels. However, the regression slope deviated substantially from unity, with ELISA results systematically lower than UHPLC-MS/MS values, indicating an approximate 2-fold underestimation.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_5_Linear_regression_analysis_comparing_total_ergot_alkaloid_concentrations_determined_by_ELISA_and_UHPLC_MS_MS_5d7b5c5c61.jpeg" alt="J. Agric. Food Chem. 2026, 74, 25, 20015–20027: Figure 5. Linear regression analysis comparing total ergot alkaloid concentrations determined by ELISA and UHPLC-MS/MS for wheat and durum wheat cargo samples (n = 102). Each point represents the mean of duplicate measurements (extracted from the same test portion) ELISA determinations for an individual cargo sample, plotted against the corresponding UHPLC-MS/MS result. Statistical analysis was performed using linear regression." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_5_Linear_regression_analysis_comparing_total_ergot_alkaloid_concentrations_determined_by_ELISA_and_UHPLC_MS_MS_5d7b5c5c61.jpeg 197w," sizes="100vw" width="992" height="784"></p><p>Bland-Altman analysis confirmed this proportional bias, showing a consistent negative mean difference between ELISA and UHPLC-MS/MS results across the concentration range (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.jafc.6c05234#fig6">Figure 6</a>). Importantly, the magnitude of disagreement did not increase randomly with concentration; rather, it reflected a systematic offset, indicating that the discrepancy was not driven by analytical imprecision or outliers but by fundamental differences in method response characteristics. This pattern indicates method-level bias rather than random analytical variability, which may arise from combined workflow effects including extraction, matrix response, and immunochemical cross-reactivity. The magnitude of the ELISA-UHPLC-MS/MS bias was substantially greater than the intermediate precision observed for the ELISA quality-control material, supporting the interpretation that the disagreement reflects systematic differences in method response rather than insufficient ELISA repeatability. Such behavior is well documented when immunoassays are compared with chromatographic methods for complex mycotoxin mixtures, including ergot alkaloids and other structurally diverse mycotoxins in cereals and feed. <a href="javascript:void(0);">(28,30,33)</a> These studies consistently report matrix- and profile-dependent bias in ELISA relative to LC-MS/MS, arising from differential antibody cross-reactivity and the summed immunoreactivity response of the assay, because ELISA produces an immunoreactivity-weighted total that depends on antibody affinity toward individual alkaloids and their relative abundance in the sample, whereas UHPLC-MS/MS quantifies compound-specific concentrations of each alkaloid and its epimers using compound-specific transitions and response factors, and total ergot alkaloid concentration is calculated as the sum of these targeted analytes. In contrast, ELISA produces an immunoreactivity-weighted total, determined by antibody affinity toward individual alkaloids and their competitive binding behavior within the assay format. Consequently, agreement between ELISA and UHPLC-MS/MS depends not only on total concentration, but also on the relative distribution of individual alkaloids within each sample. Although differences in extraction solvent composition and pH may influence ergot alkaloid recovery, stability, and epimeric distribution, each method was applied according to its intended analytical workflow. The ELISA was performed using the manufacturer-recommended acidic methanol/water extraction, whereas UHPLC-MS/MS was performed using the validated acetonitrile/aqueous ammonium carbonate extraction procedure. Therefore, the comparison reflects the performance of the complete methods as used in practice, rather than an isolated comparison of extraction solvents. The sequential extraction experiment further showed that repeating the ELISA extraction under the same kit conditions did not substantially increase the ELISA-measured response, supporting the adequacy of the kit extraction within the ELISA workflow while recognizing that it does not directly compare acidic and ammonium carbonate-based extraction conditions. Previous ELISA-LC-MS/MS comparison studies for ergot alkaloids have reported both under- and overestimation depending on assay design and matrix, including differences in alkaloid profile, cereal type, and antibody cross-reactivity. Turner et al. observed substantial overestimation of ergot alkaloids by ELISA relative to HPLC in rye field samples, attributed to strong antibody cross-reactivity toward alkaloids prevalent in rye matrices. Similar profile-dependent bias has also been reported in interlaboratory and method-comparison studies, <a href="javascript:void(0);">(33)</a> demonstrating that this behavior is not unique to a single data set.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_6_Bland_Altman_plot_comparing_ELISA_and_UHPLC_MS_MS_measurements_of_total_ergot_alkaloids_1be40cce50.jpeg" alt="J. Agric. Food Chem. 2026, 74, 25, 20015–20027: Figure 6. Bland-Altman plot comparing ELISA and UHPLC-MS/MS measurements of total ergot alkaloids for wheat and durum wheat cargo samples (n = 102)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_J_Agric_Food_Chem_2026_74_25_20015_20027_Figure_6_Bland_Altman_plot_comparing_ELISA_and_UHPLC_MS_MS_measurements_of_total_ergot_alkaloids_1be40cce50.jpeg 230w," sizes="100vw" width="1437" height="977"></p><p>This study provides a comprehensive evaluation of a commercially available ELISA for total ergot alkaloids, using wheat samples as the primary application matrix, and integrates performance metrics with mechanistic insights into method behavior. While the assay demonstrated strong repeatability, calibration stability, and robustness to procedural factors such as test portion mass and extraction conditions, systematic differences relative to UHPLC-MS/MS were consistently observed. By linking these differences to compound-specific antibody cross-reactivity and matrix-dependent signal modulation, this work clarifies that ELISA-derived results reflect an immunochemically weighted response rather than a stoichiometric total. This distinction is critical for the appropriate interpretation of ELISA data and supports its use within tiered analytical strategies as a rapid screening tool, complemented by UHPLC-MS/MS for confirmatory quantification and regulatory decision-making.</p></div>

Comparative Evaluation of Total Ergot Alkaloids Determination by ELISA and UHPLC-MS/MS in Wheat: Implications of Cross-Reactivity and Matrix Effects

<p><strong>In the week of July 6, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Waters Corporation: Characterizing Next-Generation Antibody Therapeutics: LC Strategies for Multispecifics, ADCs &amp; AOCs</strong></h5><ul><li>Tu, 7.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6317">Registration</a></li></ul><p>In this webinar, we share a pragmatic characterization roadmap using LC-based methods across intact, subunit, and peptide-mapping workflows.</p><h5><strong>2. Separation Science: Advances in Antibiotic Extraction from Water: An Automated SPE Approach</strong></h5><ul><li>We, 8.7.2026 09:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6319">Registration</a></li></ul><p>Streamline water analysis workflows and gain practical insights for modern environmental monitoring.</p><h5><strong>3. SCIEX: Analysis of per- and polyfluoroalkyl substances (PFAS) in food substances using LC-MS/MS solutions</strong></h5><ul><li>We, 8.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6322">Registration</a></li></ul><p>Master PFAS analysis in food safety. Learn how SCIEX LC-MS/MS solutions and QTRAP workflows overcome analytical challenges to ensure accurate and compliant result confirmation.</p><h5><strong>4. Wiley: From liquids to solids: expand what your UV-Vis-NIR Spectrometer can do</strong></h5><ul><li>We, 8.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6367">Registration</a></li></ul><p>Discover how the Agilent Cary UV-Vis-NIR spectrometer, together with Specac accessories, enables reliable analysis of liquids, powders, films, pellets, and highly scattering solid samples.</p><h5><strong>5. Thermo Fisher Scientific: Advanced tools to maximize your sample throughput with Chromeleon Software and Vanquish UHPLC</strong></h5><ul><li>Th, 9.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6326">Registration</a></li></ul><p>Learn how Chromeleon software and the Vanquish Duo UHPLC system streamline sample analysis, automate routine workflows, increase throughput, and reduce errors through practical demonstrations.</p><h5><strong>6. Bruker: 4D-Metabolomics™ in Action: Real-World Strategies for Deep Discovery and Confident Annotation</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6328">Registration</a></li></ul><p>Explore how next-generation mass spectrometry technologies, ion mobility, and computational tools are helping researchers move from complex datasets to confident insight.</p><h5><strong>7. Waters Corporation: Cracking the Code on Nitrogen Methods</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6327">Registration</a></li></ul><p>Learn the fundamentals of nitrogen analysis for wastewater testing. Explore analytical methods, QA/QC, sample handling, compliance reporting, and troubleshooting for accurate environmental monitoring.</p><h5><strong>8. SelectScience: Next-generation metabolomics: From annotation to discovery at scale</strong></h5><ul><li>Th, 9.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6281">Registration</a></li></ul><p>Explore how next-generation mass spectrometry, ion mobility, and advanced computational tools accelerate confident small-molecule annotation and discovery in metabolomics.</p><h5><strong>9. SCIEX: LC-MS/HRMS Approaches for Monitoring Organic Micropollutants in Wastewater and Environmental Systems</strong></h5><ul><li>Fr, 10.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6370">Registration</a></li></ul><p>Discover how advanced LC-MS/HRMS workflows enable trace-level detection of organic micropollutants, suspect and non-target screening, and environmental monitoring of wastewater systems.</p>

