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Meng F, Zhou N, Hu G, Liu R, Zhang Y, Jing M, Hou Q. A comprehensive overview of recent advances in generative models for antibodies. Comput Struct Biotechnol J 2024; 23:2648-2660. [PMID: 39027650 PMCID: PMC11254834 DOI: 10.1016/j.csbj.2024.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 06/15/2024] [Accepted: 06/18/2024] [Indexed: 07/20/2024] Open
Abstract
Therapeutic antibodies are an important class of biopharmaceuticals. With the rapid development of deep learning methods and the increasing amount of antibody data, antibody generative models have made great progress recently. They aim to solve the antibody space searching problems and are widely incorporated into the antibody development process. Therefore, a comprehensive introduction to the development methods in this field is imperative. Here, we collected 34 representative antibody generative models published recently and all generative models can be divided into three categories: sequence-generating models, structure-generating models, and hybrid models, based on their principles and algorithms. We further studied their performance and contributions to antibody sequence prediction, structure optimization, and affinity enhancement. Our manuscript will provide a comprehensive overview of the status of antibody generative models and also offer guidance for selecting different approaches.
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Affiliation(s)
- Fanxu Meng
- College of Chemical Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Na Zhou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250100, China
- National Institute of Health Data Science of China, Shandong University, Jinan 250100, China
| | - Guangchun Hu
- School of Information Science and Engineering, University of Jinan, Jinan 250022, China
| | - Ruotong Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250100, China
- National Institute of Health Data Science of China, Shandong University, Jinan 250100, China
| | - Yuanyuan Zhang
- College of Chemical Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Ming Jing
- Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
- Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan 250000, China
| | - Qingzhen Hou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250100, China
- National Institute of Health Data Science of China, Shandong University, Jinan 250100, China
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Mishra NN, Sharma A, Shalini S, Sharma S, Jain P, Sharma RK, Chander H, Prasad J, Anvikar AR, Chand S. National Control Laboratory Assessment of Quality of Rituximab Biosimilars in India. Monoclon Antib Immunodiagn Immunother 2022; 41:260-274. [DOI: 10.1089/mab.2021.0066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
| | - Anu Sharma
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Swati Shalini
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Sonia Sharma
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Paras Jain
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Ratnesh K. Sharma
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Harish Chander
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - J.P. Prasad
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Anupkumar R. Anvikar
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
| | - Subhash Chand
- Therapeutic Antibody Laboratory, National Institute of Biologicals, Noida, India
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Takada M, Ohba Y, Kamiya S, Kabashima T, Nakashima K. Simple and rapid analysis of tocilizumab using HPLC-fluorescence detection method. LUMINESCENCE 2019; 34:347-352. [PMID: 30809900 DOI: 10.1002/bio.3615] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 01/11/2019] [Accepted: 01/22/2019] [Indexed: 12/30/2022]
Abstract
We developed a novel assay using high-performance liquid chromatography (HPLC) with fluorescence detection for the determination of tocilizumab (TCZ), after it has undergone a facile and rapid pretreatment. TCZ belongs to the same subclass as IgG1 (Immunoglobulin G subclass 1), and we could separate TCZ from IgG1 without antigen-antibody reactions, with the novel detection method. The separation of these antibodies was achieved by pretreatment with an organic solvent containing a base, such as trimethylamine and triethylamine. The effect of these bases on the separation of TCZ is related to the hydrophobicity of the base rather than the electrostatic charge. The results indicated that the surface charge of antibodies changed because of the structural change, even though the difference in the amino acid sequences of the antibodies was very low. Our method is available for the separation of the antibody subclasses, and it would be useful to assay TCZ in blood.
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Affiliation(s)
- Makoto Takada
- Faculty of Pharmaceutical Sciences, Nagasaki International University, Sasebo City, Nagasaki, Japan
| | - Yoshihito Ohba
- Faculty of Pharmaceutical Sciences, Nagasaki International University, Sasebo City, Nagasaki, Japan
| | - Seitaro Kamiya
- Faculty of Pharmaceutical Sciences, Nagasaki International University, Sasebo City, Nagasaki, Japan
| | - Tsutomu Kabashima
- Faculty of Pharmaceutical Sciences, Nagasaki International University, Sasebo City, Nagasaki, Japan
| | - Kenichiro Nakashima
- Faculty of Pharmaceutical Sciences, Nagasaki International University, Sasebo City, Nagasaki, Japan
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Chan BM, Badh A, Berry KA, Grauer SA, King CT. Flow Cytometry-Based Epitope Binning Using Competitive Binding Profiles for the Characterization of Monoclonal Antibodies against Cellular and Soluble Protein Targets. SLAS DISCOVERY 2018; 23:613-623. [DOI: 10.1177/2472555218774334] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
A key step in the therapeutic antibody drug discovery process is early identification of diverse candidate molecules. Information comparing antibody binding epitopes can be used to classify antibodies within a large panel, guiding rational lead molecule selection. We describe a novel epitope binning method utilizing high-throughput flow cytometry (HTFC) that leverages cellular barcoding or spectrally distinct beads to multiplex samples to characterize antibodies raised against cell membrane receptor or soluble protein targets. With no requirement for sample purification or direct labeling, the method is suited for early characterization of antibody candidates. This method generates competitive binding profiles of each antibody against a defined set of known or unknown reference antibodies for binding to epitopes of an antigen. Antibodies with closely related competitive binding profiles indicate similar epitopes and are classified in the same bin. These large, high-throughput, multiplexed experiments can yield epitope bins or clusters for the entire antibody panel, from which a conceptual map of the epitope space for each antibody can be created. Combining this valuable epitope information with other data, such as functional activity, sequence, and selectivity of binding to orthologs and paralogs, enables us to advance the best epitope-diverse candidates for further development.
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Affiliation(s)
| | - Anita Badh
- Amgen Discovery Research, Burnaby, BC, Canada
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Affiliation(s)
- Xiaoying Wang
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan P. R. China, 410083
| | - Feimeng Zhou
- Department of Chemistry and Biochemistry, California State University, Los Angeles, Los Angeles, California 90032, United States
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Abstract
The ability to quantify binding affinity of molecular interactions is an essential component of drug development and life science research. This chapter outlines the practical use of surface plasmon resonance spectroscopy to monitor protein-protein interactions with an emphasis on basic experimental design. A short summary of epitope binning assays is also included.
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