SNP2SIM

SNP2SIM is a Python-based workflow that generates reproducible molecular dynamics and molecular docking simulations to analyze the impact of sequence variations on protein function. The workflow consists of three independent modules that can be used sequentially:

1. Generation of mutant protein structures and configuration files required for molecular dynamics simulations of solvated protein variant structures using NAMD and VMD software.

2. Clustering of the resulting trajectories based on the structural diversity of residues involved in ligand binding to produce unique variant scaffolds of the protein structure.

3. Binding the unique structural conformations to small molecule ligand libraries using AutoDock Vina to predict variant-induced changes to drug binding relative to the wild-type protein structure.

SNP2SIM simplifies the simulation of variant-specific drug interactions and enables large-scale computational mutagenesis by controlling the parameterization of molecular simulations across multiple users or distributed computing infrastructures. This allows for the parallelization of computationally intensive molecular simulations and facilitates the comparison of various simulation options.

Topic

Molecular dynamics;Molecular modelling;Small molecules

Detail

  • Operation: Molecular dynamics;Molecular docking;Scaffolding

  • Software interface: Command-line interface

  • Language: Python

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: NIH/NHGRI, NIH/NHLBI.

  • Input: -

  • Output: -

  • Contact: Matthew McCoy mdm299@georgetown.edu

  • Collection: -

  • Maturity: -

Publications

  • SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants.
  • McCoy MD, et al. SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants. SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants. 2019; 20:171. doi: 10.1186/s12859-019-2774-9
  • https://doi.org/10.1186/s12859-019-2774-9
  • PMID: 30943891
  • PMC: PMC6448223

Download and documentation


< Back to DB search