Webinars LabRulezLCMS Week 28/2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 6th July 2026? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies </strong>and<strong> Metrohm </strong>and posters by<strong> Shimadzu/ASMS, Thermo Fisher Scientific/ASMS </strong>and <strong>Waters Corporation/ASMS!</strong></p><h3><strong>1. Agilent Technologies: Determination of 41 Per- and Polyfluoroalkyl Substances (PFAS) in Cosmetics</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_captiva_emr_pfas_food_ii_cartridge_5994_9111en_agilent_be91861646.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Per- and polyfluoroalkyl substances (PFAS) are synthetic compounds composed of highly stable carbon–fluorine (C–F) bonds, giving them exceptional thermal and chemical stability, leading to poor environmental degradability. PFAS have been used in cosmetics to provide water resistance, oil repellency, or application smoothness. The unintentionally presented PFAS residues in raw materials may remain in finished cosmetic products, and can be absorbed through the skin. Lip products and spray type products can also lead to inhalation or oral exposure to residues.<sup>1,2</sup>&nbsp;</p><p>Agilent Captiva EMR PFAS Food cartridges are designed to provide streamlined and comprehensive matrix removal after QuEChERS extraction for complex sample matrices, demonstrating effective matrix cleanup efficiency and excellent performance for quantitative PFAS analysis.<sup>3,4</sup> In this study, we performed QuEChERS extraction followed by cleanup with Captiva EMR PFAS Food II cartridges for PFAS analysis in five types of cosmetics.</p><h4><strong>Experimental</strong></h4><h5><strong>Equipment and materials&nbsp;</strong></h5><p>The study was performed using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+III"><strong>Agilent 1290 Infinity III LC</strong></a> system consisting of an Agilent 1290 Infinity III high-speed pump (G7120A), an Agilent 1290 Infinity III multisampler (G7167B), and an Agilent 1290 Infinity III multicolumn thermostat (G7116B). The LC system was coupled to an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6495D"><strong>Agilent 6495D triple quadrupole LC/MS system</strong></a> (G6495D) equipped with an Agilent Jet Stream Electrospray ion source. Agilent MassHunter Workstation software was used for data acquisition and analysis.&nbsp;</p><p>The 1290 Infinity III LC system was modified using an Agilent InfinityLab PFAS Analysis HPLC conversion kit (part number 5004-0006), including an Agilent InfinityLab PFC delay column, 4.6 × 30 mm (part number 5062-8100). Chromatographic separation was performed using an Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=ZORBAX+RRHD+Eclipse+Plus"><strong>ZORBAX RRHD Eclipse Plus</strong></a> C18, 95 Å, 2.1 × 100 mm, 1.8 µm (part number 959758-902).</p><h4><strong>Results and discussion&nbsp;</strong></h4><h5><strong>Chromatography and calibration curve linearity&nbsp;</strong></h5><p>Figure 2 shows the overlaid chromatograms for 41 PFAS calibration standards, including 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, and 10.0 ng/mL in ACN. The table on the right shows the peaks identification and corresponding retention time. Across 41 PFAS compounds, R² values ranged from 0.9940 to 0.9998, indicating excellent linearity for all analytes' calibration curves across the calibration range of 0.05 to 10.0 ng/mL.</p><h5><strong>PFAS detection in real cosmetic samples&nbsp;</strong></h5><p>Of the 15 cosmetic products assessed, one eyeshadow sample was detected with a trace level of positive PFAS analytes, including PFHeA, PFHpA, PFNA, and PFOA, at about 0.1 ng/g in the sample. Figure 5 shows the method blanks and positive detection of PFHpA and PFNA in this eyeshadow&nbsp;product.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>A simplified, rapid, and reliable method using QuEChERS extraction followed by EMR mixed-mode passthrough cleanup using the Agilent Captiva EMR PFAS Food II cartridge and LC/MS/MS detection was developed for 41 PFAS analysis in cosmetics.</p><h3><strong>2. Metrohm: brightRC – Advanced brightener analysis with a response curve</strong></h3><p><strong>Next-level brightener determination in nonlinear systems</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_v_242_download_83376b2923.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>WHAT IS BRIGHTRC?&nbsp;</strong></h4><p>brightRC is a response curve calibration approach for the determination of brightener-type additives by CVS or CPVS (Cyclic Pulse Voltammetric Stripping), hence the name «brightRC». This technique is suitable to measure brightener content in copper baths for plating. The method is based on signal normalization using the electrolyte value, which is the response for the virgin makeup solution (VMS) saturated with suppressor, and brightener defined as Q0 in the viva software. All recorded signals are divided by Q0 and the normalized values are plotted against concentration to generate an external calibration curve. This calibration can then be used for routine sample determination without repeated standard additions.&nbsp;</p><p>The sample is simply measured using the same method as the calibration, signals are normalized and evaluated using the mathematically fitted calibration curve. By decoupling calibration from sample measurement, brightRC removes the need for repeated standard additions with each sample measurement, enabling faster and more efficient routine analysis.&nbsp;</p><p>The brightRC calibration approach supports flexible regression models including quadratic and nonlinear regression. This allows reliable quantification of additive systems that do not exhibit a wide linear working range or exhibit nonlinear response characteristics, thereby expanding the range of applicable brightener chemistries.&nbsp;</p><p>One important detail that further differentiates brightRC from the MLAT approach relates to normalization of the signal for calibration and sample analysis. This normalization approach improves measurement robustness as variations in absolute signal intensity naturally occurring over the working day are mathematically compensated.</p><h4><strong>HOW DOES BRIGHTRC WORK IN PRACTICE?&nbsp;</strong></h4><p>The brightRC workflow separates calibration and sample analysis. It can be implemented in different setups (from manual to fully automated) depending on the additive system and concentration range. After recording the electrolyte value, calibration standards are measured to establish the calibration curve, otherwise known as the response curve. Once the calibration is stored, samples are determined with the same CVS or CPVS method, without further standard additions. The sample concentration is automatically calculated from the normalized signal using the calibration curve.&nbsp;</p><p>For sample measurement, viva 4.0 provides two practical approaches:&nbsp;</p><ol><li>«brightRC with solution exchange»&nbsp;</li><li>«brightRC with sample dilution» Both variants follow the same calibration principle and differ only in the sample handling strategy.</li></ol><h4><strong>WHEN TO USE BRIGHTRC?&nbsp;</strong></h4><p>brightRC is ideal for routine brightener control in stable plating baths where high sample throughput is required. It is particularly suitable when matrix conditions are consistent and electrode fouling is limited. The approach is especially advantageous for additive systems exhibiting nonlinear signal behavior. If strong matrix variations, significant breakdown products, or severe electrode fouling are expected and a linear correlation between signal and analyte concentration is guaranteed, standard addition techniques such as MLAT are preferred because they may provide additional robustness.</p><h3><strong>3. Shimadzu / ASMS: PFAS Analysis of Leachate: Evaluating Key Sample Preparation and LC–MS/MS Parameters for Improved Performance</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/WP_255_PFAS_Analysis_of_Leachate_Evaluating_Key_Sample_Preparation_and_LC_MSMS_Parameters_for_Improved_Performance_1114ee264c.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Landfill leachate is a highly complex and variable matrix that poses significant challenges for the analysis of per- and polyfluoroalkyl substances (PFAS). Although U.S. Environmental Protection Agency Method 1633A provides a standardized framework for PFAS quantitation,1 analytical performance remains strongly influenced by sample preparation, chromatographic separation, and mass spectrometric conditions. Landfill leachate samples were extracted using WAX SPE following EPA 1633A and analyzed by LC–MS/MS using a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8060"><strong>Shimadzu LCMS-8060</strong></a><strong> </strong>under negative ESI conditions. This study evaluates the key factors governing LC–MS/MS sensitivity, signal response, and reproducibility in landfill leachate, including a systematic assessment of SPE, chromatographic behavior, and ionsource conditions across PFAS classes (Figure 1).</p><h4><strong>Results&nbsp;</strong></h4><p>Chromatographic performance was evaluated across four C18 columns (A–D) using peak area, height, asymmetry, and HETP. Two columns produced a higher signal and improved peak shape, while the remaining columns showed greater efficiency. Under repeated batches followed by storage in acetonitrile, the Shimadzu GIST column produced a consistent signal (≤15% change), whereas another column showed 20–50% signal loss, particularly for long-chain PFAS and precursors, indicating greater susceptibility to matrix accumulation (Figure 2).</p><h4><strong>Conclusion&nbsp;</strong></h4><ul><li>PFAS analytical performance was dependent on compoundclass-dependent extraction, chromatography, and ionization behavior.&nbsp;</li><li>GIST demonstrated lower signal variability under repeated matrix exposure, with lower signal degradation than alternative C18 phases.</li><li>Neutral PFAS showed poor retention on WAX sorbents, requiring optimization beyond standard EPA 1633A extraction conditions.&nbsp;</li><li>PFCA response was more influenced by gas flow conditions, whereas PFSA response was more sensitive to source temperature conditions.</li></ul><h3><strong>4. Thermo Fisher Scientific / ASMS: Ultra-high throughput proteomics at &gt;500 samples/day using advanced </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/398"><strong>Vanquish Neo UHPLC</strong></a><strong> methods with </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1959"><strong>Orbitrap Astral Zoom MS</strong></a></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004708_lsms_ultra_high_throughput_vanquish_astral_proteomics_po004708_asms2026_na_en_f6499c3eec.pdf"><strong>Full PDF for download</strong></a></li></ul><p>High-throughput mass spectrometry is increasingly critical for large-cohort proteomics, population-scale studies, and screening applications. While established LC–MS platforms routinely support several hundred samples per day, further increases in throughput are often limited by chromatographic stability, robustness, and reproducibility under ultra-short gradient conditions, as well as the acquisition speed of the mass spectrometer. Here, we describe an advanced ultra-high-throughput LC–MS methodology developed on the Thermo Scientific Vanquish Neo UHPLC system and Thermo Scientific Orbitrap Astral Zoom mass spectrometer. The goal of this work was to extend the practical throughput limits of LC–MS while achieving deep proteome coverage and maintaining run-to-run reproducibility.</p><h4><strong>Materials and methods</strong></h4><h5><strong>LC-MS analysis&nbsp;</strong></h5><p>Samples were separated on a Thermo Scientific 150 µm × 70 mm C18 column (prototype, not commercially available yet) operated at 4 µL/min using a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/398"><strong>Vanquish Neo UHPLC system</strong></a> in NanoCap Trap&amp;Elute configuration at room temperature. Prototype methods allowing for reduced LC duty cycles (approx. 1 min of sample pickup/loading and integrated trap-column offline wash) were applied, the standard gradients were adjusted to 1 – 3 min. The Thermo Scientific PepMap Neo 5 µm C18 300 µm × 5 mm cartridge was used as trap column and the separation column connected with a 15 µm ID capillary Thermo Scientific EASY-Spray emitter (ES994) to an EASY-Spray source. The <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1959"><strong>Orbitrap Astral Zoom MS</strong></a> (ICSW AST 2.2) was operated in a dataindependent acquisition (DIA) mode, MS method parameters are given in Table 1. Comparative data for the chemoproteomics samples at lower throughputs (60-300 SPD) were acquired using an EASY-Spray 150 µm × 150 mm C18 column (ES906), as described before.&nbsp;</p><h5><strong>Data analysis&nbsp;</strong></h5><p>The raw data files were processed with Spectronaut® 20.5 software (Biognosys AG), <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1782"><strong>Thermo Scientific Proteome Discoverer </strong></a>3.3 SP1 with <strong>CHIMERYS 5.0 </strong>or DIA-NN Enterprise 2.3.2 (Aptila Biotech GmbH) nodes using default settings as specified in the individual figures. The data was searched against the Homo sapiens SwissProt database (TaxID=9606: 42,252 sequences) and contaminants FASTA file. Peptide numbers correspond to unique stripped peptides</p><h4><strong>Conclusions&nbsp;</strong></h4><ul><li>The advanced Vanquish Neo UHPLC methodology in combination with the Orbitrap Astral Zoom MS delivered highly reproducible, deep and precise proteome profiling across ultra-high-throughput regimes (600 SPD) exceeding current field benchmarks.&nbsp;</li><li>The workflow enables rapid chemoproteomic screening, as demonstrated with activity-based protein profiling (ABPP) samples, reliably identifying enriched putative target proteins of an antibiotic small molecule probe.</li></ul><h3><strong>5. Waters Corporation / ASMS: Assessing Relative Response of Four European-Regulated PFAS in Human Serum Using Cyclic Ion Mobility MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009410_c98e7c87ec.pdf"><strong>Full PDF for download</strong></a></li></ul><div><div><section><div><div><div><div><div><div><p>The poster presents an LC-Cyclic-IMS-MS approach for assessing four European-regulated PFAS—PFOS, PFOA, PFNA, and PFHxS—in human serum. The study focuses on environmental exposure monitoring in Ghanaian firefighters and e-waste handlers, using ion mobility mass spectrometry to add separation power and improve identification confidence in complex biological matrices. The work is motivated by increasing regulatory concern around PFAS toxicity, bioaccumulation, and the need for reliable exposure assessment in human biofluids.</p><p>The experimental workflow combined reversed-phase LC with a quadrupole-cyclic ion mobility-time-of-flight MS system (<a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/202"><strong>SELECT SERIES</strong> <strong>Cyclic IMS</strong></a>). Human serum samples were prepared using SPE µElution plates with a polymeric reversed-phase/weak anion exchange sorbent. The LC system was modified with PFAS-free components and an isolator column to reduce background contamination, which is especially important for trace-level PFAS analysis. Identification was supported by retention time, accurate mass, isotopically labelled internal standards, and collision cross section values.</p><p>The results showed detectable levels of the four regulated PFAS in both occupational groups, with a combined detection rate of 83% across human serum samples and NIST reference standards. Firefighter samples generally showed higher concentration ranges than e-waste handler samples, especially for PFOS, PFOA, PFNA, and PFHxS. For example, PFNA reached up to 5.713 ng/mL in firefighter serum, compared with up to 1.513 ng/mL in e-waste handler serum.</p><p>Overall, the poster concludes that LC-Cyclic-IMS-MS provides a highly specific strategy for PFAS analysis in complex biological samples. Ion mobility and CCS values improve confidence in trace-level identification and help distinguish target PFAS from co-eluting matrix background. The authors suggest that this approach can support both targeted PFAS monitoring and broader non-targeted screening of known and emerging PFAS, while also helping future studies connect exposure data with environmental fate and potential toxicological effects.</p></div></div></div></div></div></div></section></div></div>

