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Proceedings ArticleDOI

ProMuteHT: A High Throughput Compute Pipeline for Generating Protein Mutants in silico

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TLDR
ProMuteHT is presented, a program for high throughput in silico generating user-specified sets of mutant protein structures with single or multiple amino acid substitutions that are of high quality, as determined via all-atom and mutated residue RMSD measurements for existing mutant structures in the PDB.
Abstract
Understanding how an amino acid substitution affects a protein's structure is fundamental to advancing drug design and protein docking studies. Mutagenesis experiments on physical proteins provide a precise assessment of the effects of mutations, but they are time and cost prohibitive. Computational approaches for performing in silico amino acid substitutions are available, but they are not suited for generating large numbers of protein variants needed for high-throughput screening studies. We present ProMuteHT, a program for high throughput in silico generating user-specified sets of mutant protein structures with single or multiple amino acid substitutions. We combine our custom mutation algorithm with side chain homology modeling external libraries, and generate energetically feasible mutant structures. Our efficient command-line invocation syntax requires only a few arguments to specify large datasets of mutant structures. We achieve quick run-times due to our hybrid approach in which we limit the use of costly energy calculations when mutating from a large to a small amino acid. We compare our mutant structures with those generated by FoldX, and report faster run-times. We show that the mutants generated by ProMuteHT are of high quality, as determined via all-atom and mutated residue RMSD measurements for existing mutant structures in the PDB.

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Journal ArticleDOI

Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

TL;DR: This work compares and assess the utility of several machine learning methods and their ability to predict the effects of single and double mutations, and introduces a voting scheme to synthesize a single prediction from the individual predictions of the three models.
Proceedings ArticleDOI

Predicting the Effect of Point Mutations on Protein Structural Stability

TL;DR: This work in silico generate mutant protein structures, and compute several rigidity metrics for each of them, which are features for support vector regression, random forest, and deep neural network methods.
Proceedings ArticleDOI

Elucidating Which Pairwise Mutations Affect Protein Stability: An Exhaustive Big Data Approach

TL;DR: This work motivates and demonstrates a proof of concept approach for conducting in silico experiments in which all possible mutant structures with 2 amino acid substitutions for three proteins with 46, 67, and 99 residues are generated.
Journal ArticleDOI

Mutation Sensitivity Maps: Identifying Residue Substitutions That Impact Protein Structure Via a Rigidity Analysis In Silico Mutation Approach.

TL;DR: A computation pipeline whose only input is a Protein Data Bank file containing the 3D coordinates of the atoms of a biomolecule is motivate and presented, and a Mutation Sensitivity Map is developed, to permit identifying residues that are most sensitive to mutations.
References
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Journal ArticleDOI

The Protein Data Bank

TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Journal ArticleDOI

Scalable molecular dynamics with NAMD

TL;DR: NAMD as discussed by the authors is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales to hundreds of processors on high-end parallel platforms, as well as tens of processors in low-cost commodity clusters, and also runs on individual desktop and laptop computers.
Journal ArticleDOI

SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling.

Nicolas Guex, +1 more
- 01 Jan 1997 - 
TL;DR: An environment for comparative protein modeling is developed that consists of SWISS‐MODEL, a server for automated comparativeprotein modeling and of the SWiss‐PdbViewer, a sequence to structure workbench that provides a large selection of structure analysis and display tools.
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