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HDX-MS-Guided computational modeling for rapid and accurate antibody-antigen interface mapping.

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Τίτλος: HDX-MS-Guided computational modeling for rapid and accurate antibody-antigen interface mapping.
Συγγραφείς: McMahon W; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA., Zhang H; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Li X; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Oganesyan V; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Payne S; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Mehzabeen N; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Dyk NV; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Liu W; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Howard W; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA., Zhao P; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA., Zhang Y; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA., Fang M; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA., Chen X; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA., Mazor Y; Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA., Shi Y; Analytical Sciences, Biopharmaceutical Development, AstraZeneca, Gaithersburg, MD, USA.
Πηγή: MAbs [MAbs] 2026 Dec; Vol. 18 (1), pp. 2722455. Date of Electronic Publication: 2026 Sep 11.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Taylor & Francis Country of Publication: United States NLM ID: 101479829 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1942-0870 (Electronic) Linking ISSN: 19420862 NLM ISO Abbreviation: MAbs Subsets: MEDLINE
Imprint Name(s): Publication: 2015- : Philadelphia, PA : Taylor & Francis
Original Publication: Austin, TX : Landes Bioscience
Ιατρικοί όροι (MeSH): Hydrogen Deuterium Exchange-Mass Spectrometry*/methods , Epitope Mapping*/methods , Epitopes*/chemistry , Epitopes*/immunology , Antigen-Antibody Complex*/chemistry , Antigen-Antibody Complex*/immunology, Immunoglobulin Fab Fragments/chemistry ; Humans ; Models, Molecular ; Crystallography, X-Ray
Περίληψη: Accurate mapping of paratopes and epitopes at antibody-antigen (Ab-Ag) interfaces is essential for the rational design of therapeutic antibodies in early drug development. Traditional methods for determining high-resolution Ab-Ag complex structures, such as X-ray crystallography and cryo-electron microscopy, are labor-intensive and require substantial time and resources. Although recent computational approaches have increased throughput, prediction accuracy and reliability remain limited, particularly without experimental structural constraints. Here, we present a hydrogen-deuterium exchange mass spectrometry (HDX-MS)-guided structural modeling workflow for efficient and accurate epitope and paratope mapping across three prospective case studies in therapeutic protein discovery and engineering. Across these systems, peptide-level HDX-MS data were sufficient to guide docking and structural modeling, whereas targeted electron transfer dissociation (ETD) HDX-MS was applied in one system as a higher-resolution, orthogonal approach to further localize critical binding residues. The workflow was applied to diverse Ab-Ag architectures spanning Fab and VHH binders and homodimeric and heterodimeric antigen ectodomains, and HDX-MS data were integrated with HADDOCK, AlphaFold2, and Protenix to generate Ab-Ag complex models. Comparison with subsequently obtained in-house X-ray crystal structures, used here as orthogonal high-resolution reference structures, showed strong agreement in overall binding orientation and interface placement. These results demonstrate the robustness and practical utility of this integrative approach for structure-informed antibody engineering in therapeutic protein discovery.