News from LabRulezLCMS Library - Week 28, 2026

<p><strong>In the week of July 13, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. GERSTEL: Automated SPE Sample Preparation for PFAS and Ultra-Short-Chain PFAS in Aqueous Matrices</strong></h5><ul><li>Tu, 14.7.2026 14:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6329">Registration</a></li></ul><p>Learn how laboratories automate SPE sample preparation for PFAS and ultra-short-chain PFAS in aqueous matrices to obtain cleaner extracts ready for LC-MS/MS analysis.</p><h5><strong>2. Phenomenex: Under Pressure: Mastering Backpressure in HPLC</strong></h5><ul><li>We, 15.7.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6330">Registration</a></li></ul><p>Master HPLC backpressure troubleshooting. Learn how column dimensions, tubing, mobile phases, and sample matrices influence system pressure and how to resolve common issues.</p><h5><strong>3. SCIEX: PFAS in Pharmaceuticals</strong></h5><ul><li>We, 15.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6332">Registration</a></li></ul><p>Master PFAS analysis in pharmaceutical workflows. Learn analytical strategies and contamination control for sensitive detection in APIs and packaging materials.</p><h5><strong>4. Thermo Fisher Scientific: Characterizing Complex Biotherapeutics Based on New Modalities: Uncover New LC-MS Workflow Strategies</strong></h5><ul><li>We, 15.7.2026 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6331">Registration</a></li></ul><p>Resolve complex oligonucleotide impurities. Learn how inert UHPLC flow paths and Orbitrap MS minimize metal adducts and improve chromatographic separation for ASO therapeutics.</p><h5><strong>5. Waters Corporation: Does Chromatography Still Matter? The Critical Role of UPLC in Clinical LC-MS/MS Performance</strong></h5><ul><li>We, 15.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6371">Registration</a></li></ul><p>Discover why LC remains essential in clinical LC-MS/MS workflows and how UPLC improves sensitivity, reproducibility, robustness, and analytical confidence in routine clinical testing.</p><h5><strong>6. Unchained Labs: Get Hooked on Automated Buffer Exchange with Lil’ Tuna</strong></h5><ul><li>We, 15.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6383">Registration</a></li></ul><p>See how easily Lil’ Tuna automates buffer exchange and concentration experiments, simplifying sample preparation while improving laboratory efficiency.</p><h5><strong>7. Agilent Technologies: Food Fortification, Measured: The Analytical Testing Behind the Standards</strong></h5><ul><li>Th, 16.7.2026 07:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6336">Registration</a></li></ul><p>Master food fortification testing. Learn how HPLC, LC-MS, and ICP-MS verify micronutrient levels and support compliance with regulatory standards.</p><h5><strong>8. Restek Corporation: PFAS - Analysis of Per- and Polyfluorinated Alkyl Substances</strong></h5><ul><li>Th, 16.7.2026 14:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6384">Registration</a></li></ul><p>Join this webinar to discover practical tips and proven methods for obtaining robust and reproducible PFAS data using Restek analytical solutions.</p><h5><strong>9. Thermo Fisher Scientific: Sterility Testing Remains a Critical Component of Batch Release and Overall Sterility Assurance</strong></h5><ul><li>Th, 16.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6364">Registration</a></li></ul><p>Explore compendial and rapid sterility testing approaches, method selection, media choice, and risk-based strategies to strengthen sterility assurance and support compliant pharmaceutical quality control.</p><h5><strong>10. SciY/Mestrelab Research: No More Boxes on Slides. Examples of Workflow Orchestration and Their Impact from R&amp;D to Production on Demand</strong></h5><ul><li>Th, 16.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6335">Registration</a></li></ul><p>Bridge the gap between laboratory automation and AI. Discover practical workflows for reaction screening, structure verification, and closed-loop experiments.</p><h5><strong>11. SelectScience: Building Confidence at Scale in 4D-Metabolomics with Data Quality, Depth and Connectivity in Focus</strong></h5><ul><li>Fr, 17.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6338">Registration</a></li></ul><p>Scale up your 4D-metabolomics workflows. Learn how timsMetabo and MetaboScape software ensure data quality, confident annotation, and AI-ready digital archives.</p>

Webinars LabRulezLCMS Week 29/2026

Tracking Protein Misfolding and Oligomerization: A Temperature-Controlled Ion Mobility-Mass Spectrometry Approach

