1
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Roffler AA, Maurer DP, Lunn TJ, Sironen T, Forbes KM, Schmidt AG. Bat humoral immunity and its role in viral pathogenesis, transmission, and zoonosis. Front Immunol 2024; 15:1269760. [PMID: 39156901 PMCID: PMC11329927 DOI: 10.3389/fimmu.2024.1269760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 02/08/2024] [Indexed: 08/20/2024] Open
Abstract
Bats harbor viruses that can cause severe disease and death in humans including filoviruses (e.g., Ebola virus), henipaviruses (e.g., Hendra virus), and coronaviruses (e.g., SARS-CoV). Bats often tolerate these viruses without noticeable adverse immunological effects or succumbing to disease. Previous studies have largely focused on the role of the bat's innate immune response to control viral pathogenesis, but little is known about bat adaptive immunity. A key component of adaptive immunity is the humoral response, comprised of antibodies that can specifically recognize viral antigens with high affinity. The antibody genes within the 1,400 known bat species are highly diverse, and these genetic differences help shape fundamental aspects of the antibody repertoire, including starting diversity and viral antigen recognition. Whether antibodies in bats protect, mediate viral clearance, and prevent transmission within bat populations is poorly defined. Furthermore, it is unclear how neutralizing activity and Fc-mediated effector functions contribute to bat immunity. Although bats have canonical Fc genes (e.g., mu, gamma, alpha, and epsilon), the copy number and sequences of their Fc genes differ from those of humans and mice. The function of bat antibodies targeting viral antigens has been speculated based on sequencing data and polyclonal sera, but functional and biochemical data of monoclonal antibodies are lacking. In this review, we summarize current knowledge of bat humoral immunity, including variation between species, their potential protective role(s) against viral transmission and replication, and address how these antibodies may contribute to population dynamics within bats communities. A deeper understanding of bat adaptive immunity will provide insight into immune control of transmission and replication for emerging viruses with the potential for zoonotic spillover.
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Affiliation(s)
- Anne A. Roffler
- Ragon Institute of Mass General, MIT, and Harvard, Cambridge, MA, United States
| | - Daniel P. Maurer
- Ragon Institute of Mass General, MIT, and Harvard, Cambridge, MA, United States
| | - Tamika J. Lunn
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, United States
| | - Tarja Sironen
- Department of Virology, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
| | - Kristian M. Forbes
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, United States
| | - Aaron G. Schmidt
- Ragon Institute of Mass General, MIT, and Harvard, Cambridge, MA, United States
- Department of Microbiology, Harvard Medical School, Boston, MA, United States
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2
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Shanker VR, Bruun TUJ, Hie BL, Kim PS. Unsupervised evolution of protein and antibody complexes with a structure-informed language model. Science 2024; 385:46-53. [PMID: 38963838 DOI: 10.1126/science.adk8946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 05/29/2024] [Indexed: 07/06/2024]
Abstract
Large language models trained on sequence information alone can learn high-level principles of protein design. However, beyond sequence, the three-dimensional structures of proteins determine their specific function, activity, and evolvability. Here, we show that a general protein language model augmented with protein structure backbone coordinates can guide evolution for diverse proteins without the need to model individual functional tasks. We also demonstrate that ESM-IF1, which was only trained on single-chain structures, can be extended to engineer protein complexes. Using this approach, we screened about 30 variants of two therapeutic clinical antibodies used to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We achieved up to 25-fold improvement in neutralization and 37-fold improvement in affinity against antibody-escaped viral variants of concern BQ.1.1 and XBB.1.5, respectively. These findings highlight the advantage of integrating structural information to identify efficient protein evolution trajectories without requiring any task-specific training data.
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Affiliation(s)
- Varun R Shanker
- Stanford Biophysics Program, Stanford University School of Medicine, Stanford, CA 94305, USA
- Stanford Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA 94305, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
| | - Theodora U J Bruun
- Stanford Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA 94305, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Brian L Hie
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Peter S Kim
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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3
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Ornelas MY, Ouyang WO, Wu NC. A library-on-library screen reveals the breadth expansion landscape of a broadly neutralizing betacoronavirus antibody. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597810. [PMID: 38915656 PMCID: PMC11195093 DOI: 10.1101/2024.06.06.597810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Broadly neutralizing antibodies (bnAbs) typically evolve cross-reactivity breadth through acquiring somatic hypermutations. While evolution of breadth requires improvement of binding to multiple antigenic variants, most experimental evolution platforms select against only one antigenic variant at a time. In this study, a yeast display library-on-library approach was applied to delineate the affinity maturation of a betacoronavirus bnAb, S2P6, against 27 spike stem helix peptides in a single experiment. Our results revealed that the binding affinity landscape of S2P6 varies among different stem helix peptides. However, somatic hypermutations that confer general improvement in binding affinity across different stem helix peptides could also be identified. We further showed that a key somatic hypermutation for breadth expansion involves long-range interaction. Overall, our work not only provides a proof-of-concept for using a library-on-library approach to analyze the evolution of antibody breadth, but also has important implications for the development of broadly protective vaccines.
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Affiliation(s)
- Marya Y. Ornelas
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Wenhao O. Ouyang
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Nicholas C. Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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4
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McConnell SA, Casadevall A. Immunoglobulin constant regions provide stabilization to the paratope and enforce epitope specificity. J Biol Chem 2024; 300:107397. [PMID: 38763332 PMCID: PMC11215335 DOI: 10.1016/j.jbc.2024.107397] [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: 04/11/2024] [Accepted: 05/09/2024] [Indexed: 05/21/2024] Open
Abstract
Constant domains in antibody molecules at the level of the Fab (CH1 and CL) have long been considered to be simple scaffolding elements that physically separate the paratope-defining variable (V) region from the effector function-mediating constant (C) regions. However, due to recent findings that C domains of different isotypes can modulate the fine specificity encoded in the V region, elucidating the role of C domains in shaping the paratope and influencing specificity is a critical area of interest. To dissect the relative contributions of each C domain to this phenomenon, we generated antibody fragments with different C regions omitted, using a set of antibodies targeting capsular polysaccharides from the fungal pathogen, Cryptococcus neoformans. Antigen specificity mapping and functional activity measurements revealed that V region-only antibody fragments exhibited poly-specificity to antigenic variants and extended to recognition of self-antigens, while measurable hydrolytic activity of the capsule was greatly attenuated. To better understand the mechanistic origins of the remarkable loss of specificity that accompanies the removal of C domains from identical paratopes, we performed molecular dynamics simulations which revealed increased paratope plasticity in the scFv relative to the corresponding Fab. Together, our results provide insight into how the remarkable specificity of immunoglobulins is governed and maintained at the level of the Fab through the enforcement of structural restrictions on the paratope by CH1 domains.
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Affiliation(s)
- Scott A McConnell
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Arturo Casadevall
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
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5
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Szkodny AC, Lee KH. A systemic approach to identifying sequence frameworks that decrease mAb production in a transient Chinese hamster ovary cell expression system. Biotechnol Prog 2024:e3466. [PMID: 38607316 DOI: 10.1002/btpr.3466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/17/2024] [Accepted: 03/27/2024] [Indexed: 04/13/2024]
Abstract
Monoclonal antibodies (mAbs) are often engineered at the sequence level for improved clinical performance yet are rarely evaluated prior to candidate selection for their "developability" characteristics, namely expression, which can necessitate additional resource investments to improve the manufacturing processes for problematic mAbs. A strong relationship between primary sequence and expression has emerged, with slight differences in amino acid sequence resulting in titers differing by up to an order of magnitude. Previous work on these "difficult-to-express" (DTE) mAbs has shown that these phenotypes are driven by post-translational bottlenecks in antibody folding, assembly, and secretion processes. However, it has been difficult to translate these findings across cell lines and products. This work presents a systematic approach to study the impact of sequence variation on mAb expression at a larger scale and under more industrially relevant conditions. The analysis found 91 mutations that decreased transient expression of an IgG1κ in Chinese hamster ovary (CHO) cells and revealed that mutations at inaccessible residues, especially those leading to decreases in residue hydrophobicity, are not favorable for high expression. This workflow can be used to better understand sequence determinants of mAb expression to improve candidate selection procedures and reduce process development timelines.
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Affiliation(s)
- Alana C Szkodny
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware, USA
| | - Kelvin H Lee
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware, USA
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6
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Rong Y, Chen IL, Larrabee L, Sawant MS, Fuh G, Koenig P. An Engineered Mouse Model That Generates a Diverse Repertoire of Endogenous, High-Affinity Common Light Chain Antibodies. Antibodies (Basel) 2024; 13:14. [PMID: 38390875 PMCID: PMC10885109 DOI: 10.3390/antib13010014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/20/2024] [Accepted: 01/25/2024] [Indexed: 02/24/2024] Open
Abstract
Bispecific antibodies have gained increasing popularity as therapeutics as they enable novel activities that cannot be achieved with monospecific antibodies. Some of the most popular bispecific formats are molecules in which two Fab arms with different antigen specificities are combined into one IgG-like molecule. One way to produce these bispecific molecules requires the discovery of antibodies against the two antigens of interest that share a common light chain. Here, we present the generation and characterization of a common light chain mouse model, in which the endogenous IGKJ cluster is replaced with a prearranged, modified murine IGKV10-96/IGKJ1 segment. We demonstrate that genetic modification does not impact B-cell development. Upon immunization with ovalbumin, the animals generate an antibody repertoire with VH gene segment usage of a similar diversity to wildtype mice, while the light chain diversity is restricted to antibodies derived from the prearranged IGKV10-96/IGKJ1 germline. We further show that the clonotype diversity of the common light chain immune repertoire matches the diversity of immune repertoire isolated from wildtype mice. Finally, the common light chain anti-ovalbumin antibodies have only slightly lower affinities than antibodies isolated from wildtype mice, demonstrating the suitability of these animals for antibody discovery for bispecific antibody generation.
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Affiliation(s)
- Yinghui Rong
- 23andMe, Inc. Therapeutics, 349 Oyster Point Boulevard, South San Francisco, CA 94080, USA
| | - I-Ling Chen
- 23andMe, Inc. Therapeutics, 349 Oyster Point Boulevard, South San Francisco, CA 94080, USA
| | - Lance Larrabee
- 23andMe, Inc. Therapeutics, 349 Oyster Point Boulevard, South San Francisco, CA 94080, USA
| | - Manali S Sawant
- 23andMe, Inc. Therapeutics, 349 Oyster Point Boulevard, South San Francisco, CA 94080, USA
| | - Germaine Fuh
- 23andMe, Inc. Therapeutics, 349 Oyster Point Boulevard, South San Francisco, CA 94080, USA
| | - Patrick Koenig
- 23andMe, Inc. Therapeutics, 349 Oyster Point Boulevard, South San Francisco, CA 94080, USA
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7
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Guo D, De Sciscio ML, Chi-Fung Ng J, Fraternali F. Modelling the assembly and flexibility of antibody structures. Curr Opin Struct Biol 2024; 84:102757. [PMID: 38118364 DOI: 10.1016/j.sbi.2023.102757] [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: 10/13/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 12/22/2023]
Abstract
Antibodies are large protein assemblies capable of both specifically recognising antigens and engaging with other proteins and receptors to coordinate immune action. Traditionally, structural studies have been dedicated to antibody variable regions, but efforts to determine and model full-length antibody structures are emerging. Here we review the current knowledge on modelling the structures of antibody assemblies, focusing on their conformational flexibility and the challenge this poses to obtaining and evaluating structural models. Integrative modelling approaches, combining experiments (cryo-electron microscopy, mass spectrometry, etc.) and computational methods (molecular dynamics simulations, deep-learning based approaches, etc.), hold the promise to map the complex conformational landscape of full-length antibody structures.
