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- Jun Zhao
- Division of Biotechnology Review and Research I, Office of Biotechnology Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA
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- Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, MD 21702, USA
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- Wen-Jin Wu
- Division of Biotechnology Review and Research I, Office of Biotechnology Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA
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- Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, MD 21702, USA
説明
<jats:p>Antibody therapies with high efficiency and low toxicity are becoming one of the major approaches in antibody therapeutics. Based on high-throughput sequencing and increasing experimental structures of antibodies/antibody-antigen complexes, computational approaches can predict antibody/antigen structures, engineering the function of antibodies and design antibody-antigen complexes with improved properties. This review summarizes recent progress in the field of in silico design of antibodies, including antibody structure modeling, antibody-antigen complex prediction, antibody stability evaluation, and allosteric effects in antibodies and functions. We listed the cases in which these methods have helped experimental studies to improve the affinities and physicochemical properties of antibodies. We emphasized how the molecular dynamics unveiled the allosteric effects during antibody-antigen recognition and antibody-effector recognition.</jats:p>
収録刊行物
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- Antibodies
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Antibodies 7 (3), 22-, 2018-06-29
MDPI AG