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 13th July 2026? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you posters by <strong>Agilent Technologies / ASMS, Shimadzu / ASMS, Thermo Fisher Scientific / HPLC Symposium </strong>and<strong> Waters Corporation / HPLC Symposium </strong>and technical note by<strong> KNAUER!</strong></p><h3><strong>1. Agilent Technologies / ASMS: Intact Protein Analysis in Plasma Using Automated 2D-LC/TOF with Multiple Heart-Cutting</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_intact_protein_mhc_2d_lc_tof_wp_679_asms_2026_en_agilent_edb54f4854.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Direct intact and top-down protein analysis enables comprehensive characterization of proteoforms, post-translational modifications, and fragments that are often lost in bottom-up workflows.1 However, intact mass analysis in complex biological matrices such as whole plasma is challenged by extreme dynamic range and ion suppression, commonly necessitating affinity-based enrichment.&nbsp;</p><p>Here, we demonstrate a non-affinity, orthogonal separation strategy using a 2D-LC/TOF workflow with multi-heart-cutting for native intact protein analysis directly in plasma. Therapeutic monoclonal antibodies (mAbs) trastuzumab and antibody-drug conjugate T-DM1, were used as model systems to evaluate performance.&nbsp;</p><p>The workflow employs an Agilent 1290 Infinity III 2D-LC system for orthogonal separations and precise multiple heart-cutting, coupled to a high-resolution, high-sensitivity Agilent 6230C Accurate Mass TOF LC/MS System.</p><h4><strong>Experimental</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><ul><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+III+2D-LC"><strong>Agilent 1290 Infinity III 2D-LC system </strong></a>comprised the following modules:&nbsp;<ul><li>1290 Infinity III Bio Multisampler with Thermostat (G7137A)&nbsp;</li><li>1290 Infinity III Multicolumn Thermostat (G7116B)&nbsp;</li><li>1290 Infinity III Diode Array Detector (G7117B) with Max-Light cartridge cell (G7117-60020)&nbsp;</li><li>1260 Infinity III Bio Flexible Pump (G7131C)&nbsp;</li><li>1290 Infinity III Bio High-speed Pump (G7132A)&nbsp;</li><li>1290 Infinity Valve Drive (G1170A) with 2D-LC ASM Valve (G5643B)&nbsp;</li><li>Two 1290 Infinity III Valve Drives (G1170A) with multiple heart-cutting valves (G5642-64000) equipped with 40 µL Bio loops&nbsp;</li><li>1290 Infinity III Valve Drive (G1170A) with a 2- position/6-port valve (G4231A) (used as a diverter valve)&nbsp;</li></ul></li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6230C"><strong>Agilent 6230C Accurate Mass TOF LC/MS System</strong></a></li></ul><h5><strong>LC/MS Analysis&nbsp;</strong></h5><p>Data acquisition and analysis were carried out using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=MassHunter+acquisition"><strong>MassHunter acquisition</strong></a> (12.2), <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=BioConfirm"><strong>BioConfirm</strong></a> (12.1) and <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=MassHunter+Qualitative+Analysis"><strong>MassHunter Qualitative Analysis </strong></a>(13.0) software.</p><h4><strong>Conclusions</strong></h4><ul><li>Agilent 2D-LC enables direct native MS analysis of intact proteins from plasma without affinity-based enrichment.&nbsp;</li><li>UV-guided and multiple heart-cutting simplify 2D-LC method development and provide high-resolution isolation of native proteins from complex biological matrices such as plasma.&nbsp;</li><li>The Agilent 6230C Accurate Mass TOF delivers high sensitivity and excellent mass accuracy, enabling confident intact protein characterization under native conditions.</li></ul><h3><strong>2. KNAUER: Mind the pressure in preparative up-scaling – effects of particle size and solvent composition on back pressure</strong></h3><ul><li>Technical note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/VTN_0051_knauer_mind_the_pressure_in_preparative_up_scaling_effects_of_particle_size_and_solvent_comp_12e49884d3.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The back pressure of a chromatographic system is generated by the system components, the capillaries, the column, the solvent, and the applied flow rate. Each system has a maximum pressure which it can sustain, and therefore the pressure must be monitored as it is a limiting factor during method development. The back pressure generated by a column is dependent on the particle size and its length. The development of a preparative method is ideally performed on an analytical scale and after optimization the method is then scaled up to preparative scale.</p><p>As preparative HPLC systems normally have lower maximum pressures, it is important to keep the generated pressure in the range of the later preparative system.&nbsp;</p><p>The larger the particles of the column material are, the lower will be the generated back pressure. With increasing particle size, the resolution is decreasing at the same time. Depending on the separation task, the resolution can be a critical point, and it is important to find the right compromise between resolution and backpressure. Additionally, larger particles are significantly less price intensive, which is another factor to be considered especially for large scale purifications. Often solvent mixtures of water with acetonitrile, methanol or ethanol are used for reverse phased methods. Depending on the organic solvent composition, the generated back pressure differs significantly which could be reduced by changing the solvent composition slightly or the organic solvent if possible. The back pressure generated by the solvent will not or only slightly change during the up-scaling process.&nbsp;</p><p>Here, the influence of particle size, flow rate and solvent composition on the back pressure was evaluated. Further, a practical scale-up was performed to evaluate the values obtained on analytical scale to those in larger scale.</p><h4><strong>User Tips:&nbsp;</strong></h4><ul><li>What is the finale scale you want to operate later?&nbsp;</li><li>What are the pressure limitations of the preparative system?&nbsp;</li><li>Be aware of the solvent back pressure&nbsp;</li><li>Consider particle size not only for best separation&nbsp;</li><li>Consider the flow rate</li></ul><h4><strong>MATERIAL AND METHODS&nbsp;</strong></h4><ul><li><strong>Pump: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2372"><strong>AZURA® P 6.1LHPG</strong></a>, 10 ml, sst&nbsp;</li><li><strong>Autosampler: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2375"><strong>AZURA AS 6.1L</strong></a></li><li><strong>Detector:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2423"><strong>UV AZURA DAD 2.1L&nbsp;</strong></a></li><li><strong>Flow cell: </strong>Pressure proof 10 mm, 10 µl, 300 bar&nbsp;</li><li><strong>Thermostat:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2376"><strong>CT2.1&nbsp;</strong></a></li><li><strong>Columns:&nbsp;</strong><ul><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1633"><strong>Eurospher II 100-5 C18, 150 x 4.6 mm&nbsp;</strong></a></li><li>Eurospher II 100-10 C18, 150 x 4.6 mm&nbsp;</li><li>Eurospher II 100-15 C18, 150 x 4.6 mm&nbsp;</li><li>Eurospher II 100-20/45 C18, 150 x 4.6 mm &nbsp;</li></ul></li><li><strong>Software&nbsp;</strong><ul><li>ClarityChrom 10.1&nbsp;</li><li>ClarityChrom 10.1 PDA extension</li></ul></li></ul><h4><strong>CONCLUSION&nbsp;</strong></h4><p>The back pressures of four C18 150 x 4.6 mm columns, which differed only in particle size were measured and compared at different flow rates and solvent compositions. As expected, the 5 µm column showed the highest and the 20/45 µm column the lowest back pressure at all tested conditions. The pressure curves of ethanol and methanol gradients were similar, with a maximum pressure at approximately 50% solvent. The pressure curve of the acetonitrile gradient differed from the other two, showing the highest pressure at a lower organic solvent content of approximately 35%, after which the pressure dropped. Ethanol showed the highest pressure, followed by methanol and then acetonitrile. Determining the column back pressure at an analytical scale is an important tool during preparative method development. Ideally, if a linear scale up from the analytical to the preparative scale is conducted, the column back pressure should stay the same. This helps to predict if the method can be scaled up to the desired size in terms of back pressure.