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Affiliation(s)
- Dongjun Guo
- Institute of Structural and Molecular Biology, University College London, Darwin Building, Gower Street, London, WC1E 6BT, United Kingdom; Randall Centre for Cell & Molecular Biophysics, King's College London, New Hunt's House, Guy's Campus, London, SE1 1UL, United Kingdom
| | - Maria Laura De Sciscio
- Institute of Structural and Molecular Biology, University College London, Darwin Building, Gower Street, London, WC1E 6BT, United Kingdom; Department of Chemistry, Sapienza University of Rome, P.le A. Moro 5, Rome, 00185, Italy
| | - Joseph Chi-Fung Ng
- Institute of Structural and Molecular Biology, University College London, Darwin Building, Gower Street, London, WC1E 6BT, United Kingdom
| | - Franca Fraternali
- Institute of Structural and Molecular Biology, University College London, Darwin Building, Gower Street, London, WC1E 6BT, United Kingdom.
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8
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Shanker VR, Bruun TU, Hie BL, Kim PS. Inverse folding of protein complexes with a structure-informed language model enables unsupervised antibody evolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572475. [PMID: 38187780 PMCID: PMC10769282 DOI: 10.1101/2023.12.19.572475] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Large language models trained on sequence information alone are capable of learning high level principles of protein design. However, beyond sequence, the three-dimensional structures of proteins determine their specific function, activity, and evolvability. Here we show that a general protein language model augmented with protein structure backbone coordinates and trained on the inverse folding problem can guide evolution for diverse proteins without needing to explicitly model individual functional tasks. We demonstrate inverse folding to be an effective unsupervised, structure-based sequence optimization strategy that also generalizes to multimeric complexes by implicitly learning features of binding and amino acid epistasis. Using this approach, we screened ~30 variants of two therapeutic clinical antibodies used to treat SARS-CoV-2 infection and achieved up to 26-fold improvement in neutralization and 37-fold improvement in affinity against antibody-escaped viral variants-of-concern BQ.1.1 and XBB.1.5, respectively. In addition to substantial overall improvements in protein function, we find inverse folding performs with leading experimental success rates among other reported machine learning-guided directed evolution methods, without requiring any task-specific training data.
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Affiliation(s)
- Varun R. Shanker
- Stanford Biophysics Program, Stanford University School of Medicine, Stanford, CA 94305, USA
- Stanford Medical Scientist Training Program, Stanford University School of Medicine, Stanford CA 94305, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
| | - Theodora U.J. Bruun
- Stanford Medical Scientist Training Program, Stanford University School of Medicine, Stanford CA 94305, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Brian L. Hie
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Peter S. Kim
- Sarafan ChEM-H, Stanford University, Stanford, CA 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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9
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Nijkamp E, Ruffolo JA, Weinstein EN, Naik N, Madani A. ProGen2: Exploring the boundaries of protein language models. Cell Syst 2023; 14:968-978.e3. [PMID: 37909046 DOI: 10.1016/j.cels.2023.10.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 05/01/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023]
Abstract
Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial-intelligence-driven protein design. However, we lack a sufficient understanding of how very large-scale models and data play a role in effective protein model development. We introduce a suite of protein language models, named ProGen2, that are scaled up to 6.4B parameters and trained on different sequence datasets drawn from over a billion proteins from genomic, metagenomic, and immune repertoire databases. ProGen2 models show state-of-the-art performance in capturing the distribution of observed evolutionary sequences, generating novel viable sequences, and predicting protein fitness without additional fine-tuning. As large model sizes and raw numbers of protein sequences continue to become more widely accessible, our results suggest that a growing emphasis needs to be placed on the data distribution provided to a protein sequence model. Our models and code are open sourced for widespread adoption in protein engineering. A record of this paper's Transparent Peer Review process is included in the supplemental information.
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Affiliation(s)
| | - Jeffrey A Ruffolo
- Program in Molecular Biophysics, The Johns Hopkins University, Baltimore, MD, USA; Profluent Bio, Berkeley, CA, USA
| | - Eli N Weinstein
- Data Science Institute, Columbia University, New York, NY, USA
| | | | - Ali Madani
- Salesforce Research, Palo Alto, CA, USA; Profluent Bio, Berkeley, CA, USA.
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10
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Oksanen S, Saarinen R, Korkiakoski A, Lamminmäki U, Huovinen T. Genotyped functional screening of soluble Fab clones enables in-depth analysis of mutation effects. Sci Rep 2023; 13:13107. [PMID: 37567990 PMCID: PMC10421887 DOI: 10.1038/s41598-023-40241-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 08/07/2023] [Indexed: 08/13/2023] Open
Abstract
Monoclonal antibodies (mAbs) and their fragments are widely used in therapeutics, diagnostics and basic research. Although display methods such as phage display offer high-throughput, affinities of individual antibodies need to be accurately measured in soluble format. We have developed a screening platform capable of providing genotyped functional data from a total of 9216 soluble, individual antigen binding fragment (Fab) clones by employing next-generation sequencing (NGS) with hierarchical indexing. Full-length, paired variable domain sequences (VL-VH) are linked to functional screening data, enabling in-depth analysis of mutation effects. The platform was applied to four phage display-selected scFv/Fab screening projects and one site-saturation VH affinity maturation project. Genotyped functional screening simultaneously enabled the identification of affinity improving mutations in the VH domain of Fab 49A3 recognizing Dengue virus non-structural protein 1 (NS1) serotype 2 and informed on VH residue positions which cannot be changed from wild-type without decreasing the affinity. Genotype-based identification revealed to us the extent of intraclonal signal variance inherent to single point screening data, a phenomenon often overlooked in the field. Moreover, genotyped screening eliminated the redundant selection of identical genotypes for further study and provided a new analysis tool to evaluate the success of phage display selections and remaining clonal diversity in the screened repertoires.
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Affiliation(s)
- Sami Oksanen
- Department of Life Sciences, University of Turku, 20520, Turku, Finland.
| | - Roope Saarinen
- Department of Life Sciences, University of Turku, 20520, Turku, Finland
| | | | - Urpo Lamminmäki
- Department of Life Sciences, University of Turku, 20520, Turku, Finland
| | - Tuomas Huovinen
- Department of Life Sciences, University of Turku, 20520, Turku, Finland.
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11
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Bauer J, Rajagopal N, Gupta P, Gupta P, Nixon AE, Kumar S. How can we discover developable antibody-based biotherapeutics? Front Mol Biosci 2023; 10:1221626. [PMID: 37609373 PMCID: PMC10441133 DOI: 10.3389/fmolb.2023.1221626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 07/10/2023] [Indexed: 08/24/2023] Open
Abstract
Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.
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Affiliation(s)
- Joschka Bauer
- Early Stage Pharmaceutical Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
| | - Nandhini Rajagopal
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Priyanka Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Pankaj Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Andrew E. Nixon
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Sandeep Kumar
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
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12
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Rappazzo CG, Fernández-Quintero ML, Mayer A, Wu NC, Greiff V, Guthmiller JJ. Defining and Studying B Cell Receptor and TCR Interactions. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2023; 211:311-322. [PMID: 37459189 PMCID: PMC10495106 DOI: 10.4049/jimmunol.2300136] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 04/15/2023] [Indexed: 07/20/2023]
Abstract
BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.
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Affiliation(s)
| | | | - Andreas Mayer
- Division of Infection and Immunity, University College London, London WC1E 6BT, UK
| | - Nicholas C. Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Jenna J. Guthmiller
- Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045
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13
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Arslan M, Uluçay T, Kale S, Kalyoncu S. Engineering of conserved residues near antibody heavy chain complementary determining region 3 (HCDR3) improves both affinity and stability. BIOCHIMICA ET BIOPHYSICA ACTA. PROTEINS AND PROTEOMICS 2023; 1871:140915. [PMID: 37059314 DOI: 10.1016/j.bbapap.2023.140915] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/11/2023] [Accepted: 04/11/2023] [Indexed: 04/16/2023]
Abstract
Affinity and stability are crucial parameters in antibody development and engineering approaches. Although improvement in both metrics is desirable, trade-offs are almost unavoidable. Heavy chain complementarity determining region 3 (HCDR3) is the best-known region for antibody affinity but its impact on stability is often neglected. Here, we present a mutagenesis study of conserved residues near HCDR3 to elicit the role of this region in the affinity-stability trade-off. These key residues are positioned around the conserved salt bridge between VH-K94 and VH-D101 which is crucial for HCDR3 integrity. We show that the additional salt bridge at the stem of HCDR3 (VH-K94:VH-D101:VH-D102) has an extensive impact on this loop's conformation, therefore simultaneous improvement in both affinity and stability. We find that the disruption of π-π stacking near HCDR3 (VH-Y100E:VL-Y49) at the VH-VL interface cause an irrecoverable loss in stability even if it improves the affinity. Molecular simulations of putative rescue mutants exhibit complex and often non-additive effects. We confirm that our experimental measurements agree with the molecular dynamic simulations providing detailed insights for the spatial orientation of HCDR3. VH-V102 right next to HCDR3 salt bridge might be an ideal candidate to overcome affinity-stability trade-off.
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Affiliation(s)
- Merve Arslan
- Izmir Biomedicine and Genome Center, Balçova, 35340 Izmir, Turkey; Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Balçova, 35340 Izmir, Turkey
| | - Tuğçe Uluçay
- Izmir Biomedicine and Genome Center, Balçova, 35340 Izmir, Turkey
| | - Seyit Kale
- Izmir Biomedicine and Genome Center, Balçova, 35340 Izmir, Turkey
| | - Sibel Kalyoncu
- Izmir Biomedicine and Genome Center, Balçova, 35340 Izmir, Turkey.
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14
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Moulana A, Dupic T, Phillips AM, Desai MM. Genotype-phenotype landscapes for immune-pathogen coevolution. Trends Immunol 2023; 44:384-396. [PMID: 37024340 PMCID: PMC10147585 DOI: 10.1016/j.it.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 03/08/2023] [Accepted: 03/09/2023] [Indexed: 04/07/2023]
Abstract
Our immune systems constantly coevolve with the pathogens that challenge them, as pathogens adapt to evade our defense responses, with our immune repertoires shifting in turn. These coevolutionary dynamics take place across a vast and high-dimensional landscape of potential pathogen and immune receptor sequence variants. Mapping the relationship between these genotypes and the phenotypes that determine immune-pathogen interactions is crucial for understanding, predicting, and controlling disease. Here, we review recent developments applying high-throughput methods to create large libraries of immune receptor and pathogen protein sequence variants and measure relevant phenotypes. We describe several approaches that probe different regions of the high-dimensional sequence space and comment on how combinations of these methods may offer novel insight into immune-pathogen coevolution.
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Affiliation(s)
- Alief Moulana
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Thomas Dupic
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Angela M Phillips
- Department of Microbiology and Immunology, University of California at San Francisco, San Francisco, CA 94143, USA
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA 02138, USA; Quantitative Biology Initiative, Harvard University, Cambridge, MA 02138, USA.
