1
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Gordon GL, Raybould MIJ, Wong A, Deane CM. Prospects for the computational humanization of antibodies and nanobodies. Front Immunol 2024; 15:1399438. [PMID: 38812514 PMCID: PMC11133524 DOI: 10.3389/fimmu.2024.1399438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 05/02/2024] [Indexed: 05/31/2024] Open
Abstract
To be viable therapeutics, antibodies must be tolerated by the human immune system. Rational approaches to reduce the risk of unwanted immunogenicity involve maximizing the 'humanness' of the candidate drug. However, despite the emergence of new discovery technologies, many of which start from entirely human gene fragments, most antibody therapeutics continue to be derived from non-human sources with concomitant humanization to increase their human compatibility. Early experimental humanization strategies that focus on CDR loop grafting onto human frameworks have been critical to the dominance of this discovery route but do not consider the context of each antibody sequence, impacting their success rate. Other challenges include the simultaneous optimization of other drug-like properties alongside humanness and the humanization of fundamentally non-human modalities such as nanobodies. Significant efforts have been made to develop in silico methodologies able to address these issues, most recently incorporating machine learning techniques. Here, we outline these recent advancements in antibody and nanobody humanization, focusing on computational strategies that make use of the increasing volume of sequence and structural data available and the validation of these tools. We highlight that structural distinctions between antibodies and nanobodies make the application of antibody-focused in silico tools to nanobody humanization non-trivial. Furthermore, we discuss the effects of humanizing mutations on other essential drug-like properties such as binding affinity and developability, and methods that aim to tackle this multi-parameter optimization problem.
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Affiliation(s)
| | | | | | - Charlotte M. Deane
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
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2
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Melo-Braga MN, Carvalho MB, Ferreira MCE, Lavinder J, Abbasi A, Palmisano G, Thaysen-Andersen M, Sajadi MM, Ippolito GC, Felicori LF. Unveiling the multifaceted landscape of N-glycosylation in antibody variable domains: Insights and implications. Int J Biol Macromol 2024; 257:128362. [PMID: 38029898 PMCID: PMC11003471 DOI: 10.1016/j.ijbiomac.2023.128362] [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: 09/08/2023] [Revised: 11/02/2023] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
N-glycosylation at the antibody variable domain has emerged as an important modification influencing antibody function. Despite its significance, information regarding its role and regulation remains limited. To address this gap, we comprehensively explored antibody structures housing N-glycosylation within the Protein Data Bank, yielding fresh insights into this intricate landscape. Our findings revealed that among 208 structures, N-glycosylation was more prevalent in human and mouse antibodies containing IGHV1-8 and IGHV2-2 germline genes, respectively. Moreover, our research highlights the potential for somatic hypermutation to introduce N-glycosylation sites by substituting polar residues (Ser or Thr) in germline variable genes with asparagine. Notably, our study underscores the prevalence of N-glycosylation in antiviral antibodies, especially anti-HIV. Besides antigen-antibody interaction, our findings suggest that N-glycosylation may impact antibody specificity, affinity, and avidity by influencing Fab dimer formation and complementary-determining region orientation. We also identified different glycan structures in HIV and SARS-CoV-2 antibody proteomic datasets, highlighting disparities from the N-glycan structures between PDB antibodies and biological repertoires further highlighting the complexity of N-glycosylation patterns. Our findings significantly enrich our understanding of the N-glycosylation's multifaceted characteristics within the antibody variable domain. Additionally, they underscore the pressing imperative for a more comprehensive characterization of its impact on antibody function.
