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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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2
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Niu J, Wang Q, Zhao W, Meng B, Xu Y, Zhang X, Feng Y, Qi Q, Hao Y, Zhang X, Liu Y, Xiang J, Shao Y, Yang B. Structures and immune recognition of Env trimers from two Asia prevalent HIV-1 CRFs. Nat Commun 2023; 14:4676. [PMID: 37542068 PMCID: PMC10403546 DOI: 10.1038/s41467-023-40321-x] [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: 11/11/2022] [Accepted: 07/21/2023] [Indexed: 08/06/2023] Open
Abstract
Structure-guided immunofocusing HIV-1 vaccine design entails a comprehensive understanding of Envs from diverse HIV-1 subtypes, including circulating recombinant forms (CRFs). Here, we present the cryo-EM structures of Envs from two Asia prevalent CRFs (CRF01_AE and CRF07_BC) at 3.0 and 3.5 Å. We compare the structures and glycosylation patterns of Envs from different subtypes and perform cross-clade statistical analyses to reveal the unique features of CRF01_AE V1 region, which are associated with the resistance to certain bNAbs. We also solve a 4.1 Å cryo-EM structure of CRF01_AE Env in complex with F6, the first bNAb from CRF01_AE-infected individuals. F6 recognizes a gp120-gp41 spanning epitope to allosterically destabilize the Env trimer apex and weaken inter-protomer packing, which in turn hinders the receptor binding and induces Env trimer disassembly, demonstrating a dual mechanism of neutralization. These findings broaden our understanding of CRF Envs and shed lights on immunofocusing HIV-1 vaccine design.
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Affiliation(s)
- Jun Niu
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qi Wang
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Wenwen Zhao
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Bing Meng
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Youwei Xu
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Xianfang Zhang
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, 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, Beijing, 102206, China
| | - Qilian Qi
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - 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, Beijing, 102206, China
| | - Xuan Zhang
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Ying Liu
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Jiangchao Xiang
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - 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, Beijing, 102206, China.
- Changping Laboratory, Beijing, 102206, China.
| | - Bei Yang
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China.
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3
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Hermet P, Delache B, Herate C, Wolf E, Kivi G, Juronen E, Mumm K, Žusinaite E, Kainov D, Sankovski E, Virumäe K, Planken A, Merits A, Besaw JE, Yee AW, Morizumi T, Kim K, Kuo A, Berriche A, Dereuddre-Bosquet N, Sconosciuti Q, Naninck T, Relouzat F, Cavarelli M, Ustav M, Wilson D, Ernst OP, Männik A, LeGrand R, Ustav M. Broadly neutralizing humanized SARS-CoV-2 antibody binds to a conserved epitope on Spike and provides antiviral protection through inhalation-based delivery in non-human primates. PLoS Pathog 2023; 19:e1011532. [PMID: 37531329 PMCID: PMC10395824 DOI: 10.1371/journal.ppat.1011532] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
The COVID-19 pandemic represents a global challenge that has impacted and is expected to continue to impact the lives and health of people across the world for the foreseeable future. The rollout of vaccines has provided highly anticipated relief, but effective therapeutics are required to further reduce the risk and severity of infections. Monoclonal antibodies have been shown to be effective as therapeutics for SARS-CoV-2, but as new variants of concern (VoC) continue to emerge, their utility and use have waned due to limited or no efficacy against these variants. Furthermore, cumbersome systemic administration limits easy and broad access to such drugs. As well, concentrations of systemically administered antibodies in the mucosal epithelium, a primary site of initial infection, are dependent on neonatal Fc receptor mediated transport and require high drug concentrations. To reduce the viral load more effectively in the lung, we developed an inhalable formulation of a SARS-CoV-2 neutralizing antibody binding to a conserved epitope on the Spike protein, ensuring pan-neutralizing properties. Administration of this antibody via a vibrating mesh nebulization device retained antibody integrity and resulted in effective distribution of the antibody in the upper and lower respiratory tract of non-human primates (NHP). In comparison with intravenous administration, significantly higher antibody concentrations can be obtained in the lung, resulting in highly effective reduction in viral load post SARS-CoV-2 challenge. This approach may reduce the barriers of access and uptake of antibody therapeutics in real-world clinical settings and provide a more effective blueprint for targeting existing and potentially emerging respiratory tract viruses.