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15
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Harmalkar A, Rao R, Richard Xie Y, Honer J, Deisting W, Anlahr J, Hoenig A, Czwikla J, Sienz-Widmann E, Rau D, Rice AJ, Riley TP, Li D, Catterall HB, Tinberg CE, Gray JJ, Wei KY. Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features. MAbs 2023; 15:2163584. [PMID: 36683173 PMCID: PMC9872953 DOI: 10.1080/19420862.2022.2163584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/14/2022] [Accepted: 12/26/2022] [Indexed: 01/24/2023] Open
Abstract
Over the last three decades, the appeal for monoclonal antibodies (mAbs) as therapeutics has been steadily increasing as evident with FDA's recent landmark approval of the 100th mAb. Unlike mAbs that bind to single targets, multispecific biologics (msAbs) have garnered particular interest owing to the advantage of engaging distinct targets. One important modular component of msAbs is the single-chain variable fragment (scFv). Despite the exquisite specificity and affinity of these scFv modules, their relatively poor thermostability often hampers their development as a potential therapeutic drug. In recent years, engineering antibody sequences to enhance their stability by mutations has gained considerable momentum. As experimental methods for antibody engineering are time-intensive, laborious and expensive, computational methods serve as a fast and inexpensive alternative to conventional routes. In this work, we show two machine learning approaches - one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features - to better classify thermostable scFv variants from sequence. Both of these models are trained over temperature-specific data (TS50 measurements) derived from multiple libraries of scFv sequences. On out-of-distribution (refers to the fact that the out-of-distribution sequnes are blind to the algorithm) sequences, we show that a sufficiently simple CNN model performs better than general pre-trained language models trained on diverse protein sequences (average Spearman correlation coefficient, ρ , of 0.4 as opposed to 0.15). On the other hand, an antibody-specific language model performs comparatively better than the CNN model on the same task (ρ = 0.52). Further, we demonstrate that for an independent mAb with available thermal melting temperatures for 20 experimentally characterized thermostable mutations, these models trained on TS50 data could identify 18 residue positions and 5 identical amino-acid mutations showing remarkable generalizability. Our results suggest that such models can be broadly applicable for improving the biological characteristics of antibodies. Further, transferring such models for alternative physicochemical properties of scFvs can have potential applications in optimizing large-scale production and delivery of mAbs or bsAbs.
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Affiliation(s)
- Ameya Harmalkar
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Roshan Rao
- Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
| | - Yuxuan Richard Xie
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jonas Honer
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Wibke Deisting
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Jonas Anlahr
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Anja Hoenig
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Julia Czwikla
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Eva Sienz-Widmann
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Doris Rau
- Therapeutic Discovery, Amgen Research (Munich) GmbH, Munich, Germany
| | - Austin J. Rice
- Therapeutic Discovery, Amgen Research, Amgen Inc, Thousand Oaks, CA, USA
| | - Timothy P. Riley
- Therapeutic Discovery, Amgen Research, Amgen Inc, Thousand Oaks, CA, USA
| | - Danqing Li
- Therapeutic Discovery, Amgen Research, Amgen Inc, Thousand Oaks, CA, USA
| | | | | | - Jeffrey J. Gray
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Kathy Y. Wei
- Therapeutic Discovery, Amgen Research, Amgen Inc, South San Francisco, CA, USA
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16
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Somatic Hypermutation and Framework Mutations of Variable Region Contribute to Anti-Zika Virus-Specific Monoclonal Antibody Binding and Function. J Virol 2022; 96:e0007122. [PMID: 35575481 PMCID: PMC9175631 DOI: 10.1128/jvi.00071-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Zika virus (ZIKV) is a global public health concern due to its ability to cause congenital Zika syndrome and lack of approved vaccine, therapeutic, or other control measures. We discovered eight novel rabbit monoclonal antibodies (MAbs) that bind to distinct ZIKV envelope protein epitopes. The majority of the MAbs were ZIKV specific and targeted the lateral ridge of the envelope (E) protein domain III, while the MAb with the highest neutralizing activity recognized a putative quaternary epitope spanning E protein domains I and III. One of the non-neutralizing MAbs specifically recognized ZIKV precursor membrane protein (prM). Somatic hypermutation of immunoglobulin variable regions increases antibody affinity maturation and triggers antibody class switching. Negative correlations were observed between the somatic hypermutation rate of the immunoglobulin heavy-chain variable region and antibody binding parameters such as equilibrium dissociation constant, dissociation constant, and half-maximal effective concentration value of MAb binding to ZIKV virus-like particles. Complementarity-determining regions recognize the antigen epitopes and are scaffolded by canonical framework regions. Reversion of framework region amino acids to the rabbit germ line sequence decreased anti-ZIKV MAb binding activity of some MAbs. Thus, antibody affinity maturation, including somatic hypermutation and framework region mutations, contributed to the binding and function of these anti-ZIKV MAbs. IMPORTANCE ZIKV is a global health concern against which no vaccine or therapeutics are available. We characterized eight novel rabbit monoclonal antibodies recognizing ZIKV envelope and prM proteins and studied the relationship between somatic hypermutation of complementarity-determining regions, framework regions, mutations, antibody specificity, binding, and neutralizing activity. The results contribute to understanding structural features and somatic mutation pathways by which potent Zika virus-neutralizing antibodies can evolve, including the role of antibody framework regions.
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17
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Kelley RF, Tesar DB, Wang Y, Agard NJ, Holder PG, Chan J, Comps-Agrar L, Horvath J, Horvath JD, Crowell SR. Generation of a Porcine Antibody Fab Fragment Using Protein Engineering to Facilitate the Evaluation of Ocular Sustained Delivery Technology. Mol Pharm 2022; 19:1540-1547. [PMID: 35393854 DOI: 10.1021/acs.molpharmaceut.2c00048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Treatment of age-related macular degeneration (AMD) with anti-vascular endothelial growth factor (VEGF) biologic agents has been shown to restore and maintain visual acuity for many patients afflicted with wet AMD. These agents are usually administered via intravitreal injection at a dosing interval of 4-8 weeks. Employment of long-acting delivery (LAD) technologies could improve the therapeutic outcome, ensure timely treatment, and reduce burden on patients, caregivers, and the health care system. Development of LAD approaches requires thorough testing in pre-clinical species; however, therapeutic proteins of human origin may not be well tolerated during testing in non-human species due to immunogenicity. Here, we have engineered a surrogate porcine antibody Fab fragment (pigG6.31) from a human antibody for testing ocular LAD technologies in a porcine model. The engineered Fab retains the VEGF-A-binding and inhibition properties of the parental human Fab and has stability properties suitable for LAD evaluation. Upon intravitreal injection in minipigs, pigG6.31 showed first-order clearance from the ocular compartments with vitreal elimination rates consistent with other molecules of this size. Application of the surrogate molecule in an in vivo evaluation in minipigs of a prototype of the port delivery (PD) platform indicated continuous ocular delivery from the implant, with release kinetics consistent with both the results from in vitro release studies and the efficacy observed in human clinical studies of the PD system with ranibizumab (PDS). Anti-drug antibodies in the serum against pigG6.31 were not detected over exposure durations up to 16 weeks, suggesting that this molecule has low porcine immunogenicity.
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Affiliation(s)
- Robert F Kelley
- Pharmaceutical Development, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Devin B Tesar
- Pharmaceutical Development, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Yue Wang
- Pharmaceutical Development, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Nicholas J Agard
- Antibody Engineering, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Patrick G Holder
- Protein Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Joyce Chan
- Biochemical and Cellular Pharmacology, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Laetitia Comps-Agrar
- Biochemical and Cellular Pharmacology, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Judit Horvath
- Pharmaceutical Development, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Joshua D Horvath
- Device Development, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | - Susan R Crowell
- Preclinical and Translational Pharmacokinetics and Pharmacodynamics Department, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
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18
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Spielmann M, Kircher M. Computational and experimental methods for classifying variants of unknown clinical significance. Cold Spring Harb Mol Case Stud 2022; 8:mcs.a006196. [PMID: 35483875 PMCID: PMC9059783 DOI: 10.1101/mcs.a006196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
The increase in sequencing capacity, reduction in costs, and national and international coordinated efforts have led to the widespread introduction of next-generation sequencing (NGS) technologies in patient care. More generally, human genetics and genomic medicine are gaining importance for more and more patients. Some communities are already discussing the prospect of sequencing each individual's genome at time of birth. Together with digital health records, this shall enable individualized treatments and preventive measures, so-called precision medicine. A central step in this process is the identification of disease causal mutations or variant combinations that make us more susceptible for diseases. Although various technological advances have improved the identification of genetic alterations, the interpretation and ranking of the identified variants remains a major challenge. Based on our knowledge of molecular processes or previously identified disease variants, we can identify potentially functional genetic variants and, using different lines of evidence, we are sometimes able to demonstrate their pathogenicity directly. However, the vast majority of variants are classified as variants of uncertain clinical significance (VUSs) with not enough experimental evidence to determine their pathogenicity. In these cases, computational methods may be used to improve the prioritization and an increasing toolbox of experimental methods is emerging that can be used to assay the molecular effects of VUSs. Here, we discuss how computational and experimental methods can be used to create catalogs of variant effects for a variety of molecular and cellular phenotypes. We discuss the prospects of integrating large-scale functional data with machine learning and clinical knowledge for the development of accurate pathogenicity predictions for clinical applications.
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Affiliation(s)
- Malte Spielmann
- Institute of Human Genetics, University of Lübeck, 23562 Lübeck, Germany;,Institute of Human Genetics, Christian-Albrechts-Universität, 24105 Kiel, Germany;,Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany;,DZHK (German Centre for Cardiovascular Research), partner site Hamburg/Lübeck/Kiel, 23562 Lübeck, Germany
| | - Martin Kircher
- Institute of Human Genetics, University of Lübeck, 23562 Lübeck, Germany;,Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany;,DZHK (German Centre for Cardiovascular Research), partner site Berlin, 10115 Berlin, Germany
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19
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Frick R, Høydahl LS, Hodnebrug I, Vik ES, Dalhus B, Sollid LM, Gray JJ, Sandlie I, Løset GÅ. Affinity maturation of TCR-like antibodies using phage display guided by structural modeling. Protein Eng Des Sel 2022; 35:6649134. [PMID: 35871543 PMCID: PMC9536190 DOI: 10.1093/protein/gzac005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/02/2022] [Accepted: 07/05/2022] [Indexed: 12/01/2022] Open
Abstract
TCR-like antibodies represent a unique type of engineered antibodies with specificity toward pHLA, a ligand normally restricted to the sensitive recognition by T cells. Here, we report a phage display-based sequential development path of such antibodies. The strategy goes from initial lead identification through in silico informed CDR engineering in combination with framework engineering for affinity and thermostability optimization, respectively. The strategy allowed the identification of HLA-DQ2.5 gluten peptide-specific TCR-like antibodies with low picomolar affinity. Our method outlines an efficient and general method for development of this promising class of antibodies, which should facilitate their utility including translation to human therapy.
