Advances in computational structure-based antibody design

被引:35
|
作者
Hummer, Alissa M. [1 ]
Abanades, Brennan [1 ]
Deane, Charlotte M. [1 ]
机构
[1] Univ Oxford, Dept Stat, Oxford Prot Informat Grp, Oxford OX1 3LB, England
基金
英国医学研究理事会; 英国工程与自然科学研究理事会;
关键词
STRUCTURE PREDICTION; PROTEIN;
D O I
10.1016/j.sbi.2022.102379
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Antibodies are currently the most important class of biotherapeutics and are used to treat numerous diseases. Recent advances in computational methods are ushering in a new era of antibody design, driven in part by accurate structure prediction. Previously, structure-based antibody design has been limited to a relatively small number of cases where accurate structures or models of both the target antigen and antibody were available. As we move towards a time where it is possible to accurately model most antibodies and antigens, and to reliably predict their binding site, there is vast potential for true computational antibody design. In this review, we describe the latest methods that promise to launch a paradigm shift towards entirely in silico structure-based antibody design.
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页数:7
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