</p><h3><strong>3. Shimadzu / ASMS: Enhanced Quantification of Emerging UV Filter Contaminants in Drinking Water Using Optimized LC-MS/MS Technique</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/TP_121_Enhanced_Quantification_of_Emerging_UV_Filter_Contaminants_in_Drinking_Water_Using_Optimized_LC_MSMS_Technique_e733c64828.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Ultraviolet (UV) filter chemicals from sunscreens and personal care products are increasingly recognized as emerging contaminants of concern in drinking water1 . Their persistence and reported biological effects highlight the need for sensitive and reliable monitoring approaches2 . The objectives were to optimize quantitation to achieve ppt level detection without offline extraction and assess the occurrence of these compounds in multiple drinking water matrices. In this study, 20 UV filters were analyzed using a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8060RX"><strong>Shimadzu LCMS8060RX triple quadrupole mass spectrometer.</strong></a></p><h4><strong>Conclusion</strong></h4><p>A highly sensitive, precise, and robust direct injection LC–MS/MS method enables sub-ppt to high-ppb quantification of 20 UV filters in drinking water. Overall, the highly sensitive and robust Shimadzu LCMS-8060RX Triple Quadrupole Mass Spectrometer combined with this extraction-free workflow provides a simple, reliable, and high-throughput approach for quantifying emerging UV filters at ng/L concentrations in drinking water.</p><h3><strong>4. Thermo Fisher Scientific / HPLC Symposium: Comparison of biocompatible and inert UHPLC systems for LC-UV quantitation of large RNA</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004752_hplc_vanquish_amplify_metal_sensitive_analyte_analysis_po004752_na_en_ff99cfde49.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Accurate LC-UV analysis of large RNA and oligonucleotide therapeutics requires highly inert chromatographic flow paths because interactions between the negatively charged phosphodiester backbone and metallic surfaces can cause analyte loss, peak broadening, and reduced quantitative sensitivity, particularly at low concentration.&nbsp;</p><p>Here, an inert UHPLC system – Vanquish Amplify system, incorporating inert-coated flow path components was evaluated against a biocompatible UHPLC configuration using MP35N alloy capillaries and additionally against a commercially available inert UHPLC platform. Large RNA fragments of 500 and 5000 nucleotides were analyzed by IP-RPLC to assess the difference between these systems. To further investigate flow path interactions, adenosine 5′- (α,β-methylene) diphosphate (AMPcP), a metal-sensitive analyte, was analyzed alongside adenosine, a noninteracting reference compound.</p><h5><strong>Material and Methods</strong></h5><ul><li><strong>Instrumentation: </strong>Thermo Scientific Vanquish Amplify UHPLC system</li><li><strong>Column:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=3&amp;search=SurePac+Oligo"><strong>Thermo Scientific SurePac Oligo RP MDi HPLC column</strong></a>,<br>2.5 µm 2.1 X 50 mm (P/N: 43712-052132</li><li><strong>Data Analysis: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/76"><strong>The Thermo Scientific Chromeleon Software 7.3.2 MUc Chromatography Data System (CDS)</strong></a> was used for all data acquisition and analysis.</li></ul><h4><strong>Conclusions&nbsp;</strong></h4><p>Using AMPcP with the Vanquish Amplify system demonstrated up to a twofold increase in sensitivity compared to systems with MP35N fluidics under conditions where metal interactions are most pronounced&nbsp;</p><p>For large RNA, the Vanquish Amplify UHPLC system delivered 1.25–1.35× higher signal intensity compared to systems with MP35N fluidics, enabling reduced sample consumption and improved quantitative reliability.&nbsp;</p><p>The Vanquish Amplify UHPLC system demonstrated comparable system inertness under the tested conditions for larger RNA fragments (5,000 nt) and slightly better system inertness for smaller fragments (500 nt) in this study than the MaxPeak HPS containing system, based on peak height and area comparisons using an external UV detector</p><h3><strong>5. Waters Corporation / HPLC Symposium: Development and Transfer of Quantitative Analytical Methods using Universal Detectors</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009493_8cbe4c3cc2.pdf"><strong>Full PDF for download</strong></a></li></ul><div><div><section><div><div><div><div><div><div><p>Universal detectors such as <strong>Charged Aerosol Detection (CAD)</strong> and <strong>Evaporative Light Scattering Detection (ELSD)</strong> provide valuable alternatives to traditional LC detectors including UV, fluorescence, and mass spectrometry, particularly for analytes lacking chromophores. Although both detectors are suitable for quantitative analysis, they rely on different detection principles—CAD measures the electrical charge transferred to aerosol particles, whereas ELSD detects light scattered by dried analyte particles. Because both detectors exhibit non-linear responses, quantitative methods typically require calibration models such as log-log linear or quadratic regression rather than conventional linear calibration. The poster discusses key considerations for developing robust quantitative methods and highlights the challenges associated with transferring methods between different universal detection platforms.</p><p>To demonstrate detector transferability, the authors migrated a <strong>HILIC method for sugar analysis in fruit juice</strong> from ELSD to CAD. The separation was performed on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/306"><strong>Waters Arc HPLC System</strong></a> equipped with an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=5&amp;search=XBridge+BEH+Amide"><strong>XBridge BEH Amide</strong></a><strong> (4.6 × 150 mm, 2.5 μm)</strong> column using a water/acetonitrile gradient containing triethylamine. While the chromatographic conditions remained unchanged, CAD detector parameters were optimized. Both detectors produced highly comparable quantitative performance across a calibration range of <strong>50–1000 μg/mL</strong>, achieving calibration coefficients (R²) above <strong>0.995</strong>, area RSD values below <strong>1.5%</strong>, and nearly identical concentrations of fructose, sorbitol, glucose, and sucrose in an apple juice sample. These results demonstrate that quantitative HILIC methods can be successfully transferred between ELSD and CAD with only detector-specific optimization.</p><p>The poster also evaluates method transfer between different CAD platforms using the <strong>USP Deoxycholic Acid assay</strong>. The method was implemented on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/198"><strong>Waters ACQUITY UPLC H-Class PLUS System</strong></a> with an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1823"><strong>XBridge BEH C18</strong></a><strong> (4.6 × 150 mm, 3.5 μm)</strong> column and compared against a competing LC/CAD system. After scaling the method according to <strong>USP Chapter &lt;621&gt;</strong>, both systems met all USP system suitability requirements, including repeatability and signal-to-noise criteria. Quantitative results for deoxycholic acid and related impurities were virtually identical, confirming that validated CAD methods can be reliably transferred between different vendors' LC/CAD platforms without compromising analytical performance.</p><p>Overall, the study demonstrates that both ELSD and CAD are robust universal detection techniques for quantitative liquid chromatography. While method transfer between identical detector types is generally straightforward, successful migration between ELSD and CAD—or between different CAD systems—requires careful optimization of detector parameters while preserving chromatographic conditions. The presented workflows illustrate that with appropriate calibration and detector tuning, laboratories can achieve equivalent sensitivity, precision, and quantitative accuracy, facilitating method standardization and transfer across analytical platforms.</p></div></div></div></div></div></div></section></div></div>

