MDM-TASK-web: MD-TASK and MODE-TASK web server for analyzing protein dynamics

Abstract

Highlights Web server for MD-TASK and MODE-TASK, with new tools and updates. Eight dynamic residue network centrality metrics for analyzing protein molecular dynamics, extended for static proteins. Comparative essential dynamics for improved comparison of independent molecular dynamic simulations of related proteins. A communication propensity tool for evaluating residue communication efficiency. Normal mode analysis of proteins from static structures and molecular dynamic simulations.

Allosteric pockets and dynamic residue network hubs of falcipain 2 in mutations including those linked to artemisinin resistance

“…Comparative essential dynamics, as implemented by the MDM-TASK-web “compare_essential_dynamics.py” tool [41] , was run on a local Linux cluster to assess the distribution of pocket conformational sampling across MD simulations for the WT and 11 mutant FP-2 proteins in the same eigen subspace. In essence, the comparative essential dynamics approach involves data filtering and alignment of all MD frames to a common reference (using C α atoms) before proceeding to a single decomposition.…”

“…To determine the effect of the missense mutations on the flow of information within the protein residue network, DRN analysis was performed using the newly established MDM-TASK-web server [41] . In this approach, each residue C β (C α for Gly) is treated as a node, while the inter-node proximity is used to define the edges that compose a network graph.…”

“…Averaged centrality values produced by MDM-TASK-web [41] for related proteins were pooled before extracting the global top 5% central nodes, separately for each metric as recently reported by Sheik Amamuddy et al [43] . To do so, the centrality values from each protein were concatenated as a vector and sorted in descending order to determine a global cut-off value.…”

“…Residue contact map analysis was performed to estimate how often a residue of interest interacts with its neighboring residues throughout the entire MD trajectory, using the contact_map.py and the contact_heatmap.py scripts from MDM-TASK-web [40] , [41] . A cut-off distance of 6.7 Å and a step size of 50 frames were used as parameters for the weighted contact maps, which were then aggregated into a heat map using the contact_heatmap.py .…”

“…The allosteric effect of distant mutations on enzyme function and drug resistance has previously been discussed [34] , [35] , [36] , [37] . Since we proposed the use of dynamic residue network (DRN) in mutation analysis [38] , [39] and established the relevant tools [40] , [41] , this approach has become an integral approach in studying mutation-induced effects in protein structure and function [34] , [35] , [42] . This article takes advantage of an extended version of DRN to assess the impact of these mutations.…”