Robotic QM/MM-driven maturation of antibody combining sites

• DOI: 10.1126/sciadv.1501695
• Publication Date: 2016-10-20T03:44:19Z
• Authors: Ivan V. Smirnov; Andrey V. Golovin; Spyros D. Chatzie...; Anastasiya V. Ste...; Yingjie Peng; Olga I. Zolotareva; Alexey A. Belogurov; Inna N. Kurkova; Natalie A. Ponoma...; Matthias Wilmanns; G. Michael Blackburn; Alexander G. Gabibov; Richard A. Lerner
• Keywords: QM/MM

In vitro selection of antibodies from large repertoires immunoglobulin (Ig) combining sites using combinatorial libraries is a powerful tool, with great potential for generating in vivo scavengers toxins. However, addition maturation function necessary to enable these selected more closely mimic the full mammalian immune response. We approached this goal quantum mechanics/molecular mechanics (QM/MM) calculations achieve silico. preselected A17, an Ig template, naïve library its ability disarm toxic pesticide related organophosphorus nerve agents. Virtual screening 167,538 robotically generated mutants identified optimum single point mutation, which experimentally boosted wild-type scavenger performance by 170-fold. validated QM/MM predictions via kinetic analysis and crystal structures mutant apo-A17 covalently modified Ig, thereby identifying displacement one water molecule arginine as delivering catalysis.