References: J Biol Chem. 2014 Dec 19;289(51):35388-96. (PMID: 25344622)
Anal Chem. 2007 Nov 15;79(22):8686-93. (PMID: 17935303)
Eur J Nucl Med Mol Imaging. 2023 Feb;50(3):679-691. (PMID: 36346438)
Bioinformatics. 2023 Jan 1;39(1):. (PMID: 36370083)
Nature. 2021 Aug;596(7873):583-589. (PMID: 34265844)
Methods Mol Biol. 2018;1785:13-27. (PMID: 29714009)
MAbs. 2023 Jan-Dec;15(1):2285285. (PMID: 38010385)
Nat Rev Drug Discov. 2018 Jul;17(7):509-527. (PMID: 29904196)
J Am Soc Mass Spectrom. 2026 Jun 3;37(6):1391-1401. (PMID: 41915381)
Proc Natl Acad Sci U S A. 2008 Jul 1;105(26):9029-34. (PMID: 18574150)
Anal Chem. 2020 Jun 2;92(11):7453-7461. (PMID: 32427467)
Structure. 2020 Jan 7;28(1):119-129.e2. (PMID: 31727476)
Science. 2003 Nov 21;302(5649):1364-8. (PMID: 14631033)
Biochem J. 2017 May 16;474(11):1867-1877. (PMID: 28381646)
Front Anal Sci. 2023;3:. (PMID: 37746528)
Cancer Res. 2011 Mar 15;71(6):2250-9. (PMID: 21406401)
Front Immunol. 2023 Nov 10;14:1275304. (PMID: 38022650)
Transplantation. 1982 Feb;33(2):156-62. (PMID: 6949383)
Proc Natl Acad Sci U S A. 2016 Apr 19;113(16):4440-5. (PMID: 27036003)
Methods Mol Biol. 2018;1785:1-10. (PMID: 29714008)
Science. 2018 Aug 31;361(6405):876-880. (PMID: 30166484)
Nature. 2024 Jun;630(8016):493-500. (PMID: 38718835)
J Struct Biol. 2025 Mar;217(1):108166. (PMID: 39765317)
Nat Methods. 2019 Jul;16(7):595-602. (PMID: 31249422)
Bioinformatics. 2024 Oct 1;40(10):. (PMID: 39348158)
J Am Soc Mass Spectrom. 2022 Feb 2;33(2):215-237. (PMID: 35077179)
Contributed Indexing: Keywords: Antibody-antigen interface mapping; HDX-MS; computational modeling
Substance Nomenclature: 0 (Immunoglobulin Fab Fragments)
0 (Epitopes)
0 (Antigen-Antibody Complex)
Entry Date(s): Date Created: 20260911 Date Completed: 20260911 Latest Revision: 20260917
Update Code: 20260917
PubMed Central ID: PMC13577250
DOI: 10.1080/19420862.2026.2722455
PMID: 42725674
Βάση Δεδομένων: MEDLINE
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  Data: Accurate mapping of paratopes and epitopes at antibody-antigen (Ab-Ag) interfaces is essential for the rational design of therapeutic antibodies in early drug development. Traditional methods for determining high-resolution Ab-Ag complex structures, such as X-ray crystallography and cryo-electron microscopy, are labor-intensive and require substantial time and resources. Although recent computational approaches have increased throughput, prediction accuracy and reliability remain limited, particularly without experimental structural constraints. Here, we present a hydrogen-deuterium exchange mass spectrometry (HDX-MS)-guided structural modeling workflow for efficient and accurate epitope and paratope mapping across three prospective case studies in therapeutic protein discovery and engineering. Across these systems, peptide-level HDX-MS data were sufficient to guide docking and structural modeling, whereas targeted electron transfer dissociation (ETD) HDX-MS was applied in one system as a higher-resolution, orthogonal approach to further localize critical binding residues. The workflow was applied to diverse Ab-Ag architectures spanning Fab and VHH binders and homodimeric and heterodimeric antigen ectodomains, and HDX-MS data were integrated with HADDOCK, AlphaFold2, and Protenix to generate Ab-Ag complex models. Comparison with subsequently obtained in-house X-ray crystal structures, used here as orthogonal high-resolution reference structures, showed strong agreement in overall binding orientation and interface placement. These results demonstrate the robustness and practical utility of this integrative approach for structure-informed antibody engineering in therapeutic protein discovery.
