CuT-REMD : uma nova abordagem para predição de estruturas terciárias de proteínas baseada em raio de corte incremental

Abstract

Among the main computational techniques currently applied to study proteins, classical molecular dynamics plays a important hole, specially its variation called replica exchange molecular dynamics or REMD, which provides efficient conformational sampling. Regular secondary structures elements of proteins are formed and maintained via stabilization by hydrogen bonds within helices and between strands of a -sheet. Packing of these structural elements, allowed by flexible turns and loops connecting them, leads to the formation of a structure that, in the successful cases, represents the native, functional state of a protein. Ionic, dipole, van der Waals, hydrophobic interactions, and hydrogen bonding are fundamental to these events. Most of these forces are strong up to a distance of 4.0 Å. Hence, these are the distances involved in the formation of local structural nubs that can further propagate and form whole elements of secondary structure. The common practice while simulating is, however, to keep fixed the cutoff at values higher or equal to 8.0 Å. Here a novel replica exchange molecular dynamics approach based on running cutoffs (varying from 4.0 Å to 8.0 Å) to enhance protein structure prediction is presented. We first proved the method as a reproducible one, as well as following a Boltzmann distribution and sampling different structures of conventional REMD. The human villin headpiece protein (PDB ID: 1UNC) was used as case study. We tested 9 different simulation protocols, in triplicate, and proved the use of incremental cutoff as an effective approach to enhance the quality and speed of protein structure predictions via replica exchange molecular dynamics. Applying the method to the protein test set, although of limited size, CuT-REMD showed good performance against the ab initio methods, most of the time being either as the best prediction method or with close results to the best ones. This made it possible to also compare CuT-REMD with de novo methods. Despite the difficulties, CuT-REMD maintained a good performance even surpassing certain servers for all tested proteins. The results obtained are encouraging, with the emergence of new questions to be addressed in the future.