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Yan Z, Kim K, Kim H, Ha B, Gambiez A, Bennett J, de Almeida Mendes M, Trevizani R, Mahita J, Richardson E, Marrama D, Blazeska N, Koşaloğlu-Yalçın Z, Nielsen M, Sette A, Peters B, Greenbaum J. Next-generation IEDB tools: a platform for epitope prediction and analysis. Nucleic Acids Res 2024; 52:W526-W532. [PMID: 38783079 PMCID: PMC11223806 DOI: 10.1093/nar/gkae407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/24/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website. The initial release focuses on consolidation of all tools related to HLA class I epitopes (MHC binding, elution, immunogenicity, and processing), making all of these predictions accessible from a single application and allowing for their simultaneous execution with minimal user inputs. Additionally, the PEPMatch tool for identifying highly similar epitopes in a set of curated proteomes, as well as a tool for epitope clustering, are available on the site. The NG Tools site allows users to build data pipelines by sending the output of one tool as input for the next. Over the next several years, all pre-existing IEDB Tools, and any newly developed tools, will be integrated into this new site. Here we describe the philosophy behind the redesign and demonstrate the utility and productivity enhancements that are enabled by the new interface.
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Affiliation(s)
- Zhen Yan
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Kevin Kim
- Information Technology, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Haeuk Kim
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Brendan Ha
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Anaïs Gambiez
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Jason Bennett
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | | | - Raphael Trevizani
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
- Fiocruz Ceará, Fundação Oswaldo Cruz, Rua São José s/n, Precabura, Eusébio/CE, Brazil
| | - Jarjapu Mahita
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Eve Richardson
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Daniel Marrama
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Nina Blazeska
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | | | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, B1650 Buenos Aires, Argentina
| | - Alessandro Sette
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Bjoern Peters
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jason A Greenbaum
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
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Tsai WTK, Li Y, Yin Z, Tran P, Phung Q, Zhou Z, Peng K, Qin D, Tam S, Spiess C, Brumm J, Wong M, Ye Z, Wu P, Cohen S, Carter PJ. Nonclinical immunogenicity risk assessment for knobs-into-holes bispecific IgG 1 antibodies. MAbs 2024; 16:2362789. [PMID: 38845069 PMCID: PMC11164226 DOI: 10.1080/19420862.2024.2362789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 05/29/2024] [Indexed: 06/12/2024] Open
Abstract
Bispecific antibodies, including bispecific IgG, are emerging as an important new class of antibody therapeutics. As a result, we, as well as others, have developed engineering strategies designed to facilitate the efficient production of bispecific IgG for clinical development. For example, we have extensively used knobs-into-holes (KIH) mutations to facilitate the heterodimerization of antibody heavy chains and more recently Fab mutations to promote cognate heavy/light chain pairing for efficient in vivo assembly of bispecific IgG in single host cells. A panel of related monospecific and bispecific IgG1 antibodies was constructed and assessed for immunogenicity risk by comparison with benchmark antibodies with known low (Avastin and Herceptin) or high (bococizumab and ATR-107) clinical incidence of anti-drug antibodies. Assay methods used include dendritic cell internalization, T cell proliferation, and T cell epitope identification by in silico prediction and MHC-associated peptide proteomics. Data from each method were considered independently and then together for an overall integrated immunogenicity risk assessment. In toto, these data suggest that the KIH mutations and in vitro assembly of half antibodies do not represent a major risk for immunogenicity of bispecific IgG1, nor do the Fab mutations used for efficient in vivo assembly of bispecifics in single host cells. Comparable or slightly higher immunogenicity risk assessment data were obtained for research-grade preparations of trastuzumab and bevacizumab versus Herceptin and Avastin, respectively. These data provide experimental support for the common practice of using research-grade preparations of IgG1 as surrogates for immunogenicity risk assessment of their corresponding pharmaceutical counterparts.
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Affiliation(s)
- Wen-Ting K. Tsai
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
| | - Yinyin Li
- Department of Biochemical and Cellular Pharmacology, Genentech, Inc, South San Francisco, CA, USA
| | - Zhaojun Yin
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Peter Tran
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Qui Phung
- Department of Microchemistry, Proteomics and Lipidomics, Genentech, Inc, South San Francisco, CA, USA
| | - Zhenru Zhou
- Department of Microchemistry, Proteomics and Lipidomics, Genentech, Inc, South San Francisco, CA, USA
| | - Kun Peng
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Dan Qin
- Department of Biochemical and Cellular Pharmacology, Genentech, Inc, South San Francisco, CA, USA
| | - Sien Tam
- Department of Biochemical and Cellular Pharmacology, Genentech, Inc, South San Francisco, CA, USA
| | - Christoph Spiess
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
| | - Jochen Brumm
- Department of Nonclinical Biostatistics, Genentech, Inc, South San Francisco, CA, USA
| | - Manda Wong
- Department of Structural Biology, Genentech, Inc, South San Francisco, CA, USA
| | - Zhengmao Ye
- Department of Biochemical and Cellular Pharmacology, Genentech, Inc, South San Francisco, CA, USA
| | - Patrick Wu
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Sivan Cohen
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Paul J. Carter
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
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Dai J, Izadi S, Zarzar J, Wu P, Oh A, Carter PJ. Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG 1 antibody. MAbs 2024; 16:2304282. [PMID: 38269489 PMCID: PMC10813588 DOI: 10.1080/19420862.2024.2304282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/08/2024] [Indexed: 01/26/2024] Open
Abstract
Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤ 2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~ 200 anti-GCGR IgG1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2-10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.
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Affiliation(s)
- Jing Dai
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
| | - Saeed Izadi
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Jonathan Zarzar
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Patrick Wu
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Angela Oh
- Department of Structural Biology, Genentech, Inc, South San Francisco, CA, USA
| | - Paul J. Carter
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
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