– Name: Ref
  Label: References
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  Data: J Biol Chem. 2014 Dec 19;289(51):35388-96. (PMID: <searchLink fieldCode="PM" term="%2225344622%22">25344622)</searchLink><br />Anal Chem. 2007 Nov 15;79(22):8686-93. (PMID: <searchLink fieldCode="PM" term="%2217935303%22">17935303)</searchLink><br />Eur J Nucl Med Mol Imaging. 2023 Feb;50(3):679-691. (PMID: <searchLink fieldCode="PM" term="%2236346438%22">36346438)</searchLink><br />Bioinformatics. 2023 Jan 1;39(1):. (PMID: <searchLink fieldCode="PM" term="%2236370083%22">36370083)</searchLink><br />Nature. 2021 Aug;596(7873):583-589. (PMID: <searchLink fieldCode="PM" term="%2234265844%22">34265844)</searchLink><br />Methods Mol Biol. 2018;1785:13-27. (PMID: <searchLink fieldCode="PM" term="%2229714009%22">29714009)</searchLink><br />MAbs. 2023 Jan-Dec;15(1):2285285. (PMID: <searchLink fieldCode="PM" term="%2238010385%22">38010385)</searchLink><br />Nat Rev Drug Discov. 2018 Jul;17(7):509-527. (PMID: <searchLink fieldCode="PM" term="%2229904196%22">29904196)</searchLink><br />J Am Soc Mass Spectrom. 2026 Jun 3;37(6):1391-1401. (PMID: <searchLink fieldCode="PM" term="%2241915381%22">41915381)</searchLink><br />Proc Natl Acad Sci U S A. 2008 Jul 1;105(26):9029-34. (PMID: <searchLink fieldCode="PM" term="%2218574150%22">18574150)</searchLink><br />Anal Chem. 2020 Jun 2;92(11):7453-7461. (PMID: <searchLink fieldCode="PM" term="%2232427467%22">32427467)</searchLink><br />Structure. 2020 Jan 7;28(1):119-129.e2. (PMID: <searchLink fieldCode="PM" term="%2231727476%22">31727476)</searchLink><br />Science. 2003 Nov 21;302(5649):1364-8. (PMID: <searchLink fieldCode="PM" term="%2214631033%22">14631033)</searchLink><br />Biochem J. 2017 May 16;474(11):1867-1877. (PMID: <searchLink fieldCode="PM" term="%2228381646%22">28381646)</searchLink><br />Front Anal Sci. 2023;3:. (PMID: <searchLink fieldCode="PM" term="%2237746528%22">37746528)</searchLink><br />Cancer Res. 2011 Mar 15;71(6):2250-9. (PMID: <searchLink fieldCode="PM" term="%2221406401%22">21406401)</searchLink><br />Front Immunol. 2023 Nov 10;14:1275304. (PMID: <searchLink fieldCode="PM" term="%2238022650%22">38022650)</searchLink><br />Transplantation. 1982 Feb;33(2):156-62. (PMID: <searchLink fieldCode="PM" term="%226949383%22">6949383)</searchLink><br />Proc Natl Acad Sci U S A. 2016 Apr 19;113(16):4440-5. (PMID: <searchLink fieldCode="PM" term="%2227036003%22">27036003)</searchLink><br />Methods Mol Biol. 2018;1785:1-10. (PMID: <searchLink fieldCode="PM" term="%2229714008%22">29714008)</searchLink><br />Science. 2018 Aug 31;361(6405):876-880. (PMID: <searchLink fieldCode="PM" term="%2230166484%22">30166484)</searchLink><br />Nature. 2024 Jun;630(8016):493-500. (PMID: <searchLink fieldCode="PM" term="%2238718835%22">38718835)</searchLink><br />J Struct Biol. 2025 Mar;217(1):108166. (PMID: <searchLink fieldCode="PM" term="%2239765317%22">39765317)</searchLink><br />Nat Methods. 2019 Jul;16(7):595-602. (PMID: <searchLink fieldCode="PM" term="%2231249422%22">31249422)</searchLink><br />Bioinformatics. 2024 Oct 1;40(10):. (PMID: <searchLink fieldCode="PM" term="%2239348158%22">39348158)</searchLink><br />J Am Soc Mass Spectrom. 2022 Feb 2;33(2):215-237. (PMID: <searchLink fieldCode="PM" term="%2235077179%22">35077179)</searchLink>
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