News from LabRulezLCMS Library - Week 29, 2026

<p><strong>This study presents an advanced hydrogen–deuterium exchange mass spectrometry (HDX-MS) workflow that enables quantitative determination of small-molecule–protein binding affinities with residue-level resolution. By combining HDX-MS/MS, electron capture dissociation, and ligand titration experiments, the method estimates apparent dissociation constants at the global, peptide, and individual amino acid levels.</strong></p><p>The approach provides spatially resolved affinity measurements while taking advantage of automated HDX-MS workflows for sample handling and data analysis. It offers a scalable platform for mapping ligand–protein interactions and supports structure–activity relationship studies in drug discovery and biopharmaceutical research.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/jasms.6c00020"><strong>Residue-Level Determination of Small-Molecule–Protein Affinities by Hydrogen–Deuterium Exchange Mass Spectrometry</strong></a></h4><p><span>De Lin, Luma Godoy Magalhaes, Joel McMillan, Thomas C. Eadsforth, Greg Stewart, Kieran R. Cartmill, Vincent L. G. Postis<strong>*</strong>, and<strong> </strong>Glenn R. Masson<strong>*</strong></span></p><p>J. Am. Soc. Mass Spectrom. 2026, 37, 6, 1391–1401</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/jasms.6c00020">https://doi.org/10.1021/jasms.6c00020</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Hydrogen–Deuterium Exchange Mass Spectrometry (HDX-MS) has emerged as a key technique in structure-based drug discovery, enabling a rapid characterization of protein–ligand interactions and conformational dynamics in both biopharmaceutical and small molecule development. <a href="javascript:void(0);">(1−8)</a> Typically, HDX-MS studies follow a “bottom-up” workflow in which the therapeutical target is incubated with a saturating concentration of ligand in the presence of a deuterated buffer for a series of defined time points. Hydrogen–deuterium exchange is then quenched, and the protein chemically denatured. The denatured protein is then proteolytically digested, and the resulting peptides are analyzed by LC–MS to determine the extent of deuterium incorporation across their sequences. <a href="javascript:void(0);">(9)</a> These resulting data provide peptide-level spatial resolution, typically 5–35 amino acids, allowing the identification of regions stabilized or shielded from the solvent upon ligand binding. <a href="javascript:void(0);">(10)</a> Higher resolution, including single-residue resolution, can be achieved computationally, especially when high peptide redundancy and sequence coverage is obtained. <a href="javascript:void(0);">(11−13)</a></p><p>To minimize heterogeneous exchange behavior, ligand-binding HDX-MS experiments are commonly conducted at concentrations well above the compound dissociation constant (<i>K</i><sub>D</sub>), producing a fully bound complex to avoid heterogeneous bimodal isotopic envelopes. <a href="javascript:void(0);">(2)</a> This belies the fact that HDX-MS workflows have been previously described which are capable of determining affinity constants, such as PLIMSTEX <a href="javascript:void(0);">(14)</a> and SUPREX, <a href="javascript:void(0);">(15)</a> and a push to make HDX-MS more “quantitative”, <i>i.e.</i>, able to abstract meaningful (and crucially comparable) biophysical constants from HDX-MS data. <a href="javascript:void(0);">(16)</a> Furthermore, there has been renewed interest, notably from the Wilson group and co-workers, in HDX-MS/MS (<i>i.e.</i>, the fragmentation of a deuterated precursor peptide to produce deuterated product ions), which enables residue-level investigation of deuterated peptides. <a href="javascript:void(0);">(17−19)</a> These experiments build on the comprehensive and groundbreaking work in the groups of Jørgensen and Rand, who used electron capture dissociation (ECD) or electron transfer dissociation (ETD) to achieve fragmentation with minimal hydrogen/deuterium (H/D) scrambling. <a href="javascript:void(0);">(20−23)</a> Although HDX-MS/MS has been applied to ligand binding, <a href="javascript:void(0);">(24,25)</a> its use has remained limited, possibly due to the low efficiency of fragmentation and the stringent controls required to detect signal scrambling. Newer technologies, such as Electron-Activated Dissociation (EAD), have shown improved performance, increasing the accessibility of scramble-free HDX-MS/MS for ligand screening. <a href="javascript:void(0);">(17)</a></p><p>Here, we report a compound titration experiment using both HDX-MS and ECD-based HDX-MS/MS that enables the determination of apparent dissociation constants (<i>K</i><sub>D</sub><sup>app</sup>) with an amino acid spatial resolution. Using the <i>Plasmodium falciparum</i> GCN5 bromodomain as a model system, we measured deuterium uptake as a function of compound concentration at the peptide and single-amino acid level to extract quantitative affinity information. Comparison with orthogonal biophysical methods showed a strong agreement between HDX-derived and reference <i>K</i><sub>D</sub> values. This approach provides a time-efficient, low-sample-consumption, in-solution method of quantifying ligand binding and mapping local conformational changes, enabling detailed characterization of the mode of interaction and binding mechanisms in protein–ligand events.</p><h4><strong>Methods</strong></h4><h5><strong>Hydrogen–Deuterium Exchange-Mass Spectrometry</strong></h5><p>HDX-MS data were acquired using the HDX manager (Waters Corp.) maintained at 0.1 °C and coupled in-line to a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/202"><strong>SELECT SERIES Cyclic IMS QTOF mass spectrometer</strong> </a>(Waters Corp.). Automated liquid handling was performed using a PAL3 robotic tool change system, controlled by Chronos Software (LEAP Technologies). The protein was digested in-line for 2 min at 20 °C using an Enzymate BEH Pepsin 2.1 mm × 30 mm column (Waters Corp.). The generated peptides were desalted in buffer A (0.1% formic acid in water) using an ACQUITY UPLC BEH C18 VanGuard Precolumn (1.7 μm, 5 × 2.1 mm; Waters Corp.) prior to reversed-phase separation on an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1952"><strong>ACQUITY UPLC C18 column</strong></a> (1.7 μm, 100 × 1 mm; Waters Corp.). Peptides were eluted using a 40 μL/min flow rate from 5% to 85% buffer B (0.1% formic acid in acetonitrile) in buffer A. Data were acquired in positive mode over a <i>m</i>/<i>z</i> range of 50–1200 with a spray voltage of 2.0 kV with leucine enkephalin (<i>m</i>/<i>z</i> 556.2766) used as a lockmass internal calibrant during data acquisition.</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Dissociation Constants Determined via Peptide-Level HDX-MS/MS Analysis</strong></h5><p>We next sought to determine whether ECD could be used under minimized H/D-scrambling conditions to determine apparent dissociation constants (<i>K</i><sub>D</sub><sup>app</sup>) at single-amino-acid resolution. The source and ECD cell parameters were optimized for minimal deuterium scrambling, initially using the P1 peptide HDX scrambling monitor to tune as previously described <a href="javascript:void(0);">(21,24,37,42)</a> with further refinement being conducted using the loss of ammonia method as described by Rand et al. <a href="javascript:void(0);">(22)</a> (Supporting Information <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/jasms.6c00020/suppl_file/js6c00020_si_001.pdf">Figure S1</a>). Targeted ECD fragmentation was then applied to deuterated precursor ions of the PfGCN5-BRD peptide containing residues 18 to 33. This peptide, detected predominantly in +3 charge state and with a relative abundance exceeding 10<sup>5</sup> counts, produced an almost complete <i>c</i> ion series including <i>c</i>3-<i>c</i>7 and <i>c</i>9-<i>c</i>11 and <i>z</i> ion fragments <i>z</i>9-<i>z</i>13, providing a near-complete single-residue coverage (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/jasms.6c00020#fig3">Figure 3</a>).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/J_Am_Soc_Mass_Spectrom_2026_37_6_1391_1401_Figure_3_Representative_ECD_MS_MS_spectra_473ebb2617.jpg" alt="J. Am. Soc. Mass Spectrom. 2026, 37, 6, 1391–1401: Figure 3. Representative ECD MS/MS spectra of the [M + 3H]3+ precursor ion of the peptide LEKQQSAWPFLKPVSL acquired under nondeuterated and deuterated conditions. (A) ECD spectrum of the nondeuterated peptide at 0 s exchange (precursor m/z 624.40, 3+) and ECD spectrum following 5 min deuterium labeling (precursor m/z 626.30, 3+). Spectra are displayed at the indicated relative intensity scales. Predominantly c- and z-type ions consistent with nonergodic ECD cleavage were observed. (B) High-resolution isotopic distributions of a representative ECD fragment ion (c11) of the peptide LEKQQSAWPFLKPVSL under nondeuterated and deuterated conditions with and without 120 μM compound ′4250." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_J_Am_Soc_Mass_Spectrom_2026_37_6_1391_1401_Figure_3_Representative_ECD_MS_MS_spectra_473ebb2617.jpg 190w," sizes="100vw" width="2079" height="1708"></p><p>Compound titration of ′4250 across the same eight-point concentration curve as used for peptide-level HDX-MS enabled the determination of residue-level <i>K</i><sub>D</sub><sup>app</sup> values using HDX-MS/MS for the interacting region A24-V31 (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/jasms.6c00020#fig4">Figure 4</a>). The apparent affinities ranged from 19.4 μM for P30 V to 1.3 μM for K29. Notably, this stretch of amino acids contains two proline residues, P30 and P25, which are “invisible” to HDX-MS/MS analysis due to the absence of backbone amide hydrogens. The HDX-MS/MS analysis therefore not only localized the ligand binding interface between PfGCN5-BRD and ′4250 but also provided quantitative, residue-specific affinity information.