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Affiliation(s)
- Marcella Nunes Melo-Braga
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas da Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
| | - Milene Barbosa Carvalho
- Departamento de Ciência da Computação da Universidade Federal de São João Del Rei, São João Del Rei, MG, Brazil
| | - Manuela Cristina Emiliano Ferreira
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas da Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Jason Lavinder
- Department of Molecular Biosciences, University of Texas, Austin, TX, USA
| | - Abdolrahim Abbasi
- Division of Clinical Care and Research, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Giuseppe Palmisano
- Department of Parasitology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil; School of Natural Sciences, Macquarie University, Sydney, Australia
| | - Morten Thaysen-Andersen
- School of Natural Sciences, Macquarie University, Sydney, Australia; Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan
| | - Mohammad M Sajadi
- Division of Clinical Care and Research, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Gregory C Ippolito
- Department of Molecular Biosciences, University of Texas, Austin, TX, USA
| | - Liza F Felicori
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas da Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
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3
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Gupta S, Nerli S, Kutti Kandy S, Mersky GL, Sgourakis NG. HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes. Nat Commun 2023; 14:6349. [PMID: 37816745 PMCID: PMC10564892 DOI: 10.1038/s41467-023-42163-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 09/29/2023] [Indexed: 10/12/2023] Open
Abstract
The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity.
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Affiliation(s)
- Sagar Gupta
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Santrupti Nerli
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sreeja Kutti Kandy
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Glenn L Mersky
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nikolaos G Sgourakis
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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4
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Maeta S, Nakakido M, Matsuura H, Sakai N, Hirata K, Kuroda D, Fukunaga A, Tsumoto K. Arginine cluster introduction on framework region in anti-lysozyme antibody improved association rate constant by changing conformational diversity of CDR loops. Protein Sci 2023; 32:e4745. [PMID: 37550885 PMCID: PMC10461459 DOI: 10.1002/pro.4745] [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: 12/28/2022] [Revised: 05/30/2023] [Accepted: 08/01/2023] [Indexed: 08/09/2023]
Abstract
Antibodies are used for many therapeutic and biotechnological purposes. Because the affinity of an antibody to the antigen is critical for clinical efficacy of pharmaceuticals, many affinity maturation strategies have been developed. Although we previously reported an affinity maturation strategy in which the association rate of the antibody toward its antigen is improved by introducing a cluster of arginine residues into the framework region of the antibody, the detailed molecular mechanism responsible for this improvement has been unknown. In this study, we introduced five arginine residues into an anti-hen egg white lysozyme antibody (HyHEL10) Fab fragment to create the R5-mutant and comprehensively characterized the interaction between antibody and antigen using thermodynamic analysis, X-ray crystallography, and molecular dynamics (MD) simulations. Our results indicate that introduction of charged residues strongly enhanced the association rate, as previously reported, and the antibody-antigen complex structure was almost the same for the R5-mutant and wild-type Fabs. The MD simulations indicate that the mutation increased conformational diversity in complementarity-determining region loops and thereby enhanced the association rate. These observations provide the molecular basis of affinity maturation by R5 mutation.
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Affiliation(s)
- Shingo Maeta
- Bio‐Diagnostic Reagent Technology CenterSysmex CorporationKobeJapan
- Department of Bioengineering, School of EngineeringThe University of TokyoTokyoJapan
| | - Makoto Nakakido
- Department of Bioengineering, School of EngineeringThe University of TokyoTokyoJapan
- Department of Chemistry and Biotechnology, Graduate School of EngineeringThe University of TokyoTokyoJapan
| | - Hiroaki Matsuura
- Life Science Research Infrastructure Group, RIKEN SPring‐8 CenterSaitamaJapan
| | - Naoki Sakai
- Life Science Research Infrastructure Group, RIKEN SPring‐8 CenterSaitamaJapan
