利用超级计算机对广泛的突变体库进行虚拟筛选，实现抗体催化中心的进化。
Evolution of catalytic centers of antibodies by virtual screening of broad repertoire of mutants using supercomputer.
作者信息
Golovin A V, Smirnov I V, Stepanova A V, Zalevskiy A O, Zlobin A S, Ponomarenko N A, Belogurov A A, Knorre V D, Hurs E N, Chatziefthimiou S D, Wilmanns M, Blackburn G M, Khomutov R M, Gabibov A G
机构信息
Moscow State University, Moscow, 119991, Russia.
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, 117997, Russia.
出版信息
Dokl Biochem Biophys. 2017 Jul;475(1):245-249. doi: 10.1134/S1607672917040019. Epub 2017 Sep 2.
It is proposed to perform quantum mechanical/molecular dynamics calculations of chemical reactions that are planned to be catalyzed by antibodies and then conduct a virtual screening of the library of potential antibody mutants to select an optimal biocatalyst. We tested the effectiveness of this approach by the example of hydrolysis of organophosphorus toxicant paraoxon using kinetic approaches and X-ray analysis of the antibody biocatalyst designed de novo.
建议对计划由抗体催化的化学反应进行量子力学/分子动力学计算，然后对潜在抗体突变体文库进行虚拟筛选，以选择最佳生物催化剂。我们以有机磷毒物对氧磷的水解为例，采用动力学方法和从头设计的抗体生物催化剂的X射线分析，测试了该方法的有效性。
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