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Affiliation(s)
- Rahel Frick
- Centre for Immune Regulation and Department of Immunology, University of Oslo and Oslo University Hospital , Sognsvannsveien 20, 0372 Oslo, Norway
- Centre for Immune Regulation and Department of Biosciences, University of Oslo , Blindernveien 31, 0371 Oslo, Norway
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University , 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Lene S Høydahl
- Centre for Immune Regulation and Department of Immunology, University of Oslo and Oslo University Hospital , Sognsvannsveien 20, 0372 Oslo, Norway
- Centre for Immune Regulation and Department of Biosciences, University of Oslo , Blindernveien 31, 0371 Oslo, Norway
- KG Jebsen Coeliac Disease Research Centre, University of Oslo , Sognsvannsveien 20, 0372 Oslo, Norway
| | - Ina Hodnebrug
- Centre for Immune Regulation and Department of Immunology, University of Oslo and Oslo University Hospital , Sognsvannsveien 20, 0372 Oslo, Norway
- Centre for Immune Regulation and Department of Biosciences, University of Oslo , Blindernveien 31, 0371 Oslo, Norway
| | - Erik S Vik
- Nextera AS , Gaustadalléen 21, 0349 Oslo, Norway
| | - Bjørn Dalhus
- Department for Medical Biochemistry , Institute for Clinical Medicine, , Sognsvannsveien 20, 0372 Oslo, Norway
- University of Oslo , Institute for Clinical Medicine, , Sognsvannsveien 20, 0372 Oslo, Norway
- Department for Microbiology , Clinic for Laboratory Medicine, , Sognsvannsveien 20, 0372 Oslo, Norway
- Oslo University Hospital , Clinic for Laboratory Medicine, , Sognsvannsveien 20, 0372 Oslo, Norway
| | - Ludvig M Sollid
- Centre for Immune Regulation and Department of Immunology, University of Oslo and Oslo University Hospital , Sognsvannsveien 20, 0372 Oslo, Norway
- KG Jebsen Coeliac Disease Research Centre, University of Oslo , Sognsvannsveien 20, 0372 Oslo, Norway
| | - Jeffrey J Gray
- Program in Molecular Biophysics, Johns Hopkins University , 3400 N. Charles Street, Baltimore, MD 21218, USA
- Department of Chemical and Biomolecular Engineering and Institute of NanoBioTechnology, Johns Hopkins University , 3400 N. Charles Street, Baltimore, MD 21218, USA
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine , 733 N Broadway, Baltimore, MD 21205, USA
| | - Inger Sandlie
- Centre for Immune Regulation and Department of Immunology, University of Oslo and Oslo University Hospital , Sognsvannsveien 20, 0372 Oslo, Norway
- Centre for Immune Regulation and Department of Biosciences, University of Oslo , Blindernveien 31, 0371 Oslo, Norway
| | - Geir Åge Løset
- Centre for Immune Regulation and Department of Immunology, University of Oslo and Oslo University Hospital , Sognsvannsveien 20, 0372 Oslo, Norway
- Centre for Immune Regulation and Department of Biosciences, University of Oslo , Blindernveien 31, 0371 Oslo, Norway
- Nextera AS , Gaustadalléen 21, 0349 Oslo, Norway
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20
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Sheng Z, Bimela JS, Katsamba PS, Patel SD, Guo Y, Zhao H, Guo Y, Kwong PD, Shapiro L. Structural Basis of Antibody Conformation and Stability Modulation by Framework Somatic Hypermutation. Front Immunol 2022; 12:811632. [PMID: 35046963 PMCID: PMC8761896 DOI: 10.3389/fimmu.2021.811632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/07/2021] [Indexed: 11/25/2022] Open
Abstract
Accumulation of somatic hypermutation (SHM) is the primary mechanism to enhance the binding affinity of antibodies to antigens in vivo. However, the structural basis of the effects of many SHMs remains elusive. Here, we integrated atomistic molecular dynamics (MD) simulation and data mining to build a high-throughput structural bioinformatics pipeline to study the effects of individual and combination SHMs on antibody conformation, flexibility, stability, and affinity. By applying this pipeline, we characterized a common mechanism of modulation of heavy-light pairing orientation by frequent SHMs at framework positions 39H, 91H, 38L, and 87L through disruption of a conserved hydrogen-bond network. Q39LH alone and in combination with light chain framework 4 (FWR4L) insertions further modulated the elbow angle between variable and constant domains of many antibodies, resulting in improved binding affinity for a subset of anti-HIV-1 antibodies. Q39LH also alleviated aggregation induced by FWR4L insertion, suggesting remote epistasis between these SHMs. Altogether, this study provides tools and insights for understanding antibody affinity maturation and for engineering functionally improved antibodies.
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Affiliation(s)
- Zizhang Sheng
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States.,Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, United States
| | - Jude S Bimela
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Phinikoula S Katsamba
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Saurabh D Patel
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Yicheng Guo
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States.,Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, United States
| | - Haiqing Zhao
- Department of Systems Biology, Columbia University, New York, NY, United States
| | - Youzhong Guo
- Department of Medicinal Chemistry, Virginia Commonwealth University, Richmond, VA, United States.,Institute for Structural Biology, Drug Discovery, and Development, Virginia Commonwealth University, Richmond, VA, United States
| | - Peter D Kwong
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, United States
| | - Lawrence Shapiro
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States.,Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, United States
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21
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Parallel profiling of antigenicity alteration and immune escape of SARS-CoV-2 Omicron and other variants. Signal Transduct Target Ther 2022; 7:42. [PMID: 35136040 PMCID: PMC8826850 DOI: 10.1038/s41392-022-00910-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 01/23/2022] [Accepted: 01/28/2022] [Indexed: 12/18/2022] Open
Abstract
SARS-CoV-2 variants have evolved a variety of critical mutations, leading to antigenicity changes and immune escape. The recent emerging SARS-CoV-2 Omicron variant attracted global attention due to its significant resistance to current antibody therapies and vaccines. Here, we profiled the mutations of Omicron and other various circulating SARS-CoV-2 variants in parallel by computational interface analysis and in vitro experimental assays. We identified critical mutations that lead to antigenicity changes and diminished neutralization efficiency of a panel of 14 antibodies due to diverse molecular mechanisms influencing the antigen-antibody interaction. Our study identified that Omicron exhibited extraordinary potency in immune escape compared to the other variants of concern, and explores the application of computational interface analysis in SARS-CoV-2 mutation surveillance and demonstrates its potential for the early identification of concerning variants, providing preliminary guidance for neutralizing antibody therapy.
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22
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Hanning KR, Minot M, Warrender AK, Kelton W, Reddy ST. Deep mutational scanning for therapeutic antibody engineering. Trends Pharmacol Sci 2021; 43:123-135. [PMID: 34895944 DOI: 10.1016/j.tips.2021.11.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/02/2021] [Accepted: 11/10/2021] [Indexed: 12/24/2022]
Abstract
The biophysical and functional properties of monoclonal antibody (mAb) drug candidates are often improved by protein engineering methods to increase the probability of clinical efficacy. One emerging method is deep mutational scanning (DMS) which combines the power of exhaustive protein mutagenesis and functional screening with deep sequencing and bioinformatics. The application of DMS has yielded significant improvements to the affinity, specificity, and stability of several preclinical antibodies alongside novel applications such as introducing multi-specific binding properties. DMS has also been applied directly on target antigens to precisely map antibody-binding epitopes and notably to profile the mutational escape potential of viral targets (e.g., SARS-CoV-2 variants). Finally, DMS combined with machine learning is enabling advances in the computational screening and engineering of therapeutic antibodies.
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Affiliation(s)
- Kyrin R Hanning
- Te Huataki Waiora School of Health, University of Waikato, Hamilton 3240, New Zealand
| | - Mason Minot
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule (ETH) Zurich, Basel 4058, Switzerland
| | - Annmaree K Warrender
- Te Huataki Waiora School of Health, University of Waikato, Hamilton 3240, New Zealand
| | - William Kelton
- Te Huataki Waiora School of Health, University of Waikato, Hamilton 3240, New Zealand.
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule (ETH) Zurich, Basel 4058, Switzerland.
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23
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Communication pathways bridge local and global conformations in an IgG4 antibody. Sci Rep 2021; 11:23197. [PMID: 34853348 PMCID: PMC8636491 DOI: 10.1038/s41598-021-02323-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 11/15/2021] [Indexed: 12/15/2022] Open
Abstract
The affinity of an antibody for its antigen is primarily determined by the specific sequence and structural arrangement of the complementarity-determining regions (CDRs). Recent evidence, however, points toward a nontrivial relation between the CDR and distal sites: variations in the binding strengths have been observed upon mutating residues separated from the paratope by several nanometers, thus suggesting the existence of a communication network within antibodies, whose extension and relevance might be deeper than insofar expected. In this work, we test this hypothesis by means of molecular dynamics (MD) simulations of the IgG4 monoclonal antibody pembrolizumab, an approved drug that targets the programmed cell death protein 1 (PD-1). The molecule is simulated in both the apo and holo states, totalling 4 μs of MD trajectory. The analysis of these simulations shows that the bound antibody explores a restricted range of conformations with respect to the apo one, and that the global conformation of the molecule correlates with that of the CDR. These results support the hypothesis that pembrolizumab featues a multi-scale hierarchy of intertwined global and local conformational changes. The analysis pipeline developed in this work is general, and it can help shed further light on the mechanistic aspects of antibody function.
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24
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Robinson RA, McMurran C, McCully ML, Cole DK. Engineering soluble T-cell receptors for therapy. FEBS J 2021; 288:6159-6173. [PMID: 33624424 PMCID: PMC8596704 DOI: 10.1111/febs.15780] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 02/11/2021] [Accepted: 02/22/2021] [Indexed: 12/15/2022]
Abstract
Immunotherapy approaches that target peptide-human leukocyte antigen (pHLA) complexes are becoming highly attractive because of their potential to access virtually all foreign and cellular proteins. For this reason, there has been considerable interest in the development of the natural ligand for pHLA, the T-cell receptor (TCR), as a soluble drug to target disease-associated pHLA presented at the cell surface. However, native TCR stability is suboptimal for soluble drug development, and natural TCRs generally have weak affinities for pHLAs, limiting their potential to reach efficacious receptor occupancy levels as soluble drugs. To overcome these limitations and make full use of the TCR as a soluble drug platform, several protein engineering solutions have been applied to TCRs to enhance both their stability and affinity, with a focus on retaining target specificity and selectivity. Here, we review these advances and look to the future for the next generation of soluble TCR-based therapies that can target monomorphic HLA-like proteins presenting both peptide and nonpeptide antigens.
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25
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Findlay GM. Linking genome variants to disease: scalable approaches to test the functional impact of human mutations. Hum Mol Genet 2021; 30:R187-R197. [PMID: 34338757 PMCID: PMC8490018 DOI: 10.1093/hmg/ddab219] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 07/19/2021] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
The application of genomics to medicine has accelerated the discovery of mutations underlying disease and has enhanced our knowledge of the molecular underpinnings of diverse pathologies. As the amount of human genetic material queried via sequencing has grown exponentially in recent years, so too has the number of rare variants observed. Despite progress, our ability to distinguish which rare variants have clinical significance remains limited. Over the last decade, however, powerful experimental approaches have emerged to characterize variant effects orders of magnitude faster than before. Fueled by improved DNA synthesis and sequencing and, more recently, by CRISPR/Cas9 genome editing, multiplex functional assays provide a means of generating variant effect data in wide-ranging experimental systems. Here, I review recent applications of multiplex assays that link human variants to disease phenotypes and I describe emerging strategies that will enhance their clinical utility in coming years.