| | - Kunio Hirata
- Life Science Research Infrastructure Group, RIKEN SPring‐8 CenterSaitamaJapan
| | - Daisuke Kuroda
- Department of Bioengineering, School of EngineeringThe University of TokyoTokyoJapan
- Department of Chemistry and Biotechnology, Graduate School of EngineeringThe University of TokyoTokyoJapan
- Research Center for Drug and Vaccine DevelopmentNational Institute of Infectious DiseasesTokyoJapan
| | - Atsushi Fukunaga
- Bio‐Diagnostic Reagent Technology CenterSysmex CorporationKobeJapan
| | - Kouhei Tsumoto
- Department of Bioengineering, School of EngineeringThe University of TokyoTokyoJapan
- Department of Chemistry and Biotechnology, Graduate School of EngineeringThe University of TokyoTokyoJapan
- Institute of Medical ScienceThe University of TokyoTokyoJapan
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5
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Gordon GL, Capel HL, Guloglu B, Richardson E, Stafford RL, Deane CM. A comparison of the binding sites of antibodies and single-domain antibodies. Front Immunol 2023; 14:1231623. [PMID: 37533864 PMCID: PMC10392943 DOI: 10.3389/fimmu.2023.1231623] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 06/27/2023] [Indexed: 08/04/2023] Open
Abstract
Antibodies are the largest class of biotherapeutics. However, in recent years, single-domain antibodies have gained traction due to their smaller size and comparable binding affinity. Antibodies (Abs) and single-domain antibodies (sdAbs) differ in the structures of their binding sites: most significantly, single-domain antibodies lack a light chain and so have just three CDR loops. Given this inherent structural difference, it is important to understand whether Abs and sdAbs are distinguishable in how they engage a binding partner and thus, whether they are suited to different types of epitopes. In this study, we use non-redundant sequence and structural datasets to compare the paratopes, epitopes and antigen interactions of Abs and sdAbs. We demonstrate that even though sdAbs have smaller paratopes, they target epitopes of equal size to those targeted by Abs. To achieve this, the paratopes of sdAbs contribute more interactions per residue than the paratopes of Abs. Additionally, we find that conserved framework residues are of increased importance in the paratopes of sdAbs, suggesting that they include non-specific interactions to achieve comparable affinity. Furthermore, the epitopes of sdAbs are only marginally less accessible than those of Abs: we posit that this may be explained by differences in the orientation and compaction of sdAb and Ab CDR-H3 loops. Overall, our results have important implications for the engineering and humanization of sdAbs, as well as the selection of the best modality for targeting a particular epitope.
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Affiliation(s)
- Gemma L. Gordon
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Henriette L. Capel
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Bora Guloglu
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Eve Richardson
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
| | | | - Charlotte M. Deane
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
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6
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General Trends of the Camelidae Antibody V HHs Domain Dynamics. Int J Mol Sci 2023; 24:ijms24054511. [PMID: 36901942 PMCID: PMC10003728 DOI: 10.3390/ijms24054511] [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: 02/09/2023] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023] Open
Abstract
Conformational flexibility plays an essential role in antibodies' functional and structural stability. They facilitate and determine the strength of antigen-antibody interactions. Camelidae express an interesting subtype of single-chain antibody, named Heavy Chain only Antibody. They have only one N-terminal Variable domain (VHH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, VHH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of VHH domains contributing to these abilities have already been studied compared to classical antibodies. To have the broadest view and understand the changes in dynamics of these macromolecules, large-scale molecular dynamics simulations for a large number of non-redundant VHH structures have been performed for the first time. This analysis reveals the most prevalent movements in these domains. It reveals the four main classes of VHHs dynamics. Diverse local changes were observed in CDRs with various intensities. Similarly, different types of constraints were observed in CDRs, while FRs close to CDRs were sometimes primarily impacted. This study sheds light on the changes in flexibility in different regions of VHH that may impact their in silico design.