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Affiliation(s)
| | - Benoît Delache
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Cecile Herate
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | | | - Gaily Kivi
- Icosagen Cell Factory OÜ; Tartu, Estonia
| | | | - Karl Mumm
- Icosagen Cell Factory OÜ; Tartu, Estonia
| | | | | | | | | | | | | | - Jessica E Besaw
- Department of Biochemistry, University of Toronto; Toronto, Canada
| | - Ai Woon Yee
- Department of Biochemistry, University of Toronto; Toronto, Canada
| | | | - Kyumhyuk Kim
- Department of Biochemistry, University of Toronto; Toronto, Canada
| | - Anling Kuo
- Department of Biochemistry, University of Toronto; Toronto, Canada
| | - Asma Berriche
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Nathalie Dereuddre-Bosquet
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Quentin Sconosciuti
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Thibaut Naninck
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Francis Relouzat
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Mariangela Cavarelli
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Mart Ustav
- Icosagen Cell Factory OÜ; Tartu, Estonia
| | | | - Oliver P Ernst
- Department of Biochemistry, University of Toronto; Toronto, Canada
- Department of Molecular Genetics, University of Toronto; Toronto, Canada
| | | | - Roger LeGrand
- Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial Diseases (IMVA-HB/IDMIT); Fontenay-aux-Roses, France
| | - Mart Ustav
- Icosagen Cell Factory OÜ; Tartu, Estonia
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4
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Jain T, Boland T, Vásquez M. Identifying developability risks for clinical progression of antibodies using high-throughput in vitro and in silico approaches. MAbs 2023; 15:2200540. [PMID: 37072706 PMCID: PMC10114995 DOI: 10.1080/19420862.2023.2200540] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 04/20/2023] Open
Abstract
With the growing significance of antibodies as a therapeutic class, identifying developability risks early during development is of paramount importance. Several high-throughput in vitro assays and in silico approaches have been proposed to de-risk antibodies during early stages of the discovery process. In this review, we have compiled and collectively analyzed published experimental assessments and computational metrics for clinical antibodies. We show that flags assigned based on in vitro measurements of polyspecificity and hydrophobicity are more predictive of clinical progression than their in silico counterparts. Additionally, we assessed the performance of published models for developability predictions on molecules not used during model training. We find that generalization to data outside of those used for training remains a challenge for models. Finally, we highlight the challenges of reproducibility in computed metrics arising from differences in homology modeling, in vitro assessments relying on complex reagents, as well as curation of experimental data often used to assess the utility of high-throughput approaches. We end with a recommendation to enable assay reproducibility by inclusion of controls with disclosed sequences, as well as sharing of structural models to enable the critical assessment and improvement of in silico predictions.
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Affiliation(s)
| | - Todd Boland
- Computational Biology, Adimab LLC, Lebanon, NH, USA
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5
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Waibl F, Fernández-Quintero ML, Wedl FS, Kettenberger H, Georges G, Liedl KR. Comparison of hydrophobicity scales for predicting biophysical properties of antibodies. Front Mol Biosci 2022; 9:960194. [PMID: 36120542 PMCID: PMC9475378 DOI: 10.3389/fmolb.2022.960194] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
While antibody-based therapeutics have grown to be one of the major classes of novel medicines, some antibody development candidates face significant challenges regarding expression levels, solubility, as well as stability and aggregation, under physiological and storage conditions. A major determinant of those properties is surface hydrophobicity, which promotes unspecific interactions and has repeatedly proven problematic in the development of novel antibody-based drugs. Multiple computational methods have been devised for in-silico prediction of antibody hydrophobicity, often using hydrophobicity scales to assign values to each amino acid. Those approaches are usually validated by their ability to rank potential therapeutic antibodies in terms of their experimental hydrophobicity. However, there is significant diversity both in the hydrophobicity scales and in the experimental methods, and consequently in the performance of in-silico methods to predict experimental results. In this work, we investigate hydrophobicity of monoclonal antibodies using hydrophobicity scales. We implement several scoring schemes based on the solvent-accessibility and the assigned hydrophobicity values, and compare the different scores and scales based on their ability to predict retention times from hydrophobic interaction chromatography. We provide an overview of the strengths and weaknesses of several commonly employed hydrophobicity scales, thereby improving the understanding of hydrophobicity in antibody development. Furthermore, we test several datasets, both publicly available and proprietary, and find that the diversity of the dataset affects the performance of hydrophobicity scores. We expect that this work will provide valuable guidelines for the optimization of biophysical properties in future drug discovery campaigns.