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Affiliation(s)
- Gregory M Findlay
- The Francis Crick Institute, The Genome Function Laboratory, London NW1 1AT, UK
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26
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Phillips AM, Lawrence KR, Moulana A, Dupic T, Chang J, Johnson MS, Cvijovic I, Mora T, Walczak AM, Desai MM. Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies. eLife 2021; 10:71393. [PMID: 34491198 PMCID: PMC8476123 DOI: 10.7554/elife.71393] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/05/2021] [Indexed: 12/12/2022] Open
Abstract
Over the past two decades, several broadly neutralizing antibodies (bnAbs) that confer protection against diverse influenza strains have been isolated. Structural and biochemical characterization of these bnAbs has provided molecular insight into how they bind distinct antigens. However, our understanding of the evolutionary pathways leading to bnAbs, and thus how best to elicit them, remains limited. Here, we measure equilibrium dissociation constants of combinatorially complete mutational libraries for two naturally isolated influenza bnAbs (CR9114, 16 heavy-chain mutations; CR6261, 11 heavy-chain mutations), reconstructing all possible evolutionary intermediates back to the unmutated germline sequences. We find that these two libraries exhibit strikingly different patterns of breadth: while many variants of CR6261 display moderate affinity to diverse antigens, those of CR9114 display appreciable affinity only in specific, nested combinations. By examining the extensive pairwise and higher order epistasis between mutations, we find key sites with strong synergistic interactions that are highly similar across antigens for CR6261 and different for CR9114. Together, these features of the binding affinity landscapes strongly favor sequential acquisition of affinity to diverse antigens for CR9114, while the acquisition of breadth to more similar antigens for CR6261 is less constrained. These results, if generalizable to other bnAbs, may explain the molecular basis for the widespread observation that sequential exposure favors greater breadth, and such mechanistic insight will be essential for predicting and eliciting broadly protective immune responses.
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Affiliation(s)
- Angela M Phillips
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
| | - Katherine R Lawrence
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.,NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States.,Quantitative Biology Initiative, Harvard University, Cambridge, United States.,Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
| | - Alief Moulana
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
| | - Thomas Dupic
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
| | - Jeffrey Chang
- Department of Physics, Harvard University, Cambridge, United States
| | - Milo S Johnson
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
| | - Ivana Cvijovic
- Department of Applied Physics, Stanford University, Stanford, United States
| | - Thierry Mora
- Laboratoire de physique de ÍÉcole Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Aleksandra M Walczak
- Laboratoire de physique de ÍÉcole Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.,NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States.,Quantitative Biology Initiative, Harvard University, Cambridge, United States.,Department of Physics, Harvard University, Cambridge, United States
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27
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Abstract
The patent literature should reflect the past 30 years of engineering efforts directed toward developing monoclonal antibody therapeutics. Such information is potentially valuable for rational antibody design. Patents, however, are designed not to convey scientific knowledge, but to provide legal protection. It is not obvious whether antibody information from patent documents, such as antibody sequences, is useful in conveying engineering know-how, rather than as a legal reference only. To assess the utility of patent data for therapeutic antibody engineering, we quantified the amount of antibody sequences in patents destined for medicinal purposes and how well they reflect the primary sequences of therapeutic antibodies in clinical use. We identified 16,526 patent families covering major jurisdictions (e.g., US Patent and Trademark Office (USPTO) and World Intellectual Property Organization) that contained antibody sequences. These families held 245,109 unique antibody chains (135,397 heavy chains and 109,712 light chains) that we compiled in our Patented Antibody Database (PAD, http://naturalantibody.com/pad). We find that antibodies make up a non-trivial proportion of all patent amino acid sequence depositions (e.g., 11% of USPTO Full Text database). Our analysis of the 16,526 families demonstrates that the volume of patent documents with antibody sequences is growing, with the majority of documents classified as containing antibodies for medicinal purposes. We further studied the 245,109 antibody chains from patent literature to reveal that they very well reflect the primary sequences of antibody therapeutics in clinical use. This suggests that the patent literature could serve as a reference for previous engineering efforts to improve rational antibody design.
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Affiliation(s)
- Konrad Krawczyk
- Research and Development, Natural Antibody, Hamburg, Germany
| | - Andrew Buchanan
- Department of Bio and Health Informatics, R&D, AstraZeneca, Cambridge, UK
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28
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Madan B, Zhang B, Xu K, Chao CW, O'Dell S, Wolfe JR, Chuang GY, Fahad AS, Geng H, Kong R, Louder MK, Nguyen TD, Rawi R, Schön A, Sheng Z, Nimrania R, Wang Y, Zhou T, Lin BC, Doria-Rose NA, Shapiro L, Kwong PD, DeKosky BJ. Mutational fitness landscapes reveal genetic and structural improvement pathways for a vaccine-elicited HIV-1 broadly neutralizing antibody. Proc Natl Acad Sci U S A 2021; 118:e2011653118. [PMID: 33649208 PMCID: PMC7958426 DOI: 10.1073/pnas.2011653118] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Vaccine-based elicitation of broadly neutralizing antibodies holds great promise for preventing HIV-1 transmission. However, the key biophysical markers of improved antibody recognition remain uncertain in the diverse landscape of potential antibody mutation pathways, and a more complete understanding of anti-HIV-1 fusion peptide (FP) antibody development will accelerate rational vaccine designs. Here we survey the mutational landscape of the vaccine-elicited anti-FP antibody, vFP16.02, to determine the genetic, structural, and functional features associated with antibody improvement or fitness. Using site-saturation mutagenesis and yeast display functional screening, we found that 1% of possible single mutations improved HIV-1 envelope trimer (Env) affinity, but generally comprised rare somatic hypermutations that may not arise frequently in vivo. We observed that many single mutations in the vFP16.02 Fab could enhance affinity >1,000-fold against soluble FP, although affinity improvements against the HIV-1 trimer were more measured and rare. The most potent variants enhanced affinity to both soluble FP and Env, had mutations concentrated in antibody framework regions, and achieved up to 37% neutralization breadth compared to 28% neutralization of the template antibody. Altered heavy- and light-chain interface angles and conformational dynamics, as well as reduced Fab thermal stability, were associated with improved HIV-1 neutralization breadth and potency. We also observed parallel sets of mutations that enhanced viral neutralization through similar structural mechanisms. These data provide a quantitative understanding of the mutational landscape for vaccine-elicited FP-directed broadly neutralizing antibody and demonstrate that numerous antigen-distal framework mutations can improve antibody function by enhancing affinity simultaneously toward HIV-1 Env and FP.
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Affiliation(s)
- Bharat Madan
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS 66045
| | - Baoshan Zhang
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Kai Xu
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Cara W Chao
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Sijy O'Dell
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Jacy R Wolfe
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS 66045
| | - Gwo-Yu Chuang
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Ahmed S Fahad
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS 66045
| | - Hui Geng
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Rui Kong
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Mark K Louder
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Thuy Duong Nguyen
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS 66045
| | - Reda Rawi
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Arne Schön
- Department of Biology, John Hopkins University, Baltimore, MD 21218
| | - Zizhang Sheng
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10027
| | - Rajani Nimrania
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS 66045
| | - Yiran Wang
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Tongqing Zhou
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Bob C Lin
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Nicole A Doria-Rose
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
| | - Lawrence Shapiro
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10027
- Aaron Diamond AIDS Research Center, Columbia University Irving Medical Center, New York, NY 10032
| | - Peter D Kwong
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10027
| | - Brandon J DeKosky
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS 66045;
- Department of Chemical Engineering, The University of Kansas, Lawrence, KS 66045
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29
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Affinity maturation: highlights in the application of in vitro strategies for the directed evolution of antibodies. Emerg Top Life Sci 2021; 5:601-608. [PMID: 33660765 PMCID: PMC8726058 DOI: 10.1042/etls20200331] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 02/16/2021] [Accepted: 02/23/2021] [Indexed: 01/04/2023]
Abstract
Affinity maturation is a key technique in protein engineering which is used to improve affinity and binding interactions in vitro, a process often required to fulfil the therapeutic potential of antibodies. There are many available display technologies and maturation methods developed over the years, which have been instrumental in the production of therapeutic antibodies. However, due to the inherent limitations in display capacity of these technologies, accommodation of expansive and complex library builds is still a challenge. In this article, we discuss our recent efforts in the affinity maturation of a difficult antibody lineage using an unbiased approach, which sought to explore a larger sequence space through the application of DNA recombination and shuffling techniques across the entire antibody region and selections using ribosome display. We also highlight the key features of several display technologies and diversification methods, and discuss the strategies devised by different groups in response to different challenges. Particular attention is drawn to examples which are aimed at the expansion of sequence, structural or experimental diversity through different means and approaches. Here, we provide our perspectives on these methodologies and the considerations involved in the design of effective strategies for the directed evolution of antibodies.
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30
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Hsiao YC, Chen YJJ, Goldstein LD, Wu J, Lin Z, Schneider K, Chaudhuri S, Antony A, Bajaj Pahuja K, Modrusan Z, Seshasayee D, Seshagiri S, Hötzel I. Restricted epitope specificity determined by variable region germline segment pairing in rodent antibody repertoires. MAbs 2021; 12:1722541. [PMID: 32041466 PMCID: PMC7039645 DOI: 10.1080/19420862.2020.1722541] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Antibodies from B-cell clonal lineages share sequence and structural properties as well as epitope specificity. Clonally unrelated antibodies can similarly share sequence and specificity properties and are said to be convergent. Convergent antibody responses against several antigens have been described in humans and mice and include different classes of shared sequence features. In particular, some antigens and epitopes can induce convergent responses of clonally unrelated antibodies with restricted heavy (VH) and light (VL) chain variable region germline segment usage without similarity in the heavy chain third complementarity-determining region (CDR H3), a critical specificity determinant. Whether these V germline segment-restricted responses reflect a general epitope specificity restriction of antibodies with shared VH/VL pairing is not known. Here, we investigated this question by determining patterns of antigen binding competition between clonally unrelated antigen-specific rat antibodies from paired-chain deep sequencing datasets selected based solely on VH/VL pairing. We found that antibodies with shared VH/VL germline segment pairings but divergent CDR H3 sequences almost invariably have restricted epitope specificity indicated by shared binding competition patterns. This epitope restriction included 82 of 85 clonally unrelated antibodies with 13 different VH/VL pairings binding in 8 epitope groups in 2 antigens. The corollary that antibodies with shared VH/VL pairing and epitope-restricted binding can accommodate widely divergent CDR H3 sequences was confirmed by in vitro selection of variants of anti-human epidermal growth factor receptor 2 antibodies known to mediate critical antigen interactions through CDR H3. Our results show that restricted epitope specificity determined by VH/VL germline segment pairing is a general property of rodent antigen-specific antibodies.
