Robotic mechanism-based QM/MM maturation of a scavenger antibody mutationally boosts its performance

Golovin A.V.

Lomonosov Moscow State University, Moscow 119991, Russian Federation.

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

© 2004 Designed by Lyceum of Informational Technologies №1533