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Affiliation(s)
- Franz Waibl
- Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | | | - Florian S. Wedl
- Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | - Hubert Kettenberger
- Large Molecule Research, Roche Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany
| | - Guy Georges
- Large Molecule Research, Roche Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany
| | - Klaus R. Liedl
- Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
- *Correspondence: Klaus R. Liedl,
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6
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Van De Vyver AJ, Walz AC, Heins MS, Abdolzade-Bavil A, Kraft TE, Waldhauer I, Otteneder MB. Investigating brain uptake of a non-targeting monoclonal antibody after intravenous and intracerebroventricular administration. Front Pharmacol 2022; 13:958543. [PMID: 36105215 PMCID: PMC9465605 DOI: 10.3389/fphar.2022.958543] [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: 05/31/2022] [Accepted: 08/02/2022] [Indexed: 11/13/2022] Open
Abstract
Monoclonal antibodies play an important role in the treatment of various diseases. However, the development of these drugs against neurological disorders where the drug target is located in the brain is challenging and requires a good understanding of the local drug concentration in the brain. In this original research, we investigated the systemic and local pharmacokinetics in the brain of healthy rats after either intravenous (IV) or intracerebroventricular (ICV) administration of EGFRvIII-T-Cell bispecific (TCB), a bispecific monoclonal antibody. We established an experimental protocol that allows serial sampling in serum, cerebrospinal fluid (CSF) and interstitial fluid (ISF) of the prefrontal cortex in freely moving rats. For detection of drug concentration in ISF, a push-pull microdialysis technique with large pore membranes was applied. Brain uptake into CSF and ISF was characterized and quantified with a reduced brain physiologically-based pharmacokinetic model. The model allowed us to interpret the pharmacokinetic processes of brain uptake after different routes of administration. The proposed model capturing the pharmacokinetics in serum, CSF and ISF of the prefrontal cortex suggests a barrier function between the CSF and ISF that impedes free antibody transfer. This finding suggests that ICV administration may not be better suited to reach higher local drug exposure as compared to IV administration. The model enabled us to quantify the relative contribution of the blood-brain barrier (BBB) and Blood-CSF-Barrier to the uptake into the interstitial fluid of the brain. In addition, we compared the brain uptake of three monoclonal antibodies after IV dosing. In summary, the presented approach can be applied to profile compounds based on their relative uptake in the brain and provides quantitative insights into which pathways are contributing to the net exposure in the brain.
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Affiliation(s)
- Arthur J. Van De Vyver
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel, Switzerland
| | - Antje-Christine Walz
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel, Switzerland
- *Correspondence: Antje-Christine Walz,
| | | | - Afsaneh Abdolzade-Bavil
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Munich, Penzberg, Germany
| | - Thomas E. Kraft
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Munich, Penzberg, Germany
| | - Inja Waldhauer
- Roche Pharma Research and Early Development (pRED), Roche Innovation Center Zurich (RICZ), Schlieren, Switzerland
| | - Michael B. Otteneder
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel, Switzerland
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7
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V HH Structural Modelling Approaches: A Critical Review. Int J Mol Sci 2022; 23:ijms23073721. [PMID: 35409081 PMCID: PMC8998791 DOI: 10.3390/ijms23073721] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/23/2022] [Accepted: 03/23/2022] [Indexed: 12/20/2022] Open
Abstract
VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.