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/J_Am_Soc_Mass_Spectrom_2026_37_6_1391_1401_Figure_4_Single_amino_acid_HDX_MS_to_derive_spatial_K_Dapp_at_a_single_residue_resolution_compared_to_crystallography_data_2724ca7867.jpg" alt="J. Am. Soc. Mass Spectrom. 2026, 37, 6, 1391–1401: Figure 4. Single amino-acid HDX-MS to derive spatial KDapp at a single residue resolution compared to crystallography data. (A) HDX-MS/MS was conducted using targeted ECD on a single peptide while titrating the ′4250 compound. Consecutive fragments are used to determine individual exchange rates, from which % deuteration can be derived. Each data point is averaged with standard deviation, from n = 3, with each exchange reaction being conducted independently. (B) Detail of ′4250 electron density binding to PfGCN5-BRD with amino acids pertinent to subsequent HDX-MS/MS analysis colored red/green. (C) Map of potential polar contacts between ′4250 and PfGCN5-BRD as identified via crystallography. Water molecules shown as red spheres." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_J_Am_Soc_Mass_Spectrom_2026_37_6_1391_1401_Figure_4_Single_amino_acid_HDX_MS_to_derive_spatial_K_Dapp_at_a_single_residue_resolution_compared_to_crystallography_data_2724ca7867.jpg 184w," sizes="100vw" width="2033" height="1722"></p><p>Comparing the crystal structure of ′4250 with PfGCN5-BRD to the HDX-MS/MS there is a high degree of agreement (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/jasms.6c00020#fig4">Figure 4</a>B,C). There are several contacts between ′4250 and the amino acids identified in the HDX-MS/MS, although residues M74, N82, and Y39, which interact with the purine derivative part of ′4250 are not present in the HDX-MS/MS data set, we can observe that W25/K29 and S32 are present (as is the “invisible” P26). The site identified as the “tightest” interaction, K29, which had a <i>K</i><sub>D</sub><sup>app</sup> of 1.3 μM, has a backbone hydrogen bond to a coordinated water molecule. Interestingly, there is a network of three water molecules which mediate the interaction between P26, W25, K29, and ′4250. It is possible that the presence of ′4250 slows the solvent exchange rate by stabilizing these water molecules at the site of interaction, thus slowing the solvent exchange rate. S32 was not observed to have an interaction with ′4250 via HDX-MS/MS, but the crystal structure suggests that S32’s amide group has a hydrogen bond with ′4250. The fact that this was not observed via HDX-MS/MS is interesting, as it would be expected that, given HDX measures the rate of solvent exchange on the peptide bond amide, one would expect that this residue would experience a high degree of solvent exchange rate protection on compound binding. In the “apo” structure of PfGCN5-BRD (PDB:<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.2210/pdb4QNS/pdb">4QNS</a>), <a href="javascript:void(0);">(43)</a> there is no hydrogen-bonded water associated with this amide group, perhaps meaning there is no exchange event here to disrupt, or potentially, the rate of solvent exchange is slower than our 5 min time point, meaning that this interaction was outside the kinetic window of the HDX-MS/MS experiment.</p><h4><strong>Conclusion</strong></h4><p>Recent advances in peptide fragmentation technologies for HDX-MS/MS <a href="javascript:void(0);">(2,17,18,44)</a> have renewed interest in achieving residue-level localization of deuterium uptake. Here, we demonstrate that HDX-MS/MS using ECD can not only localize ligand binding sites but, through compound titration at selected exchange time points, also be used to derive apparent dissociation constants (<i>K</i><sub>D</sub><sup>app</sup>). This represents a novel and generally applicable in-solution approach to quantifying ligand affinity without the need for protein tagging or immobilization.</p><p>HDX-MS has been used before to derive affinity constants, with studies such as PLIMSTEX <a href="javascript:void(0);">(14)</a> being capable of determining protein/ligand affinity and SUPREX <a href="javascript:void(0);">(15)</a> focusing on protein/DNA affinity. However, both of these approaches essentially measured the entire protein’s change in deuteration uptake on ligand binding, meaning that while a high-quality, in-solution affinity constant using HDX-MS could be obtained, the spatial dimension afforded by middle-down HDX-MS had been lost. Using a HDX-MS (as opposed to HDX-MS/MS) workflow, we were able to assess the local <i>K</i><sub>D</sub><sup>app</sup> for ligand binding at a peptide level resolution. This workflow is simple, can be conducted using commercial HDX-MS systems, and offers a rapid and automatable means of determining in solution <i>K</i><sub>D</sub><sup>app</sup>.</p><p>An interesting aspect of applying a titration-based HDX-MS approach is that it produces a distribution of apparent affinity constants across the protein sequence rather than a single value. This may seem paradoxical as ligand binding is a classical 1:1 equilibrium between a single bound and a single unbound state; <a href="javascript:void(0);">(45)</a> thus all residues in the protein should in principle report the same <i>K</i><sub>D</sub>. The apparent heterogeneity in <i>K</i><sub>D</sub><sup>app</sup> observed here, therefore, requires interpretation.</p><p>Under EX2 conditions, the deuterium uptake at any given amide hydrogen reflects a time-averaged occupancy-weighted average of the local conformational flexibility in the bound and unbound states. For residues directly contacting the ligand backbone─where binding directly suppresses amide hydrogen exchange through steric occlusion or hydrogen bonding─the Δ<i>D</i> signal will closely track ligand occupancy, and the fitted <i>K</i><sub>D</sub><sup>app</sup> will most faithfully reflect the thermodynamic binding constant. For residues that are protected indirectly, through ligand-induced conformational stabilization propagated across the binding interface, the value of Δ<i>D</i><sub>max</sub> at saturation will be smaller (because the per-residue contribution of stabilization is lower), and the associated <i>K</i><sub>D</sub><sup>app</sup> may deviate from the global value as a function of how cooperatively that stabilization is coupled to ligand occupancy. Furthermore, residues that are exchanging on time scales faster or slower than our fixed exchange time point may be systematically under- or over-represented in their apparent sensitivity to the binding event. The fact that the mean <i>K</i><sub>D</sub><sup>app</sup> across all peptides approximates the SPR-derived <i>K</i><sub>D</sub> is encouraging, but this agreement rests on a single compound–protein pair and should be tested systematically. Finally, a degree of cooperativity is expected to operate within these measurements: once the ligand has occupied the binding pocket, neighboring residues that have little direct contact with the compound are nonetheless more likely to be conformationally restrained, and this indirect effect will be reflected in their <i>K</i><sub>D</sub><sup>app</sup> values. Further experimentation across a broader array of protein targets and binding modalities, including allosteric modalities in nonequilibrium environments <a href="javascript:void(0);">(46)</a> is required to develop a predictive framework for interpreting the spatial <i>K</i><sub>D</sub> distribution in terms of the underlying interaction chemistry.</p><p>A key advantage of HDX-MS/MS is its ability to resolve affinity information at single-amino-acid spatial resolution, providing insight into local modes of interaction that complement traditional Structure––Activity Relationship (SAR) studies. The combination of HDX-MS-derived spatial interaction mapping with conventional SAR analysis can accelerate hit validation and early lead optimization by linking the compound structure to localized protein response. The lead optimization stage of drug discovery often requires a medium-throughput structural biology approach to determine how adjustments in lead compounds alter the target engagement. HDX-MS/MS is well suited to facilitate a semiautomated in-solution approach to screen these relatively small (10–30) compound series where both <i>K</i><sub>D</sub><sup>app</sup> measurements on a peptide and amino acid level can inform likely compound engagement profiles, especially if coupled to HDX-MS/MS restraint-guided drug docking simulations.</p><p>The peptide-level <i>K</i><sub>D</sub><sup>app</sup> determination approach described in this study is compatible with standard HDX-MS instrumentation and can be readily adapted to other protein–ligand systems, particularly where in-solution binding measurements are advantageous. The affinity measurement can also be conducted without the use of protein affinity tags (such as His/Strep-tags) or the need for fluorescent moieties, which may introduce artifacts into the experiment. Future developments in automated ECD data acquisition and analysis are expected to further improve throughput and robustness, expanding the applicability of this approach in drug discovery.</p></div>

