Mutational Locally Enhanced Sampling (MULES) for quantitative prediction of the effects of mutations at protein–protein interfaces

Abstract

We have successfully developed and validated with experiment a new computational method for quantitatively predicting the effects of mutations at a protein–protein interface. From over 500 ns of explicitly solvated molecular dynamics, Mutational Locally Enhanced Sampling (MULES) shows significantly improved accuracy over post-processing methods for a prototypical set of mutations, with a maximum mean unsigned error to experiment of 0.5 kcal mol⁻¹ and comparable or better precision. The technique in principle allows the effect of any mutation to be calculated, whether natural or non-natural. The versatility, quantitative accuracy, high precision and speed of MULES compared to existing computational prediction techniques enhance its potential for modelling changes to the interface in a systematic way, thereby aiding peptide and protein interaction design.