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8
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Stravinskiene D, Sliziene A, Baranauskiene L, Petrikaite V, Zvirbliene A. Inhibitory Monoclonal Antibodies and Their Recombinant Derivatives Targeting Surface-Exposed Carbonic Anhydrase XII on Cancer Cells. Int J Mol Sci 2020; 21:ijms21249411. [PMID: 33321910 PMCID: PMC7763246 DOI: 10.3390/ijms21249411] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 12/08/2020] [Indexed: 01/17/2023] Open
Abstract
Monoclonal and recombinant antibodies are widely used for the diagnostics and therapy of cancer. They are generated to interact with cell surface proteins which are usually involved in the development and progression of cancer. Carbonic anhydrase XII (CA XII) contributes to the survival of tumors under hypoxic conditions thus is considered a candidate target for antibody-based therapy. In this study, we have generated a novel collection of monoclonal antibodies (MAbs) against the recombinant extracellular domain of CA XII produced in HEK-293 cells. Eighteen out of 24 MAbs were reactive with cellular CA XII on the surface of live kidney and lung cancer cells as determined by flow cytometry. One MAb 14D6 also inhibited the enzymatic activity of recombinant CA XII as measured by the stopped-flow assay. MAb 14D6 showed the migrastatic effect on human lung carcinoma A549 and renal carcinoma A498 cell lines in a ‘wound healing’ assay. It did not reduce the growth of multicellular lung and renal cancer spheroids but reduced the cell viability by the ATP Bioluminescence assay. Epitope mapping revealed the surface-exposed amino acid sequence (35-FGPDGENS-42) close to the catalytic center of CA XII recognized by the MAb 14D6. The variable regions of the heavy and light chains of MAb 14D6 were sequenced and their complementarity-determining regions were defined. The obtained variable sequences were used to generate recombinant antibodies in two formats: single-chain fragment variable (scFv) expressed in E. coli and scFv fused to human IgG1 Fc fragment (scFv-Fc) expressed in Chinese Hamster Ovary (CHO) cells. Both recombinant antibodies maintained the same specificity for CA XII as the parental MAb 14D6. The novel antibodies may represent promising tools for CA XII-related cancer research and immunotherapy.
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Affiliation(s)
- Dovile Stravinskiene
- Department of Immunology and Cell Biology, Institute of Biotechnology, Life Sciences Center, Vilnius University, Sauletekio al. 7, LT-10257 Vilnius, Lithuania; (A.S.); (A.Z.)
- Correspondence:
| | - Aiste Sliziene
- Department of Immunology and Cell Biology, Institute of Biotechnology, Life Sciences Center, Vilnius University, Sauletekio al. 7, LT-10257 Vilnius, Lithuania; (A.S.); (A.Z.)
| | - Lina Baranauskiene
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Sauletekio al. 7, LT-10257 Vilnius, Lithuania; (L.B.); (V.P.)
| | - Vilma Petrikaite
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Sauletekio al. 7, LT-10257 Vilnius, Lithuania; (L.B.); (V.P.)
- Laboratory of Drug Targets Histopathology, Institute of Cardiology, Lithuanian University of Health Sciences, Sukileliu pr. 13, LT-50162 Kaunas, Lithuania
| | - Aurelija Zvirbliene
- Department of Immunology and Cell Biology, Institute of Biotechnology, Life Sciences Center, Vilnius University, Sauletekio al. 7, LT-10257 Vilnius, Lithuania; (A.S.); (A.Z.)
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9
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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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10
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Marks C, Deane CM. How repertoire data are changing antibody science. J Biol Chem 2020; 295:9823-9837. [PMID: 32409582 DOI: 10.1074/jbc.rev120.010181] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 04/28/2020] [Indexed: 12/13/2022] Open
Abstract
Antibodies are vital proteins of the immune system that recognize potentially harmful molecules and initiate their removal. Mammals can efficiently create vast numbers of antibodies with different sequences capable of binding to any antigen with high affinity and specificity. Because they can be developed to bind to many disease agents, antibodies can be used as therapeutics. In an organism, after antigen exposure, antibodies specific to that antigen are enriched through clonal selection, expansion, and somatic hypermutation. The antibodies present in an organism therefore report on its immune status, describe its innate ability to deal with harmful substances, and reveal how it has previously responded. Next-generation sequencing technologies are being increasingly used to query the antibody, or B-cell receptor (BCR), sequence repertoire, and the amount of BCR data in public repositories is growing. The Observed Antibody Space database, for example, currently contains over a billion sequences from 68 different studies. Repertoires are available that represent both the naive state (i.e. antigen-inexperienced) and that after immunization. This wealth of data has created opportunities to learn more about our immune system. In this review, we discuss the many ways in which BCR repertoire data have been or could be exploited. We highlight its utility for providing insights into how the naive immune repertoire is generated and how it responds to antigens. We also consider how structural information can be used to enhance these data and may lead to more accurate depictions of the sequence space and to applications in the discovery of new therapeutics.
