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Increasing stability of antibody via antibody engineering: Stability engineering on an anti‐hVEGF
Author(s) -
Wang Shuang,
Liu Ming,
Zeng Dadi,
Qiu Weiyi,
Ma Pingping,
Yu Yunzhou,
Chang Hongyan,
Sun Zhiwei
Publication year - 2014
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.24626
Subject(s) - stability (learning theory) , antibody , protein engineering , computer science , protocol (science) , computational biology , chemistry , biology , immunology , biochemistry , medicine , alternative medicine , pathology , machine learning , enzyme
Antibody stability is very important for expression, activity, specificity, and storage. This knowledge of antibody structure has made it possible for a computer‐aided molecule design to be used to optimize and increase antibody stability. Many computational methods have been built based on knowledge or structure, however, a good integrated engineering system has yet to be developed that combines these methods. In the current study, we designed an integrated computer‐aided engineering protocol, which included several successful methods. Mutants were designed considering factors that affected stability and multiwall filter screening was used to improve the design accuracy. Using this protocol, the thermo‐stability of an anti‐hVEGF antibody was significantly improved. Nearly 40% of the single‐point mutants proved to be more stable than the parent antibody and most of the mutations could be stacked effectively. The T 50 also improved about 7°C by combinational mutation of seven sites in the light chain and three sites in the heavy chain. Data indicate that the protocol is an effective method for optimization of antibody structure, especially for improving thermo‐stability. This protocol could also be used to enhance the stability of other antibodies. Proteins 2014; 82:2620–2630. © 2014 Wiley Periodicals, Inc.