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Affiliation(s)
- Yi-Chun Hsiao
- Department of Antibody Engineering, Genentech, South San Francisco, CA, USA
| | - Ying-Jiun J Chen
- Department of Molecular Biology, Genentech, South San Francisco, CA, USA
| | - Leonard D Goldstein
- Department of Molecular Biology, Genentech, South San Francisco, CA, USA.,Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA, USA
| | - Jia Wu
- Department of Antibody Engineering, Genentech, South San Francisco, CA, USA
| | - Zhonghua Lin
- Department of Antibody Engineering, Genentech, South San Francisco, CA, USA
| | - Kellen Schneider
- Department of Antibody Engineering, Genentech, South San Francisco, CA, USA
| | - Subhra Chaudhuri
- Department of Molecular Biology, Genentech, South San Francisco, CA, USA
| | - Aju Antony
- Department of Molecular Biology, SciGenom Labs, Cochin, India
| | | | - Zora Modrusan
- Department of Molecular Biology, Genentech, South San Francisco, CA, USA
| | - Dhaya Seshasayee
- Department of Antibody Engineering, Genentech, South San Francisco, CA, USA
| | | | - Isidro Hötzel
- Department of Antibody Engineering, Genentech, South San Francisco, CA, USA
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31
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Jo S, Xu A, Curtis JE, Somani S, MacKerell AD. Computational Characterization of Antibody-Excipient Interactions for Rational Excipient Selection Using the Site Identification by Ligand Competitive Saturation-Biologics Approach. Mol Pharm 2020; 17:4323-4333. [PMID: 32965126 DOI: 10.1021/acs.molpharmaceut.0c00775] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Protein therapeutics typically require a concentrated protein formulation, which can lead to self-association and/or high viscosity due to protein-protein interaction (PPI). Excipients are often added to improve stability, bioavailability, and manufacturability of the protein therapeutics, but the selection of excipients often relies on trial and error. Therefore, understanding the excipient-protein interaction and its effect on non-specific PPI is important for rational selection of formulation development. In this study, we validate a general workflow based on the site identification by ligand competitive saturation (SILCS) technology, termed SILCS-Biologics, that can be applied to protein therapeutics for rational excipient selection. The National Institute of Standards and Technology monoclonal antibody (NISTmAb) reference along with the CNTO607 mAb is used as model antibody proteins to examine PPIs, and NISTmAb was used to further examine excipient-protein interactions, in silico. Metrics from SILCS include the distribution and predicted affinity of excipients, buffer interactions with the NISTmAb Fab, and the relation of the interactions to predicted PPI. Comparison with a range of experimental data showed multiple SILCS metrics to be predictive. Specifically, the number of favorable sites to which an excipient binds and the number of sites to which an excipient binds that are involved in predicted PPIs correlate with the experimentally determined viscosity. In addition, a combination of the number of binding sites and the predicted binding affinity is indicated to be predictive of relative protein stability. Comparison of arginine, trehalose, and sucrose, all of which give the highest viscosity in combination with analysis of B22 and kD and the SILCS metrics, indicates that higher viscosities are associated with a low number of predicted binding sites, with lower binding affinity of arginine leading to its anomalously high impact on viscosity. The present study indicates the potential for the SILCS-Biologics approach to be of utility in the rational design of excipients during biologics formulation.
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Affiliation(s)
- Sunhwan Jo
- SilcsBio, LLC, 8 Market Place, Suite 300, Baltimore, Maryland 21202, United States
| | - Amy Xu
- NIST Center for Neutron Research, National Institute of Standards and Technology, 100 Bureau Drive, Mail Stop 6102, Gaithersburg, Maryland 20899, United States
| | - Joseph E Curtis
- NIST Center for Neutron Research, National Institute of Standards and Technology, 100 Bureau Drive, Mail Stop 6102, Gaithersburg, Maryland 20899, United States
| | - Sandeep Somani
- Discovery Sciences, Janssen Research and Development (Janssen R&D), Spring House, Pennsylvania 19477, United States
| | - Alexander D MacKerell
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, 20 Penn Street, Baltimore, Maryland 21201, United States
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32
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Norman RA, Ambrosetti F, Bonvin AMJJ, Colwell LJ, Kelm S, Kumar S, Krawczyk K. Computational approaches to therapeutic antibody design: established methods and emerging trends. Brief Bioinform 2020; 21:1549-1567. [PMID: 31626279 PMCID: PMC7947987 DOI: 10.1093/bib/bbz095] [Citation(s) in RCA: 106] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 06/07/2019] [Accepted: 07/05/2019] [Indexed: 12/31/2022] Open
Abstract
Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.
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33
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Kumar S, Ju B, Shapero B, Lin X, Ren L, Zhang L, Li D, Zhou Z, Feng Y, Sou C, Mann CJ, Hao Y, Sarkar A, Hou J, Nunnally C, Hong K, Wang S, Ge X, Su B, Landais E, Sok D, Zwick MB, He L, Zhu J, Wilson IA, Shao Y. A V H1-69 antibody lineage from an infected Chinese donor potently neutralizes HIV-1 by targeting the V3 glycan supersite. SCIENCE ADVANCES 2020; 6:eabb1328. [PMID: 32938661 PMCID: PMC7494343 DOI: 10.1126/sciadv.abb1328] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 07/31/2020] [Indexed: 05/03/2023]
Abstract
An oligomannose patch around the V3 base of HIV-1 envelope glycoprotein (Env) is recognized by multiple classes of broadly neutralizing antibodies (bNAbs). Here, we investigated the bNAb response to the V3 glycan supersite in an HIV-1-infected Chinese donor by Env-specific single B cell sorting, structural and functional studies, and longitudinal analysis of antibody and virus repertoires. Monoclonal antibodies 438-B11 and 438-D5 were isolated that potently neutralize HIV-1 with moderate breadth, are encoded by the VH1-69 germline gene, and have a disulfide-linked long HCDR3 loop. Crystal structures of Env-bound and unbound antibodies revealed heavy chain-mediated recognition of the glycan supersite with a unique angle of approach and a critical role of the intra-HCDR3 disulfide. The mechanism of viral escape was examined via single-genome amplification/sequencing and glycan mutations around the N332 supersite. Our findings further emphasize the V3 glycan supersite as a prominent target for Env-based vaccine design.
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Affiliation(s)
- Sonu Kumar
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
- IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, CA 92037, USA
- Consortium for HIV/AIDS Vaccine Development (CHAVD), The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Bin Ju
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
- School of Medicine, Nankai University, Nankai District, Tianjin 300071, China
| | - Benjamin Shapero
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Xiaohe Lin
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Li Ren
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Lei Zhang
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Dan Li
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Zehua Zhou
- School of Medicine, Nankai University, Nankai District, Tianjin 300071, China
| | - Yi Feng
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Cindy Sou
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Colin J Mann
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Yanling Hao
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Anita Sarkar
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
- IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, CA 92037, USA
- Consortium for HIV/AIDS Vaccine Development (CHAVD), The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Jiali Hou
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Christian Nunnally
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Kunxue Hong
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Shuo Wang
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Xiangyang Ge
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China
| | - Bin Su
- Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui Province 230601, China
| | - Elise Landais
- IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, CA 92037, USA
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA
- International AIDS Vaccine Initiative, New York, NY 10004, USA
| | - Devin Sok
- IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, CA 92037, USA
- Consortium for HIV/AIDS Vaccine Development (CHAVD), The Scripps Research Institute, La Jolla, CA 92037, USA
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA
- International AIDS Vaccine Initiative, New York, NY 10004, USA
| | - Michael B Zwick
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Linling He
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Jiang Zhu
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.
| | - Ian A Wilson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.
- IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, CA 92037, USA
- Consortium for HIV/AIDS Vaccine Development (CHAVD), The Scripps Research Institute, La Jolla, CA 92037, USA
- Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Yiming Shao
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Changping District, Beijing 102206, China.
- School of Medicine, Nankai University, Nankai District, Tianjin 300071, China
- The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China
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34
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Zhou JO, Zaidi HA, Ton T, Fera D. The Effects of Framework Mutations at the Variable Domain Interface on Antibody Affinity Maturation in an HIV-1 Broadly Neutralizing Antibody Lineage. Front Immunol 2020; 11:1529. [PMID: 32765530 PMCID: PMC7379371 DOI: 10.3389/fimmu.2020.01529] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 06/10/2020] [Indexed: 11/30/2022] Open
Abstract
Understanding affinity maturation of antibodies that can target many variants of HIV-1 is important for vaccine development. While the antigen-binding site of antibodies is known to mutate throughout the co-evolution of antibodies and viruses in infected individuals, the roles of the mutations in the antibody framework region are not well understood. Throughout affinity maturation, the CH103 broadly neutralizing antibody lineage, from an individual designated CH505, altered the orientation of one of its antibody variable domains. The change in orientation was a response to insertions in the variable loop 5 (V5) of the HIV envelope. In this study, we generated CH103 lineage antibody variants in which residues in the variable domain interface were mutated, and measured the binding to both autologous and heterologous HIV-1 envelopes. Our data show that very few mutations in an early intermediate antibody of the lineage can improve binding toward both autologous and heterologous HIV-1 envelopes. We also crystallized an antibody mutant to show that framework mutations alone can result in a shift in relative orientations of the variable domains. Taken together, our results demonstrate the functional importance of residues located outside the antigen-binding site in affinity maturation.
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Affiliation(s)
- Jeffrey O Zhou
- Department of Chemistry and Biochemistry, Swarthmore College, Swarthmore, PA, United States
| | - Hussain A Zaidi
- Department of Chemistry and Biochemistry, Swarthmore College, Swarthmore, PA, United States
| | - Therese Ton
- Department of Biology, Swarthmore College, Swarthmore, PA, United States
| | - Daniela Fera
- Department of Chemistry and Biochemistry, Swarthmore College, Swarthmore, PA, United States
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35
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Crean RM, Gardner JM, Kamerlin SCL. Harnessing Conformational Plasticity to Generate Designer Enzymes. J Am Chem Soc 2020; 142:11324-11342. [PMID: 32496764 PMCID: PMC7467679 DOI: 10.1021/jacs.0c04924] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Indexed: 02/08/2023]
Abstract
Recent years have witnessed an explosion of interest in understanding the role of conformational dynamics both in the evolution of new enzymatic activities from existing enzymes and in facilitating the emergence of enzymatic activity de novo on scaffolds that were previously non-catalytic. There are also an increasing number of examples in the literature of targeted engineering of conformational dynamics being successfully used to alter enzyme selectivity and activity. Despite the obvious importance of conformational dynamics to both enzyme function and evolvability, many (although not all) computational design approaches still focus either on pure sequence-based approaches or on using structures with limited flexibility to guide the design. However, there exist a wide variety of computational approaches that can be (re)purposed to introduce conformational dynamics as a key consideration in the design process. Coupled with laboratory evolution and more conventional existing sequence- and structure-based approaches, these techniques provide powerful tools for greatly expanding the protein engineering toolkit. This Perspective provides an overview of evolutionary studies that have dissected the role of conformational dynamics in facilitating the emergence of novel enzymes, as well as advances in computational approaches that allow one to target conformational dynamics as part of enzyme design. Harnessing conformational dynamics in engineering studies is a powerful paradigm with which to engineer the next generation of designer biocatalysts.
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Affiliation(s)
- Rory M. Crean
- Department of Chemistry -
BMC, Uppsala University, Box 576, 751 23 Uppsala, Sweden
| | - Jasmine M. Gardner
- Department of Chemistry -
BMC, Uppsala University, Box 576, 751 23 Uppsala, Sweden
| | - Shina C. L. Kamerlin
- Department of Chemistry -
BMC, Uppsala University, Box 576, 751 23 Uppsala, Sweden
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36
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van der Kant R, Bauer J, Karow-Zwick AR, Kube S, Garidel P, Blech M, Rousseau F, Schymkowitz J. Adaption of human antibody λ and κ light chain architectures to CDR repertoires. Protein Eng Des Sel 2020; 32:109-127. [PMID: 31535139 PMCID: PMC6908821 DOI: 10.1093/protein/gzz012] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 06/11/2019] [Indexed: 12/16/2022] Open
Abstract
Monoclonal antibodies bind with high specificity to a wide range of diverse antigens, primarily mediated by their hypervariable complementarity determining regions (CDRs). The defined antigen binding loops are supported by the structurally conserved β-sandwich framework of the light chain (LC) and heavy chain (HC) variable regions. The LC genes are encoded by two separate loci, subdividing the entity of antibodies into kappa (LCκ) and lambda (LCλ) isotypes that exhibit distinct sequence and conformational preferences. In this work, a diverse set of techniques were employed including machine learning, force field analysis, statistical coupling analysis and mutual information analysis of a non-redundant antibody structure collection. Thereby, it was revealed how subtle changes between the structures of LCκ and LCλ isotypes increase the diversity of antibodies, extending the predetermined restrictions of the general antibody fold and expanding the diversity of antigen binding. Interestingly, it was found that the characteristic framework scaffolds of κ and λ are stabilized by diverse amino acid clusters that determine the interplay between the respective fold and the embedded CDR loops. In conclusion, this work reveals how antibodies use the remarkable plasticity of the beta-sandwich Ig fold to incorporate a large diversity of CDR loops.