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Affiliation(s)
- Claire Marks
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford, United Kingdom
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11
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Schrade A, Bujotzek A, Spick C, Wagner M, Goerl J, Wezler X, Georges G, Kontermann RE, Brinkmann U. Back-to-Germline (B2G) Procedure for Antibody Devolution. Antibodies (Basel) 2019; 8:antib8030045. [PMID: 31544851 PMCID: PMC6784197 DOI: 10.3390/antib8030045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 08/13/2019] [Accepted: 08/16/2019] [Indexed: 11/16/2022] Open
Abstract
Bispecific antibodies (bsAbs) with avidity-enhanced specificity can be used to address target cells with increased specificity, ideally binding efficiently to cells that express two cognate antigens, yet not to cells that express only one of those. Building blocks required to generate such bsAbs are binders that recognize the two antigens with high specificity yet with various (including very low monovalent) affinities. The herein described ‘back-to-germline’ (B2G) procedure defines such derivatives. It converts parent antibodies with high specificity to derivatives that retain specificity but modulate affinity. The approach defines mutations to be introduced into antibody complementarity-determining regions (CDRs) regions without requiring structures of antibody-antigen complexes. Instead, it reverses the B-cell maturation process that increases affinities, with preference on CDR residues with high antigen contact probability. Placing germline residues at those positions generates VH and VL domains and Fv-combinations thereof that retain specificities but are ‘de-matured’ to different degrees. De-maturation influences on-rates and off-rates, and can produce entities with extremely low affinity for which binding can only be detected in bivalent formats. A comparison with alanine replacement in CDRs (so far, the most frequently applied technology) indicates that B2G may be more reliable/predictable without introduction of stickiness or poly-reactivity. The applicability for generating sets of affinity-modulated monospecific variants is exemplarily shown for antibodies that bind CD138, Her2/neu, and EGFR.
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Affiliation(s)
- Anja Schrade
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Alexander Bujotzek
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Christian Spick
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Martina Wagner
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Johannes Goerl
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Xenia Wezler
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Guy Georges
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany
| | - Roland E Kontermann
- Institute of Cell Biology & Immunology, Stuttgart University, 70569 Stuttgart, Germany
| | - Ulrich Brinkmann
- Roche Pharma Research and Early Development (pRED), Large Molecule Research (LMR), Roche Innovation Center Munich, 82377 Penzberg, Germany.
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12
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Leem J, Deane CM. High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2019; 1851:367-380. [PMID: 30298409 DOI: 10.1007/978-1-4939-8736-8_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Antibodies are proteins of the adaptive immune system; they can be designed to bind almost any molecule, and are increasingly being used as biotherapeutics. Experimental antibody design is an expensive and time-consuming process, and computational antibody design methods can now be used to help develop new therapeutics and diagnostics. Within the design pipeline, accurate antibody structure modeling is essential, as it provides the basis for antibody-antigen docking, binding affinity prediction, and estimating thermal stability. Ideally, models should be rapidly generated, allowing the exploration of the breadth of antibody space. This allows methods to replicate the natural processes of antibody diversification (e.g., V(D)J recombination and somatic hypermutation), and cope with large volumes of data that are typical of next-generation sequencing datasets. Here we describe ABodyBuilder and PEARS, algorithms that build and mutate antibody model structures. These methods take ~30 s to generate a model antibody structure.