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7
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Seidler CA, Kokot J, Fernández-Quintero ML, Liedl KR. Structural Characterization of Nanobodies during Germline Maturation. Biomolecules 2023; 13:380. [PMID: 36830754 PMCID: PMC9953242 DOI: 10.3390/biom13020380] [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: 12/15/2022] [Revised: 01/27/2023] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
Camelid heavy-chain antibody variable domains (VHH), nanobodies, are the smallest-known functional antibody fragments with high therapeutic potential. In this study, we investigate a VHH binding to hen egg-white lysozyme (HEL). We structurally and dynamically characterized the conformational diversity of four VHH variants to elucidate the antigen-binding process. For two of these antibodies, not only are the dissociation constants known, but also the experimentally determined crystal structures of the VHH in complex with HEL are available. We performed well-tempered metadynamics simulations in combination with molecular dynamics simulations to capture a broad conformational space and to reconstruct the thermodynamics and kinetics of conformational transitions in the antigen-binding site, the paratope. By kinetically characterizing the loop movements of the paratope, we found that, with an increase in affinity, the state populations shift towards the binding competent conformation. The contacts contributing to antigen binding, and those who contribute to the overall stability, show a clear trend towards less variable but more intense contacts. Additionally, these investigated nanobodies clearly follow the conformational selection paradigm, as the binding competent conformation pre-exists within the structural ensembles without the presence of the antigen.
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Affiliation(s)
| | | | - Monica L. Fernández-Quintero
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, 6020 Innsbruck, Austria
| | - Klaus R. Liedl
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, 6020 Innsbruck, Austria
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8
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Abstract
The immune systems protect vertebrates from foreign molecules or antigens, and antibodies are important mediators of this system. The sequences and structural features of antibodies vary depending on species. Many of antibodies from vertebrates, including camelids, have both heavy and light chain variable domains, but camelids also have antibodies that lack the light chains. In antibodies that lack light chains, the C-terminal variable region is called the VHH domain. Antibodies recognize antigens through six complementarity-determining regions (CDRs). The third CDR of the heavy chain (CDR-H3) is at the center of the antigen-binding site and is diverse in terms of sequence and structure. Due to the importance of antibodies in basic science as well as in medical applications, there have been many studies of CDR-H3s of antibodies that possess both light and heavy chains. However, nature of CDR-H3s of single-domain VHH antibodies is less well studied. In this chapter, we describe current knowledge of sequence-structure-function correlations of single-domain VHH antibodies with emphasis on CDR-H3. Based on the 370 crystal structures in the Protein Data Bank, we also attempt structural classification of CDR-H3 in single-domain VHH antibodies and discuss lessons learned from the ever-increasing number of the structures.
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Affiliation(s)
- Daisuke Kuroda
- Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
- Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan.
| | - Kouhei Tsumoto
- Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
- Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan.
- Laboratory of Medical Proteomics, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
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9
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Gaudreault F, Corbeil CR, Purisima EO, Sulea T. Coevolved Canonical Loops Conformations of Single-Domain Antibodies: A Tale of Three Pockets Playing Musical Chairs. Front Immunol 2022; 13:884132. [PMID: 35720356 PMCID: PMC9203998 DOI: 10.3389/fimmu.2022.884132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/05/2022] [Indexed: 11/13/2022] Open
Abstract
Single-domain antibodies (sdAbs) are a promising class of biotherapeutics with unique structural traits within their paratope region. The distribution of canonical conformations explored by their complementarity determining region (CDR) loops differs to some extent from conventional two-chain Fv fragments of monoclonal antibodies (mAbs). In this study, we explored in detail the canonical structures of sdAb CDR-H1 and CDR-H2 loops and compared those with mAbs from the IGHV3 and IGHV1 gene families. We surveyed the antibody structures catalogued in SAbDab and clustered the CDR canonical loops in Cartesian space. While most of the sdAb clusters were sub-populations of previously defined canonical Fv conformations of CDR-H1 and CDR-H2, our stricter clustering approach defined narrower clusters in sequence-space. Meticulous visual inspection of sub-populations allowed a clearer understanding of sequence-structure relationships. The packing densities within structural pockets contacted by CDR-H1 and CDR-H2 canonical conformations were analyzed on the premise that these pockets cannot be left vacant as they would leave exposed supportive hydrophobic residues. The fine resolution of the canonical clusters defined here revealed unique signatures within these pockets, including distinct structural complementarities between CDR-H1 and CDR-H2 canonical clusters, which could not be perceived with the previous coarser clusters. We highlight examples where a single residue change in CDR-H1 sequence is sufficient to induce a dramatic population shift in CDR-H2 conformation. This suggests that preferences in combining CDR-H1 and CDR-H2 emerged naturally during antibody evolution, leading to preferred sets of conserved amino acids at key positions in the framework as well as within the CDR loops. We outline a game of musical chairs that is necessary to maintain the integrity of the antibody structures that arose during evolution. Our study also provides refined CDR-H1 and CDR-H2 structural templates for sdAb homology modeling that could be leveraged for improved antibody design.