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Affiliation(s)
- Rob van der Kant
- Switch Laboratory, VIB Center for Brain and Disease Research, Herestraat 49, Leuven, Belgium.,Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box, B-3000 Leuven, Belgium
| | - Joschka Bauer
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
| | | | - Sebastian Kube
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
| | - Patrick Garidel
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
| | - Michaela Blech
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
| | - Frederic Rousseau
- Switch Laboratory, VIB Center for Brain and Disease Research, Herestraat 49, Leuven, Belgium.,Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box, B-3000 Leuven, Belgium
| | - Joost Schymkowitz
- Switch Laboratory, VIB Center for Brain and Disease Research, Herestraat 49, Leuven, Belgium.,Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box, B-3000 Leuven, Belgium
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37
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Simons JF, Lim YW, Carter KP, Wagner EK, Wayham N, Adler AS, Johnson DS. Affinity maturation of antibodies by combinatorial codon mutagenesis versus error-prone PCR. MAbs 2020; 12:1803646. [PMID: 32744131 PMCID: PMC7531523 DOI: 10.1080/19420862.2020.1803646] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/22/2020] [Accepted: 07/27/2020] [Indexed: 01/08/2023] Open
Abstract
IN VITRO affinity maturation of therapeutic monoclonal antibodies is commonly applied to achieve desired properties, such as improved binding kinetics and affinity. Currently there are no universally accepted protocols for generation of variegated antibody libraries or selection thereof. Here, we performed affinity maturation using a yeast-based single-chain variable fragment (scFv) expression system to compare two mutagenesis methods: random mutagenesis across the entire V(D)J region by error-prone PCR, and a novel combinatorial mutagenesis process limited to the complementarity-determining regions (CDRs). We applied both methods of mutagenesis to four human antibodies against well-known immuno-oncology target proteins. Detailed sequence analysis showed an even mutational distribution across the entire length of the scFv for the error-prone PCR method and an almost exclusive targeting of the CDRs for the combinatorial method. Though there were distinct mutagenesis profiles for each target antibody and mutagenesis method, we found that both methods improved scFv affinity with similar efficiency. When a subset of the affinity-matured antibodies was expressed as full-length immunoglobulin, the measured affinity constants were mostly comparable to those of the respective scFv, but the full-length antibodies were inferior to their scFv counterparts for one of the targets. Furthermore, we found that improved affinity for the full-length antibody did not always translate into enhanced binding to cell-surface expressed antigen or improved immune checkpoint blocking ability, suggesting that screening with full-length antibody or antigen-binding fragment formats might be advantageous and the subject of a future study.
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38
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Barreto K, Maruthachalam BV, Hill W, Hogan D, Sutherland AR, Kusalik A, Fonge H, DeCoteau JF, Geyer CR. Next-generation sequencing-guided identification and reconstruction of antibody CDR combinations from phage selection outputs. Nucleic Acids Res 2019; 47:e50. [PMID: 30854567 PMCID: PMC6511873 DOI: 10.1093/nar/gkz131] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 12/12/2018] [Accepted: 03/07/2019] [Indexed: 12/12/2022] Open
Abstract
Next-generation sequencing (NGS) technologies have been employed in several phage display platforms for analyzing natural and synthetic antibody sequences and for identifying and reconstructing single-chain variable fragments (scFv) and antigen-binding fragments (Fab) not found by conventional ELISA screens. In this work, we developed an NGS-assisted antibody discovery platform by integrating phage-displayed, single-framework, synthetic Fab libraries. Due to limitations in attainable read and amplicon lengths, NGS analysis of Fab libraries and selection outputs is usually restricted to either VH or VL. Since this information alone is not sufficient for high-throughput reconstruction of Fabs, we developed a rapid and simple method for linking and sequencing all diversified CDRs in phage Fab pools. Our method resulted in a reliable and straightforward platform for converting NGS information into Fab clones. We used our NGS-assisted Fab reconstruction method to recover low-frequency rare clones from phage selection outputs. While previous studies chose rare clones for rescue based on their relative frequencies in sequencing outputs, we chose rare clones for reconstruction from less-frequent CDRH3 lengths. In some cases, reconstructed rare clones (frequency ∼0.1%) showed higher affinity and better specificity than high-frequency top clones identified by Sanger sequencing, highlighting the significance of NGS-based approaches in synthetic antibody discovery.
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Affiliation(s)
- Kris Barreto
- Department of Pathology, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
| | | | - Wayne Hill
- Department of Pathology, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
| | - Daniel Hogan
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada
| | - Ashley R Sutherland
- Department of Biochemistry, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
| | - Anthony Kusalik
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada
| | - Humphrey Fonge
- Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
| | - John F DeCoteau
- Department of Pathology, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
| | - C Ronald Geyer
- Department of Pathology, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
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39
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Cornwell O, Bond NJ, Radford SE, Ashcroft AE. Long-Range Conformational Changes in Monoclonal Antibodies Revealed Using FPOP-LC-MS/MS. Anal Chem 2019; 91:15163-15170. [DOI: 10.1021/acs.analchem.9b03958] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Owen Cornwell
- Astbury Centre for Structural Molecular Biology and School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, U.K
| | - Nicholas J. Bond
- Analytical Sciences, BioPharmaceutical Development, BioPharmaceuticals R&D, AstraZeneca, Granta Park, Cambridge, CB21 6GH, U.K
| | - Sheena E. Radford
- Astbury Centre for Structural Molecular Biology and School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, U.K
| | - Alison E. Ashcroft
- Astbury Centre for Structural Molecular Biology and School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, U.K
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40
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Esposito D, Weile J, Shendure J, Starita LM, Papenfuss AT, Roth FP, Fowler DM, Rubin AF. MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect. Genome Biol 2019; 20:223. [PMID: 31679514 PMCID: PMC6827219 DOI: 10.1186/s13059-019-1845-6] [Citation(s) in RCA: 112] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Accepted: 10/01/2019] [Indexed: 11/10/2022] Open
Abstract
Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here, we present MaveDB ( https://www.mavedb.org ), a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first such application, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.
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Affiliation(s)
- Daniel Esposito
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Jochen Weile
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Anthony T Papenfuss
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia
- Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
- Department of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
| | - Frederick P Roth
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada.
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- Department of Computer Science, University of Toronto, Toronto, ON, Canada.
- Canadian Institute for Advanced Research, Toronto, ON, Canada.
| | - Douglas M Fowler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Canadian Institute for Advanced Research, Toronto, ON, Canada.
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
| | - Alan F Rubin
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.
- Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia.
- Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
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41
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Guo Y, Chen K, Kwong PD, Shapiro L, Sheng Z. cAb-Rep: A Database of Curated Antibody Repertoires for Exploring Antibody Diversity and Predicting Antibody Prevalence. Front Immunol 2019; 10:2365. [PMID: 31649674 PMCID: PMC6794461 DOI: 10.3389/fimmu.2019.02365] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 09/20/2019] [Indexed: 12/18/2022] Open
Abstract
The diversity of B cell receptors provides a basis for recognizing numerous pathogens. Antibody repertoire sequencing has revealed relationships between B cell receptor sequences, their diversity, and their function in infection, vaccination, and disease. However, many repertoire datasets have been deposited without annotation or quality control, limiting their utility. To accelerate investigations of B cell immunoglobulin sequence repertoires and to facilitate development of algorithms for their analysis, we constructed a comprehensive public database of curated human B cell immunoglobulin sequence repertoires, cAb-Rep (https://cab-rep.c2b2.columbia.edu), which currently includes 306 immunoglobulin repertoires from 121 human donors, who were healthy, vaccinated, or had autoimmune disease. The database contains a total of 267.9 million V(D)J heavy chain and 72.9 million VJ light chain transcripts. These transcripts are full-length or near full-length, have been annotated with gene origin, antibody isotype, somatic hypermutations, and other biological characteristics, and are stored in FASTA format to facilitate their direct use by most current repertoire-analysis programs. We describe a website to search cAb-Rep for similar antibodies along with methods for analysis of the prevalence of antibodies with specific genetic signatures, for estimation of reproducibility of somatic hypermutation patterns of interest, and for delineating frequencies of somatically introduced N-glycosylation. cAb-Rep should be useful for investigating attributes of B cell sequence repertoires, for understanding characteristics of affinity maturation, and for identifying potential barriers to the elicitation of effective neutralizing antibodies in infection or by vaccination.
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Affiliation(s)
- Yicheng Guo
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Kevin Chen
- College of Arts and Science, Stony Brook University, Stony Brook, NY, United States
| | - Peter D Kwong
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, United States
| | - Lawrence Shapiro
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States.,Vaccine Research Center, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, United States
| | - Zizhang Sheng
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
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42
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Warszawski S, Borenstein Katz A, Lipsh R, Khmelnitsky L, Ben Nissan G, Javitt G, Dym O, Unger T, Knop O, Albeck S, Diskin R, Fass D, Sharon M, Fleishman SJ. Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces. PLoS Comput Biol 2019; 15:e1007207. [PMID: 31442220 PMCID: PMC6728052 DOI: 10.1371/journal.pcbi.1007207] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Revised: 09/05/2019] [Accepted: 06/21/2019] [Indexed: 11/18/2022] Open
Abstract
Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.
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Affiliation(s)
- Shira Warszawski
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | | | - Rosalie Lipsh
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Lev Khmelnitsky
- Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Gili Ben Nissan
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Gabriel Javitt
- Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Orly Dym
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot, Israel
| | - Tamar Unger
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot, Israel
| | - Orli Knop
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Shira Albeck
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot, Israel
| | - Ron Diskin
- Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Deborah Fass
- Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Michal Sharon
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Sarel J. Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
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43
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Mathur M, Kim CM, Munro SA, Rudina SS, Sawyer EM, Smolke CD. Programmable mutually exclusive alternative splicing for generating RNA and protein diversity. Nat Commun 2019; 10:2673. [PMID: 31209208 PMCID: PMC6572816 DOI: 10.1038/s41467-019-10403-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 05/01/2019] [Indexed: 02/07/2023] Open
Abstract
Alternative splicing performs a central role in expanding genomic coding capacity and proteomic diversity. However, programming of splicing patterns in engineered biological systems remains underused. Synthetic approaches thus far have predominantly focused on controlling expression of a single protein through alternative splicing. Here, we describe a modular and extensible platform for regulating four programmable exons that undergo a mutually exclusive alternative splicing event to generate multiple functionally-distinct proteins. We present an intron framework that enforces the mutual exclusivity of two internal exons and demonstrate a graded series of consensus sequence elements of varying strengths that set the ratio of two mutually exclusive isoforms. We apply this framework to program the DNA-binding domains of modular transcription factors to differentially control downstream gene activation. This splicing platform advances an approach for generating diverse isoforms and can ultimately be applied to program modular proteins and increase coding capacity of synthetic biological systems.