Residue-Level Determination of Small-Molecule–Protein Affinities by Hydrogen–Deuterium Exchange Mass Spectrometry

Article

Product

Events

Webinars

Application

Academy

Video

Poster

Scientists

Plastics

Environment

Food

Water

Health

Presentation

Scientific article

Interview

Toxicology

Popularization

Science and research

Software

Covid-19

Career

Laboratories

Various

Zaměření

Type of News

Focus

Everything from the world of analytical chemistry in one place. We connect people in solving their problems. At Labrulez you will find all the necessary information easily, quickly and clearly. Stop searching and start finding.

Residue-Level Determination of Small-Molecule–Protein Affinities by Hydrogen–Deuterium Exchange Mass Spectrometry

News from LabRulezLCMS Library - Week 29, 2026

Tracking Protein Misfolding and Oligomerization: A Temperature-Controlled Ion Mobility-Mass Spectrometry Approach

Webinars LabRulezLCMS Week 29/2026

News from LabRulezLCMS Library - Week 28, 2026

Webinars LabRulezLCMS Week 28/2026

Comparative Evaluation of Total Ergot Alkaloids Determination by ELISA and UHPLC-MS/MS in Wheat: Implications of Cross-Reactivity and Matrix Effects

News from LabRulezLCMS Library - Week 27, 2026

Webinars LabRulezLCMS Week 27/2026

Online Deglycosylation of Monomeric Intact Proteins Using the PNGase Rc Immobilized-Enzyme Reactor

Upcoming events

PFAS Seminar Series

Light Scattering for Complex Biologics Lunch & Learn - Mississauga, CA

Light Scattering for Complex Biologics Lunch & Learn - Seattle, WA

Webinars

PFAS Asia Summit 2026

Unknowns Uncovered: Smart LC Strategies That Work

Unlocking New Insights Into PFAS Distribution and Biological Impact