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Affiliation(s)
- Jinwoo Leem
- Department of Statistics, University of Oxford, Oxford, UK
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13
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Weber F, Bohrmann B, Niewoehner J, Fischer JA, Rueger P, Tiefenthaler G, Moelleken J, Bujotzek A, Brady K, Singer T, Ebeling M, Iglesias A, Freskgård PO. Brain Shuttle Antibody for Alzheimer’s Disease with Attenuated Peripheral Effector Function due to an Inverted Binding Mode. Cell Rep 2018; 22:149-162. [DOI: 10.1016/j.celrep.2017.12.019] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 11/01/2017] [Accepted: 12/04/2017] [Indexed: 01/03/2023] Open
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14
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Jain T, Boland T, Lilov A, Burnina I, Brown M, Xu Y, Vásquez M. Prediction of delayed retention of antibodies in hydrophobic interaction chromatography from sequence using machine learning. Bioinformatics 2017; 33:3758-3766. [DOI: 10.1093/bioinformatics/btx519] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 08/11/2017] [Indexed: 12/16/2022] Open
Affiliation(s)
- Tushar Jain
- Computational Biology, Adimab, Palo Alto, CA, USA
| | - Todd Boland
- Computational Biology, Adimab, Palo Alto, CA, USA
| | | | | | | | - Yingda Xu
- Protein Analytics, Adimab, Lebanon, NH, USA
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Xue L, Yu Q, Griss R, Schena A, Johnsson K. Bioluminescent Antibodies for Point-of-Care Diagnostics. Angew Chem Int Ed Engl 2017; 56:7112-7116. [PMID: 28510347 PMCID: PMC5488172 DOI: 10.1002/anie.201702403] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Revised: 04/11/2017] [Indexed: 01/14/2023]
Abstract
We introduce a general method to transform antibodies into ratiometric, bioluminescent sensor proteins for the no‐wash quantification of analytes. Our approach is based on the genetic fusion of antibody fragments to NanoLuc luciferase and SNAP‐tag, the latter being labeled with a synthetic fluorescent competitor of the antigen. Binding of the antigen, here synthetic drugs, by the sensor displaces the tethered fluorescent competitor from the antibody and disrupts bioluminescent resonance energy transfer (BRET) between the luciferase and fluorophore. The semisynthetic sensors display a tunable response range (submicromolar to submillimolar) and large dynamic range (ΔRmax>500 %), and they permit the quantification of analytes through spotting of the samples onto paper followed by analysis with a digital camera.
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Affiliation(s)
- Lin Xue
- Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Chemical Sciences and Engineering (ISIC), NCCR in Chemical Biology, 1015, Lausanne, Switzerland
| | - Qiuliyang Yu
- Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Chemical Sciences and Engineering (ISIC), NCCR in Chemical Biology, 1015, Lausanne, Switzerland
| | - Rudolf Griss
- Lucentix SA, EPFL Innovation Park, Bâtiment C, 1015, Lausanne, Switzerland
| | - Alberto Schena
- Lucentix SA, EPFL Innovation Park, Bâtiment C, 1015, Lausanne, Switzerland
| | - Kai Johnsson
- Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Chemical Sciences and Engineering (ISIC), NCCR in Chemical Biology, 1015, Lausanne, Switzerland.,Max-Planck-Institute for Medical Research, Department of Chemical Biology, 69120, Heidelberg, Germany
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16
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Xue L, Yu Q, Griss R, Schena A, Johnsson K. Bioluminescent Antibodies for Point-of-Care Diagnostics. Angew Chem Int Ed Engl 2017. [DOI: 10.1002/ange.201702403] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Lin Xue
- Ecole Polytechnique Fédérale de Lausanne (EPFL); Institute of Chemical Sciences and Engineering (ISIC); NCCR in Chemical Biology; 1015 Lausanne Switzerland
| | - Qiuliyang Yu
- Ecole Polytechnique Fédérale de Lausanne (EPFL); Institute of Chemical Sciences and Engineering (ISIC); NCCR in Chemical Biology; 1015 Lausanne Switzerland
| | - Rudolf Griss
- Lucentix SA; EPFL Innovation Park; Bâtiment C; 1015 Lausanne Switzerland
| | - Alberto Schena
- Lucentix SA; EPFL Innovation Park; Bâtiment C; 1015 Lausanne Switzerland
| | - Kai Johnsson
- Ecole Polytechnique Fédérale de Lausanne (EPFL); Institute of Chemical Sciences and Engineering (ISIC); NCCR in Chemical Biology; 1015 Lausanne Switzerland
- Max-Planck-Institute for Medical Research; Department of Chemical Biology; 69120 Heidelberg Germany
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17
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Hoffmann T, Marion A, Antes I. DynaDom: structure-based prediction of T cell receptor inter-domain and T cell receptor-peptide-MHC (class I) association angles. BMC STRUCTURAL BIOLOGY 2017; 17:2. [PMID: 28148269 PMCID: PMC5289058 DOI: 10.1186/s12900-016-0071-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Accepted: 12/29/2016] [Indexed: 11/22/2022]
Abstract
