Authors
Russell B Davidson, Mathialakan Thavappiragasam, T Chad Effler, Jess Woods, Dwayne A Elias, Jerry M Parks, Ada Sedova
Publication date
2021/8/1
Book
Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
Pages
1-10
Description
Protein structure prediction has become increasingly popular and successful in recent years. An essential step for fragment-free, template-free methods is the generation of a final three-dimensional protein model from a set of predicted amino acid contacts that are often described by interresidue pairwise atomic distances. Here we explore the use of modern, open-source molecular dynamics (MD) engines, which have been continually developed over the last three decades with all-atom Hamiltonians to model biomolecular structure and dynamics, to generate accurate protein structures starting from a set of inferred pairwise distances. Additionally, the ability of MD empirical physical potentials to correct inaccuracies in the predicted geometries is tested. We rigorously characterize the effect of modeling parameters on results, the effect of different amounts of error in the predicted distances on the final structures, and …
Total citations
Scholar articles