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10
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Löhr T, Sormanni P, Vendruscolo M. Conformational Entropy as a Potential Liability of Computationally Designed Antibodies. Biomolecules 2022; 12:718. [PMID: 35625644 PMCID: PMC9138470 DOI: 10.3390/biom12050718] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 05/06/2022] [Accepted: 05/08/2022] [Indexed: 01/28/2023] Open
Abstract
In silico antibody discovery is emerging as a viable alternative to traditional in vivo and in vitro approaches. Many challenges, however, remain open to enabling the properties of designed antibodies to match those produced by the immune system. A major question concerns the structural features of computer-designed complementarity determining regions (CDRs), including the role of conformational entropy in determining the stability and binding affinity of the designed antibodies. To address this problem, we used enhanced-sampling molecular dynamics simulations to compare the free energy landscapes of single-domain antibodies (sdAbs) designed using structure-based (DesAb-HSA-D3) and sequence-based approaches (DesAbO), with that of a nanobody derived from llama immunization (Nb10). Our results indicate that the CDR3 of DesAbO is more conformationally heterogeneous than those of both DesAb-HSA-D3 and Nb10, and the CDR3 of DesAb-HSA-D3 is slightly more dynamic than that of Nb10, which is the original scaffold used for the design of DesAb-HSA-D3. These differences underline the challenges in the rational design of antibodies by revealing the presence of conformational substates likely to have different binding properties and to generate a high entropic cost upon binding.
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Affiliation(s)
| | | | - Michele Vendruscolo
- Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK; (T.L.); (P.S.)
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11
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Parker MI, Meyer JE, Golemis EA, Dunbrack RL. Delineating The RAS Conformational Landscape. Cancer Res 2022; 82:2485-2498. [PMID: 35536216 DOI: 10.1158/0008-5472.can-22-0804] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 11/16/2022]
Abstract
Mutations in RAS isoforms (KRAS, NRAS, and HRAS) are among the most frequent oncogenic alterations in many cancers, making these proteins high priority therapeutic targets. Effectively targeting RAS isoforms requires an exact understanding of their active, inactive, and druggable conformations. However, there is no structural catalog of RAS conformations to guide therapeutic targeting or examining the structural impact of RAS mutations. Here we present an expanded classification of RAS conformations based on analyses of the catalytic switch 1 (SW1) and switch 2 (SW2) loops. From 721 human KRAS, NRAS, and HRAS structures available in the Protein Data Bank (206 RAS-protein co-complexes, 190 inhibitor-bound, and 325 unbound, including 204 WT and 517 mutated structures), we created a broad conformational classification based on the spatial positions of Y32 in SW1 and Y71 in SW2. Clustering all well-modeled SW1 and SW2 loops using a density-based machine learning algorithm defined additional conformational subsets, some previously undescribed. Three SW1 conformations and nine SW2 conformations were identified, each associated with different nucleotide states (GTP-bound, nucleotide-free, and GDP-bound) and specific bound proteins or inhibitor sites. The GTP-bound SW1 conformation could be further subdivided based on the hydrogen bond type made between Y32 and the GTP γ-phosphate. Further analysis clarified the catalytic impact of G12D and G12V mutations and the inhibitor chemistries that bind to each druggable RAS conformation. Overall, this study has expanded our understanding of RAS structural biology, which could facilitate future RAS drug discovery.