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Affiliation(s)
- Melina Mathur
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Cameron M Kim
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Sarah A Munro
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- Joint Initiative for Metrology in Biology, Stanford, CA, 94305, USA
- Genome-scale Measurements Group, National Institute of Standards and Technology, Stanford, CA, 94305, USA
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Shireen S Rudina
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Eric M Sawyer
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Christina D Smolke
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
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44
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Koksal AC, Pennini ME, Marelli M, Xiao X, Dall'Acqua WF. Functional mimetic of the G-protein coupled receptor CXCR4 on a soluble antibody scaffold. MAbs 2019; 11:725-734. [PMID: 30900513 DOI: 10.1080/19420862.2019.1596703] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
G-protein coupled receptors (GPCRs) constitute major drug targets due to their involvement in critical biological functions and pathophysiological disorders. The leading challenge in their structural and functional characterization has been the need for a lipid environment to accommodate their hydrophobic cores. Here, we report an antibody scaffold mimetic (ASM) platform where we have recapitulated the extracellular functional domains of the GPCR, C-X-C chemokine receptor 4 (CXCR4) on a soluble antibody framework. The engineered ASM molecule can accommodate the N-terminal loop and all three extracellular loops of CXCR4. These extracellular features are important players in ligand recruitment and interaction for allostery and signal transduction. Our study shows that ASMCXCR4 can be recognized by the anti-CXCR4 antibodies, MEDI3185, 2B11, and 12G5, and that ASMCXCR4 can bind the HIV-1 glycoprotein ligand gp120, and the natural chemokine ligand SDF-1α. Further, we show that ASMCXCR4 can competitively inhibit the SDF-1α signaling pathway, and be used as an immunogen to generate CXCR4-specific antibodies. This platform will be useful in the study of GPCR biology in a soluble receptor context for evaluating its extracellular ligand interactions.
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Affiliation(s)
- Adem C Koksal
- a Department of Antibody Discovery and Protein Engineering , AstraZeneca , Gaithersburg , MD , USA
| | - Meghan E Pennini
- b Microbial Sciences , MedImmune, AstraZeneca , Gaithersburg , MD , USA
| | - Marcello Marelli
- a Department of Antibody Discovery and Protein Engineering , AstraZeneca , Gaithersburg , MD , USA
| | - Xiaodong Xiao
- a Department of Antibody Discovery and Protein Engineering , AstraZeneca , Gaithersburg , MD , USA
| | - William F Dall'Acqua
- a Department of Antibody Discovery and Protein Engineering , AstraZeneca , Gaithersburg , MD , USA
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45
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Qiu C, Kaplan CD. Functional assays for transcription mechanisms in high-throughput. Methods 2019; 159-160:115-123. [PMID: 30797033 PMCID: PMC6589137 DOI: 10.1016/j.ymeth.2019.02.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 02/18/2019] [Indexed: 01/12/2023] Open
Abstract
Dramatic increases in the scale of programmed synthesis of nucleic acid libraries coupled with deep sequencing have powered advances in understanding nucleic acid and protein biology. Biological systems centering on nucleic acids or encoded proteins greatly benefit from such high-throughput studies, given that large DNA variant pools can be synthesized and DNA, or RNA products of transcription, can be easily analyzed by deep sequencing. Here we review the scope of various high-throughput functional assays for studies of nucleic acids and proteins in general, followed by discussion of how these types of study have yielded insights into the RNA Polymerase II (Pol II) active site as an example. We discuss methodological considerations in the design and execution of these experiments that should be valuable to studies in any system.
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Affiliation(s)
- Chenxi Qiu
- Department of Medicine, Division of Translational Therapeutics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA; Cancer Research Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Craig D Kaplan
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA.
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46
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Faber MS, Whitehead TA. Data-driven engineering of protein therapeutics. Curr Opin Biotechnol 2019; 60:104-110. [PMID: 30822697 DOI: 10.1016/j.copbio.2019.01.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 11/16/2018] [Accepted: 01/21/2019] [Indexed: 12/26/2022]
Abstract
Protein therapeutics requires a series of properties beyond biochemical activity, including serum stability, low immunogenicity, and manufacturability. Mutations that improve one property often decrease one or more of the other essential requirements for therapeutic efficacy, making the protein engineering challenge difficult. The past decade has seen an explosion of new techniques centered around cheaply reading and writing DNA. This review highlights the recent use of such high throughput technologies for engineering protein therapeutics. Examples include the use of human antibody repertoire sequence data to pair antibody heavy and light chains, comprehensive mutational analysis for engineering antibody specificity, and the use of ancestral and inter-species sequence data to engineer simultaneous improvements in enzyme catalytic efficiency and stability. We conclude with a perspective on further ways to integrate mature protein engineering pipelines with the exponential increases in the volume of sequencing data expected in the forthcoming decade.
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Affiliation(s)
- Matthew S Faber
- Dept. Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, United States
| | - Timothy A Whitehead
- Dept. of Chemical Engineering & Materials Science, Michigan State University, East Lansing, MI 48824, United States; Dept. of Biosystems Engineering, Michigan State University, East Lansing, MI 48824, United States; Dept. of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, United States; Institute for Quantitative Biology, Michigan State University, East Lansing, MI 48824, United States.
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47
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Henderson R, Watts BE, Ergin HN, Anasti K, Parks R, Xia SM, Trama A, Liao HX, Saunders KO, Bonsignori M, Wiehe K, Haynes BF, Alam SM. Selection of immunoglobulin elbow region mutations impacts interdomain conformational flexibility in HIV-1 broadly neutralizing antibodies. Nat Commun 2019; 10:654. [PMID: 30737386 PMCID: PMC6368608 DOI: 10.1038/s41467-019-08415-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 01/04/2019] [Indexed: 01/07/2023] Open
Abstract
Somatic mutations within antibody variable and framework regions (FWR) can alter thermostability and structural flexibility, but their impact on functional potency is unclear. Here we study thermostability and use molecular dynamics (MD) simulations to assess the role of FWR mutations during maturation of HIV-1 broadly neutralizing antibodies (bnAbs). The tested bnAbs show lower thermostability than their unmutated ancestor antibodies. FWR mutations in the Fab elbow region are frequently observed in HIV-1 bnAbs and MD simulations show that such FWR mutations alter interdomain flexibility in two HIV-1 bnAbs. In a CD4-binding site lineage, reversion mutations result in a loss of neutralization potency in an early intermediate and affinity-matured bnAb against autologous and heterologous Tier-2 viruses, respectively. Elbow region reversion mutations in a glycan-V3 bnAb modestly reduces potency against an autologous virus isolate. Thus, selection of mutations in the Fab elbow region impacts interdomain conformational flexibility and paratope plasticity during bnAb development.
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Affiliation(s)
- Rory Henderson
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Brian E Watts
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Hieu N Ergin
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Kara Anasti
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Robert Parks
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Shi-Mao Xia
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Ashley Trama
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Hua-Xin Liao
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
- College of Life Science and Technology, Jinan University, Guangzhou, 510632, China
| | - Kevin O Saunders
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Mattia Bonsignori
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Kevin Wiehe
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Barton F Haynes
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA
| | - S Munir Alam
- Department of Medicine, Duke University School of Medicine, Durham, NC, 27710, USA.
- Department of Pathology, Duke University School of Medicine, Durham, NC, 27710, USA.
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48
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Sormanni P, Aprile FA, Vendruscolo M. Third generation antibody discovery methods: in silico rational design. Chem Soc Rev 2018; 47:9137-9157. [PMID: 30298157 DOI: 10.1039/c8cs00523k] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Owing to their outstanding performances in molecular recognition, antibodies are extensively used in research and applications in molecular biology, biotechnology and medicine. Recent advances in experimental and computational methods are making it possible to complement well-established in vivo (first generation) and in vitro (second generation) methods of antibody discovery with novel in silico (third generation) approaches. Here we describe the principles of computational antibody design and review the state of the art in this field. We then present Modular, a method that implements the rational design of antibodies in a modular manner, and describe the opportunities offered by this approach.
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Affiliation(s)
- Pietro Sormanni
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
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49
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Kovaltsuk A, Krawczyk K, Kelm S, Snowden J, Deane CM. Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2018; 201:3694-3704. [PMID: 30397033 PMCID: PMC6485405 DOI: 10.4049/jimmunol.1800669] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 10/02/2018] [Indexed: 01/29/2023]
Abstract
Next-generation sequencing of the Ig gene repertoire (Ig-seq) produces large volumes of information at the nucleotide sequence level. Such data have improved our understanding of immune systems across numerous species and have already been successfully applied in vaccine development and drug discovery. However, the high-throughput nature of Ig-seq means that it is afflicted by high error rates. This has led to the development of error-correction approaches. Computational error-correction methods use sequence information alone, primarily designating sequences as likely to be correct if they are observed frequently. In this work, we describe an orthogonal method for filtering Ig-seq data, which considers the structural viability of each sequence. A typical natural Ab structure requires the presence of a disulfide bridge within each of its variable chains to maintain the fold. Our Ab Sequence Selector (ABOSS) uses the presence/absence of this bridge as a way of both identifying structurally viable sequences and estimating the sequencing error rate. On simulated Ig-seq datasets, ABOSS is able to identify more than 99% of structurally viable sequences. Applying our method to six independent Ig-seq datasets (one mouse and five human), we show that our error calculations are in line with previous experimental and computational error estimates. We also show how ABOSS is able to identify structurally impossible sequences missed by other error-correction methods.
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Affiliation(s)
- Aleksandr Kovaltsuk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | - Konrad Krawczyk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | | | | | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
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50
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Cooke HA, Arndt J, Quan C, Shapiro RI, Wen D, Foley S, Vecchi MM, Preyer M. EFab domain substitution as a solution to the light-chain pairing problem of bispecific antibodies. MAbs 2018; 10:1248-1259. [PMID: 30215570 PMCID: PMC6284599 DOI: 10.1080/19420862.2018.1519631] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Bispecific antibody therapeutics can expand the functionality of a conventional monoclonal antibody drug because they can bind multiple antigens. However, their great potential is counterbalanced by the challenges faced in their production. The classic asymmetric bispecific containing an Fc requires the expression of four unique chains – two light chains and two heavy chains; each light chain must pair with its correct heavy chain, which then must heterodimerize to form the full bispecific. The light-chain pairing problem has several solutions, some of which require engineering and optimization for each bispecific pair. Here, we introduce a technology called EFab Domain Substitution, which replaces the Cϵ2 of IgE for one of the CL/CH1 domains into one arm of an asymmetric bispecific to encourage the correct pairing of the light chains. EFab Domain Substitution provides very robust correct pairing while maintaining antibody function and is effective for many variable domains. We report its effect on the biophysical properties of an antibody and the crystal structure of the EFab domain substituted into the adalimumab Fab (PDB ID 6CR1).
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Affiliation(s)
- Heather A Cooke
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Joe Arndt
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Chao Quan
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Renée I Shapiro
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Dingyi Wen
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Susan Foley
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Malgorzata M Vecchi
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
| | - Martin Preyer
- a Department of Biotherapeutic and Medicinal Sciences , Biogen , Cambridge , MA , USA
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