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Conformational Selection of a Polyproline Peptide by Ebola Virus VP30
Author(s) -
Olson Mark A.
Publication year - 2018
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201800081
Subject(s) - polyproline helix , ebola virus , peptide , selection (genetic algorithm) , chemistry , human immunodeficiency virus (hiv) , virology , computational biology , biology , virus , biochemistry , computer science , machine learning
An adaptive temperature‐based replica‐exchange simulation of a peptide extracted from the Ebola virus nucleoprotein containing a polyproline sequence motif is reported. The simulation results of applying the CHARMM36m force field with a generalized Born solvent model is presented. Conformational heterogeneity is described by potentials of mean force (PMFs) for a set of reaction coordinates that define the topological fold space. Starting from an extended backbone conformation of the peptide observed in an X‐ray crystallographic assembly with the Ebola virus protein VP30, the PMFs report a conformational landscape populated by chain excursions to collapsed states with limited transitions to either an extended fold or a canonical polyproline type II helix. Clustering of the conformations and applying an elastic network interpolation model yield a multistep pathway of conformational selection that minimizes the net transition‐state cost from the population hub to the bound state. Related difference between the pathway endpoints taken from the PMFs reveal a significant free‐energy penalty in reaching a population shift. To evaluate sequence fitness of the Ebola virus peptide in generating probability distributions, two human sequence variants are modeled and are found to produce profiles that show extensive deviations, thus suggesting either dissimilar binding mechanisms or the lack of recognition by VP30.