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Affiliation(s)
- Mitchell I Parker
- Drexel University College of Medicine, Philadelphia, PA, United States
| | - Joshua E Meyer
- Fox Chase Cancer Center, Philadelphia, PA, United States
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12
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Fernández-Quintero ML, Kroell KB, Bacher LM, Loeffler JR, Quoika PK, Georges G, Bujotzek A, Kettenberger H, Liedl KR. Germline-Dependent Antibody Paratope States and Pairing Specific V H-V L Interface Dynamics. Front Immunol 2021; 12:675655. [PMID: 34447370 PMCID: PMC8382685 DOI: 10.3389/fimmu.2021.675655] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/24/2021] [Indexed: 11/13/2022] Open
Abstract
Antibodies have emerged as one of the fastest growing classes of biotherapeutic proteins. To improve the rational design of antibodies, we investigate the conformational diversity of 16 different germline combinations, which are composed of 4 different kappa light chains paired with 4 different heavy chains. In this study, we systematically show that different heavy and light chain pairings strongly influence the paratope, interdomain interaction patterns and the relative VH-VL interface orientations. We observe changes in conformational diversity and substantial population shifts of the complementarity determining region (CDR) loops, resulting in distinct dominant solution structures and differently favored canonical structures. Additionally, we identify conformational changes in the structural diversity of the CDR-H3 loop upon different heavy and light chain pairings, as well as upon changes in sequence and structure of the neighboring CDR loops, despite having an identical CDR-H3 loop amino acid sequence. These results can also be transferred to all CDR loops and to the relative VH-VL orientation, as certain paratope states favor distinct interface angle distributions. Furthermore, we directly compare the timescales of sidechain rearrangements with the well-described transition kinetics of conformational changes in the backbone of the CDR loops. We show that sidechain flexibilities are strongly affected by distinct heavy and light chain pairings and decipher germline-specific structural features co-determining stability. These findings reveal that all CDR loops are strongly correlated and that distinct heavy and light chain pairings can result in different paratope states in solution, defined by a characteristic combination of CDR loop conformations and VH-VL interface orientations. Thus, these results have broad implications in the field of antibody engineering, as they clearly show the importance of considering paired heavy and light chains to understand the antibody binding site, which is one of the key aspects in the design of therapeutics.
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Affiliation(s)
- Monica L Fernández-Quintero
- Department of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Katharina B Kroell
- Department of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Lisa M Bacher
- Department of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Johannes R Loeffler
- Department of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Patrick K Quoika
- Department of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Guy Georges
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, Germany
| | - Alexander Bujotzek
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, Germany
| | - Hubert Kettenberger
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, Germany
| | - Klaus R Liedl
- Department of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
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13
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Schoeder CT, Schmitz S, Adolf-Bryfogle J, Sevy AM, Finn JA, Sauer MF, Bozhanova NG, Mueller BK, Sangha AK, Bonet J, Sheehan JH, Kuenze G, Marlow B, Smith ST, Woods H, Bender BJ, Martina CE, Del Alamo D, Kodali P, Gulsevin A, Schief WR, Correia BE, Crowe JE, Meiler J, Moretti R. Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design. Biochemistry 2021; 60:825-846. [PMID: 33705117 PMCID: PMC7992133 DOI: 10.1021/acs.biochem.0c00912] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
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Structure-based antibody
and antigen design has advanced greatly
in recent years, due not only to the increasing availability of experimentally
determined structures but also to improved computational methods for
both prediction and design. Constant improvements in performance within
the Rosetta software suite for biomolecular modeling have given rise
to a greater breadth of structure prediction, including docking and
design application cases for antibody and antigen modeling. Here,
we present an overview of current protocols for antibody and antigen
modeling using Rosetta and exemplify those by detailed tutorials originally
developed for a Rosetta workshop at Vanderbilt University. These tutorials
cover antibody structure prediction, docking, and design and antigen
design strategies, including the addition of glycans in Rosetta. We
expect that these materials will allow novice users to apply Rosetta
in their own projects for modeling antibodies and antigens.