Background T cell receptor (TCR) molecules are involved in the adaptive immune response as they distinguish between self- and foreign-peptides, presented in major histocompatibility complex molecules (pMHC). Former studies showed that the association angles of the TCR variable domains (Vα/Vβ) can differ significantly and change upon binding to the pMHC complex. These changes can be described as a rotation of the domains around a general Center of Rotation, characterized by the interaction of two highly conserved glutamine residues. Methods We developed a computational method, DynaDom, for the prediction of TCR Vα/Vβ inter-domain and TCR/pMHC orientations in TCRpMHC complexes, which allows predicting the orientation of multiple protein-domains. In addition, we implemented a new approach to predict the correct orientation of the carboxamide endgroups in glutamine and asparagine residues, which can also be used as an external, independent tool. Results The approach was evaluated for the remodeling of 75 and 53 experimental structures of TCR and TCRpMHC (class I) complexes, respectively. We show that the DynaDom method predicts the correct orientation of the TCR Vα/Vβ angles in 96 and 89% of the cases, for the poses with the best RMSD and best interaction energy, respectively. For the concurrent prediction of the TCR Vα/Vβ and pMHC orientations, the respective rates reached 74 and 72%. Through an exhaustive analysis, we could show that the pMHC placement can be further improved by a straightforward, yet very time intensive extension of the current approach. Conclusions The results obtained in the present remodeling study prove the suitability of our approach for interdomain-angle optimization. In addition, the high prediction rate obtained specifically for the energetically highest ranked poses further demonstrates that our method is a powerful candidate for blind prediction. Therefore it should be well suited as part of any accurate atomistic modeling pipeline for TCRpMHC complexes and potentially other large molecular assemblies. Electronic supplementary material The online version of this article (doi:10.1186/s12900-016-0071-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Thomas Hoffmann
- Department of Biosciences and Center for Integrated Protein Science Munich, Technische Universität München, Emil-Erlenmeyer-Forum 8, 85354, Freising, Germany
| | - Antoine Marion
- Department of Biosciences and Center for Integrated Protein Science Munich, Technische Universität München, Emil-Erlenmeyer-Forum 8, 85354, Freising, Germany
| | - Iris Antes
- Department of Biosciences and Center for Integrated Protein Science Munich, Technische Universität München, Emil-Erlenmeyer-Forum 8, 85354, Freising, Germany.
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Bauss F, Lechmann M, Krippendorff BF, Staack R, Herting F, Festag M, Imhof-Jung S, Hesse F, Pompiati M, Kollmorgen G, da Silva Mateus Seidl R, Bossenmaier B, Lau W, Schantz C, Stracke JO, Brinkmann U, Onda M, Pastan I, Bosslet K, Niederfellner G. Characterization of a re-engineered, mesothelin-targeted Pseudomonas exotoxin fusion protein for lung cancer therapy. Mol Oncol 2016; 10:1317-29. [PMID: 27507537 PMCID: PMC5423209 DOI: 10.1016/j.molonc.2016.07.003] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Revised: 06/27/2016] [Accepted: 07/06/2016] [Indexed: 10/21/2022] Open
Abstract
Mesothelin overexpression in lung adenocarcinomas correlates with the presence of activating KRAS mutations and poor prognosis. Hence SS1P, a mesothelin-targeted immunotoxin, could offer valuable treatment options for these patients, but its use in solid tumor therapy is hampered by high immunogenicity and non-specific toxicity. To overcome both obstacles we developed RG7787, a de-immunized cytotoxic fusion protein comprising a humanized SS1 Fab fragment and a truncated, B-cell epitope silenced, 24 kD fragment of Pseudomonas exotoxin A (PE24). Reactivity of RG7787 with sera from immunotoxin-treated patients was >1000 fold reduced. In vitro RG7787 inhibited cell viability of lung cancer cell lines with picomolar potency. The pharmacokinetic properties of RG7787 in rodents were comparable to SS1P, yet it was tolerated up to 10 fold better without causing severe vascular leak syndrome or hepatotoxicity. A pharmacokinetic/pharmacodynamic model developed based on NCI-H596 xenograft studies showed that for RG7787 and SS1P, their in vitro and in vivo potencies closely correlate. At optimal doses of 2-3 mg/kg RG7787 is more efficacious than SS1P. Even large, well established tumors (600 mm(3)) underwent remission during three treatment cycles with RG7787. Also in two patient-derived lung cancer xenograft models, Lu7336 and Lu7187, RG7787 showed anti-tumor efficacy. In monotherapy two treatment cycles were moderately efficacious in the Lu7336 model but showed good anti-tumor activity in the KRAS mutant Lu7187 model (26% and 80% tumor growth inhibition, respectively). Combination of RG7787 with standard chemotherapies further enhanced efficacy in both models achieving near complete eradication of Lu7187 tumors.
