Wells, N. G. M. (2021). Predicting Mutational Free Energy Perturbations Using Molecular Dynamics Simulations. Retrieved from https://doi.org/10.14418/wes01.2.316
Computational modeling is an immensely powerful method for understanding the dynamics and energetic of proteins at the atomic level. Here we employ computational techniques to study the effects of mutations on the biophysical characteristics of proteins. First, we utilize reliable and accurate molecular dynamics simulations to predict the perturbations of 10 amyotrophic lateral sclerosis (ALS)-causing mutations on the free energy changes of Superoxide Dismutase I (SOD1) as it matures from apo monomer to metallated dimer, finding that the free energy perturbations caused by these mutations strongly depend on maturational progress. These results indicate the need for state-specific therapeutic targeting. We also find that many mutations exhibit similar patterns of perturbation to native and non-native maturation, indicating strong thermodynamic coupling between the dynamics at various sites of maturation within SOD1. We then apply these techniques to the study of the SOD1-Copper Chaperone complex, finding further mutational perturbations to the interaction of SOD1 with this important protein. Analysis of these perturbations may contribute to uncovering a unifying molecular mechanism which explains SOD1-linked ALS and may help to guide future therapeutic efforts. Finally, we apply free energy calculations to study the aryl hydrocarbon receptor nuclear translocator protein. We find that our simulations are able to recapitulate experimental evidence which shows a pressure-dependent, mutationally-induced ß-strand slip in the protein. We work towards identifying the atomistic mechanisms behind this unique structural change which may aid future efforts in precisely controlling protein conformation. These analyses will contribute to a greater understanding of how mutations influence the biophysical properties of proteins and may help to develop new therapies which can take advantage of these influences in order to treat disease.