Interaction entropy for computational alanine scanning in protein–protein binding

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Abstract

Protein–protein interactions (PPIs) are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein–protein binding is quantitatively characterized by the binding free energy whose accurate calculation from first principle is a grand challenge in computational biology. Accurate prediction of critical residues along with their specific and quantitative contributions to protein–protein binding free energy is extremely helpful to reveal binding mechanisms and identify drug‐like molecules that alter PPIs. In this overview, we describe an interaction entropy (IE) approach combined with the MM/GBSA method for solvation to compute residue‐specific protein–protein binding free energy. In this approach, the entropic contribution to binding free energy of individual residue is explicitly computed by using the IE method from a single MD trajectory. Studies for an extensive set of realistic protein–protein interaction systems demonstrated that by including the entropic contribution, the agreement between the computed residue‐specific binding free energies and the corresponding experimental data is systematically improved. We also show application of the current approach to the important major histocompatibility complex (MHC)‐antigen binding to provide important information on hot spots with potential application for use in cancer vaccine. WIREs Comput Mol Sci 2018, 8:e1342. doi: 10.1002/wcms.1342 This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Free Energy Methods Software > Simulation Methods

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