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Affiliation(s)
- Frieder Bauss
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Martin Lechmann
- Roche Pharma Research & Early Development (pRED), Pharmaceutical Sciences, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Ben-Fillippo Krippendorff
- Roche pRED Innovation Center Basel, Pharmaceutical Sciences, F. Hoffmann-La Roche AG, Grenzacherstrasse 124, CH-4070 Basel, Switzerland
| | - Roland Staack
- Roche Pharma Research & Early Development (pRED), Pharmaceutical Sciences, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Frank Herting
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Matthias Festag
- Roche pRED Innovation Center Basel, Pharmaceutical Sciences, F. Hoffmann-La Roche AG, Grenzacherstrasse 124, CH-4070 Basel, Switzerland
| | - Sabine Imhof-Jung
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Friederike Hesse
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Marc Pompiati
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Gwendlyn Kollmorgen
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Rita da Silva Mateus Seidl
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Birgit Bossenmaier
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Wilma Lau
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Christian Schantz
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Jan O Stracke
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany; Pharmaceutical Development & Supplies, Pharma Technical Development Biologics Europe, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Ulrich Brinkmann
- Roche Pharma Research & Early Development (pRED), Large Molecule Research, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Masanori Onda
- Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Ira Pastan
- Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Klaus Bosslet
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany
| | - Gerhard Niederfellner
- Roche Pharma Research & Early Development (pRED), Discovery Oncology, Innovation Center Munich, Roche Diagnostics GmbH Penzberg, Nonnenwald 2, D-82377 Penzberg, Germany.
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Leem J, Dunbar J, Georges G, Shi J, Deane CM. ABodyBuilder: Automated antibody structure prediction with data-driven accuracy estimation. MAbs 2016; 8:1259-1268. [PMID: 27392298 PMCID: PMC5058620 DOI: 10.1080/19420862.2016.1205773] [Citation(s) in RCA: 153] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
Computational modeling of antibody structures plays a critical role in therapeutic antibody design. Several antibody modeling pipelines exist, but no freely available methods currently model nanobodies, provide estimates of expected model accuracy, or highlight potential issues with the antibody's experimental development. Here, we describe our automated antibody modeling pipeline, ABodyBuilder, designed to overcome these issues. The algorithm itself follows the standard 4 steps of template selection, orientation prediction, complementarity-determining region (CDR) loop modeling, and side chain prediction. ABodyBuilder then annotates the 'confidence' of the model as a probability that a component of the antibody (e.g., CDRL3 loop) will be modeled within a root-mean square deviation threshold. It also flags structural motifs on the model that are known to cause issues during in vitro development. ABodyBuilder was tested on 4 separate datasets, including the 11 antibodies from the Antibody Modeling Assessment-II competition. ABodyBuilder builds models that are of similar quality to other methodologies, with sub-Angstrom predictions for the 'canonical' CDR loops. Its ability to model nanobodies, and rapidly generate models (∼30 seconds per model) widens its potential usage. ABodyBuilder can also help users in decision-making for the development of novel antibodies because it provides model confidence and potential sequence liabilities. ABodyBuilder is freely available at http://opig.stats.ox.ac.uk/webapps/abodybuilder .
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Affiliation(s)
- Jinwoo Leem
- a Department of Statistics , University of Oxford , Oxford , UK
| | - James Dunbar
- a Department of Statistics , University of Oxford , Oxford , UK.,b Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich , Penzberg , Germany
| | - Guy Georges
- b Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich , Penzberg , Germany
| | - Jiye Shi
- c Informatics Department , UCB Pharma , Slough , UK
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