Exploring the use of molecular dynamics in assessing protein variants for phenotypic alterations

Abstract

With the advent of rapid sequencing technologies, making sense of all the genomic variations that we see among us has been a major challenge. A plethora of algorithms and methods exist that try to address genome interpretation through genotype–phenotype linkage analysis or evaluating the loss of function/stability mutations in protein. Critical Assessment of Genome Interpretation (CAGI) offers an exceptional platform to blind-test all such algorithms and methods to assess their true ability. We take advantage of this opportunity to explore the use of molecular dynamics simulation as a tool to assess alteration of phenotype, loss of protein function, interaction, and stability. The results show that coarse-grained dynamics based protein flexibility analysis on 34 CHEK2 and 1719 CALM1 single mutants perform reasonably well for class-based predictions for phenotype alteration and two-thirds of the predicted scores return a correlation coefficient of 0.6 or more. When all-atom dynamics is used to predict altered stability due to mutations for Frataxin protein (8 cases), the predictions are comparable to the state-of-the-art methods. The competitive performance of our straightforward approach to phenotype interpretation contrasts with heavily trained machine learning approaches, and open new avenues to rationally improve genome interpretation.