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Affiliation(s)
- Clara T Schoeder
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Samuel Schmitz
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Jared Adolf-Bryfogle
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, California 92037, United States.,IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Alexander M Sevy
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee 37232-0301, United States.,Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232-0417, United States
| | - Jessica A Finn
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232-0417, United States.,Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
| | - Marion F Sauer
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee 37232-0301, United States.,Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232-0417, United States
| | - Nina G Bozhanova
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Benjamin K Mueller
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Amandeep K Sangha
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Jaume Bonet
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Jonathan H Sheehan
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Georg Kuenze
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Institute for Drug Discovery, University Leipzig Medical School, 04103 Leipzig, Germany
| | - Brennica Marlow
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee 37232-0301, United States
| | - Shannon T Smith
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee 37232-0301, United States
| | - Hope Woods
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee 37232-0301, United States
| | - Brian J Bender
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Department of Pharmacology, Vanderbilt University, Nashville, Tennessee 37212, United States
| | - Cristina E Martina
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Diego Del Alamo
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee 37232-0301, United States
| | - Pranav Kodali
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Alican Gulsevin
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - William R Schief
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, California 92037, United States.,IAVI Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Bruno E Correia
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - James E Crowe
- Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232-0417, United States.,Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
| | - Jens Meiler
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States.,Institute for Drug Discovery, University Leipzig Medical School, 04103 Leipzig, Germany
| | - Rocco Moretti
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States.,Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
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14
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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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15
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Fernández-Quintero ML, Kroell KB, Hofer F, Riccabona JR, Liedl KR. Mutation of Framework Residue H71 Results in Different Antibody Paratope States in Solution. Front Immunol 2021; 12:630034. [PMID: 33737932 PMCID: PMC7960778 DOI: 10.3389/fimmu.2021.630034] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 01/20/2021] [Indexed: 12/13/2022] Open
Abstract
Characterizing and understanding the antibody binding interface have become a pre-requisite for rational antibody design and engineering. The antigen-binding site is formed by six hypervariable loops, known as the complementarity determining regions (CDRs) and by the relative interdomain orientation (VH-VL). Antibody CDR loops with a certain sequence have been thought to be limited to a single static canonical conformation determining their binding properties. However, it has been shown that antibodies exist as ensembles of multiple paratope states, which are defined by a characteristic combination of CDR loop conformations and interdomain orientations. In this study, we thermodynamically and kinetically characterize the prominent role of residue 71H (Chothia nomenclature), which does not only codetermine the canonical conformation of the CDR-H2 loop but also results in changes in conformational diversity and population shifts of the CDR-H1 and CDR-H3 loop. As all CDR loop movements are correlated, conformational rearrangements of the heavy chain CDR loops also induce conformational changes in the CDR-L1, CDR-L2, and CDR-L3 loop. These overall conformational changes of the CDR loops also influence the interface angle distributions, consequentially leading to different paratope states in solution. Thus, the type of residue of 71H, either an alanine or an arginine, not only influences the CDR-H2 loop ensembles, but co-determines the paratope states in solution. Characterization of the functional consequences of mutations of residue 71H on the paratope states and interface orientations has broad implications in the field of antibody engineering.
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Affiliation(s)
- Monica L Fernández-Quintero
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Katharina B Kroell
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Florian Hofer
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Jakob R Riccabona
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
| | - Klaus R Liedl
- Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria
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16
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Hong ST, Su YC, Wang YJ, Cheng TL, Wang YT. Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study. Biomolecules 2021; 11:334. [PMID: 33672169 PMCID: PMC7926962 DOI: 10.3390/biom11020334] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 02/18/2021] [Accepted: 02/20/2021] [Indexed: 12/17/2022] Open
Abstract
Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira-TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira-TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0-6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.
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Affiliation(s)
- Shih-Ting Hong
- Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan;
| | - Yu-Cheng Su
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsin-Chu 300, Taiwan;
| | - Yu-Jen Wang
- Department of Mechanical and Electromechanical Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan;
| | - Tian-Lu Cheng
- Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan;
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Yeng-Tseng Wang
- Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan;
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan
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