Apr 9, 2020

Discovering loop conformational flexibility in T4 lysozyme mutants through Artificial Intelligence aided Molecular Dynamics

BioRxiv : the Preprint Server for Biology
Z. SmithPratyush Tiwary


Proteins sample a large variety of conformations distinct from their crystal structure. These structures, their thermodynamic propensities, and the pathways for moving between them contain a wealth of information about protein function that is hidden from a purely structural perspective. Molecular dynamics simulations can uncover these higher energy states but often at a prohibitively high computational cost. Here we apply our recent statistical mechanics and artificial intelligence based all-atom molecular dynamics framework for enhanced sampling of protein loops in three mutants of the protein T4 lysozyme. We are able to rank these three mutants according to the stability of their excited state and accurately recover the thermodynamic stability found through experiment. By an analysis of the optimized reaction coordinates, we also obtain crucial insight into why these specific but small perturbations in sequence space lead to tremendous variations in conformational flexibility. Our framework thus allows accurate comparison of loop conformation populations without the extensive computational resources previously required to conduct such a study, and should be directly applicable to a range of macromolecules including proteins,...Continue Reading

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Mentioned in this Paper

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