Genetic Algorithms Applied to Thermodynamic Rational Design of Mimetic Antibodies Based on the GB1 Domain of Streptococcal Protein G: An Atomistic Simulation Study.

Abstract

The development of mimetic antibodies (MA) capable of combining the high affinity and selectivity of antibodies with the small size of the peptides has enormous potential for applications in current biotechnology. In this work, we demonstrate that in silico MA design is possible through genetic algorithms (GA) developed from shell scripts capable of combining software commonly used for atomistic simulation. Our results demonstrate that, using the GB1 domain of the streptococcal G protein as a model, it is possible to optimize the molecular recognition capacity of a large MA population in a few generations. In the first case, GA was able to generate 10 MA with binding free energy (BFE) less than the vascular endothelial cell growth factor conjugated with the fms-type tyrosine kinase receptor. In the second case, it generated 13 MA with BFE less than that of the hepatitis C-E2 viral envelope conjugate with the antibody. Through the GA developed in this work, we demonstrate the use of a new protocol, capable of guiding experimental methods for the design of bioactive peptides that can assist in the development of new therapeutic molecules.