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SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants
by
Jafri, Mohsin Saleet
, Shivakumar, Vikram
, Madhavan, Subha
, Nimmagadda, Sridhar
, McCoy, Matthew D.
in
Algorithms
/ Amino acid sequence
/ Analysis
/ Atoms
/ Binding
/ Bioinformatics
/ Biomedical and Life Sciences
/ Cancer
/ Cloud computing
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Computer applications
/ Computer networks
/ Computer simulation
/ Distributed processing
/ Drug evaluation
/ Drug resistance
/ Drug screening
/ Functional analysis
/ Functional prediction
/ Genetic variation
/ Genomics
/ Humans
/ Identification and classification
/ Impact prediction
/ Infrastructure
/ Life Sciences
/ Ligand docking
/ Ligands
/ Lymphoma
/ Microarrays
/ Modules
/ Molecular docking
/ Molecular Docking Simulation - methods
/ Molecular dynamics
/ Molecular Dynamics Simulation
/ Molecular modelling
/ Molecular weight
/ Mutagenesis
/ Mutant Proteins - chemistry
/ Mutation
/ Mutation, Missense
/ Novels
/ Parallel processing
/ Parameterization
/ Programming languages
/ Protein binding
/ Protein Conformation
/ Protein structure
/ Proteins
/ Residues
/ Scaffolds
/ Simulation
/ Software
/ Structural analysis
/ Workflow
/ Workflow software
2019
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SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants
by
Jafri, Mohsin Saleet
, Shivakumar, Vikram
, Madhavan, Subha
, Nimmagadda, Sridhar
, McCoy, Matthew D.
in
Algorithms
/ Amino acid sequence
/ Analysis
/ Atoms
/ Binding
/ Bioinformatics
/ Biomedical and Life Sciences
/ Cancer
/ Cloud computing
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Computer applications
/ Computer networks
/ Computer simulation
/ Distributed processing
/ Drug evaluation
/ Drug resistance
/ Drug screening
/ Functional analysis
/ Functional prediction
/ Genetic variation
/ Genomics
/ Humans
/ Identification and classification
/ Impact prediction
/ Infrastructure
/ Life Sciences
/ Ligand docking
/ Ligands
/ Lymphoma
/ Microarrays
/ Modules
/ Molecular docking
/ Molecular Docking Simulation - methods
/ Molecular dynamics
/ Molecular Dynamics Simulation
/ Molecular modelling
/ Molecular weight
/ Mutagenesis
/ Mutant Proteins - chemistry
/ Mutation
/ Mutation, Missense
/ Novels
/ Parallel processing
/ Parameterization
/ Programming languages
/ Protein binding
/ Protein Conformation
/ Protein structure
/ Proteins
/ Residues
/ Scaffolds
/ Simulation
/ Software
/ Structural analysis
/ Workflow
/ Workflow software
2019
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SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants
by
Jafri, Mohsin Saleet
, Shivakumar, Vikram
, Madhavan, Subha
, Nimmagadda, Sridhar
, McCoy, Matthew D.
in
Algorithms
/ Amino acid sequence
/ Analysis
/ Atoms
/ Binding
/ Bioinformatics
/ Biomedical and Life Sciences
/ Cancer
/ Cloud computing
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Computer applications
/ Computer networks
/ Computer simulation
/ Distributed processing
/ Drug evaluation
/ Drug resistance
/ Drug screening
/ Functional analysis
/ Functional prediction
/ Genetic variation
/ Genomics
/ Humans
/ Identification and classification
/ Impact prediction
/ Infrastructure
/ Life Sciences
/ Ligand docking
/ Ligands
/ Lymphoma
/ Microarrays
/ Modules
/ Molecular docking
/ Molecular Docking Simulation - methods
/ Molecular dynamics
/ Molecular Dynamics Simulation
/ Molecular modelling
/ Molecular weight
/ Mutagenesis
/ Mutant Proteins - chemistry
/ Mutation
/ Mutation, Missense
/ Novels
/ Parallel processing
/ Parameterization
/ Programming languages
/ Protein binding
/ Protein Conformation
/ Protein structure
/ Proteins
/ Residues
/ Scaffolds
/ Simulation
/ Software
/ Structural analysis
/ Workflow
/ Workflow software
2019
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SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants
Journal Article
SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants
2019
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Overview
Background
Molecular simulations are used to provide insight into protein structure and dynamics, and have the potential to provide important context when predicting the impact of sequence variation on protein function. In addition to understanding molecular mechanisms and interactions on the atomic scale, translational applications of those approaches include drug screening, development of novel molecular therapies, and targeted treatment planning. Supporting the continued development of these applications, we have developed the SNP2SIM workflow that generates reproducible molecular dynamics and molecular docking simulations for downstream functional variant analysis. The Python workflow utilizes molecular dynamics software (NAMD (Phillips et al., J Comput Chem 26(16):1781-802, 2005), VMD (Humphrey et al., J Mol Graph 14(1):33-8, 27-8, 1996)) to generate variant specific scaffolds for simulated small molecule docking (AutoDock Vina (Trott and Olson, J Comput Chem 31(2):455-61, 2010)).
Results
SNP2SIM is composed of three independent modules that can be used sequentially to generate the variant scaffolds of missense protein variants from the wildtype protein structure. The workflow first generates the mutant structure and configuration files required to execute molecular dynamics simulations of solvated protein variant structures. The resulting trajectories are clustered based on the structural diversity of residues involved in ligand binding to produce one or more variant scaffolds of the protein structure. Finally, these unique structural conformations are bound to small molecule ligand libraries to predict variant induced changes to drug binding relative to the wildtype protein structure.
Conclusions
SNP2SIM provides a platform to apply molecular simulation based functional analysis of sequence variation in the protein targets of small molecule therapies. In addition to simplifying the simulation of variant specific drug interactions, the workflow enables large scale computational mutagenesis by controlling the parameterization of molecular simulations across multiple users or distributed computing infrastructures. This enables the parallelization of the computationally intensive molecular simulations to be aggregated for downstream functional analysis, and facilitates comparing various simulation options, such as the specific residues used to define structural variant clusters. The Python scripts that implement the SNP2SIM workflow are available (SNP2SIM Repository.
https://github.com/mccoymd/SNP2SIM
, Accessed 2019 February ), and individual SNP2SIM modules are available as apps on the Seven Bridges Cancer Genomics Cloud (Lau et al., Cancer Res 77(21):e3-e6, 2017; Cancer Genomics Cloud [
www.cancergenomicscloud.org
; Accessed 2018 November]).
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Analysis
/ Atoms
/ Binding
/ Biomedical and Life Sciences
/ Cancer
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Genomics
/ Humans
/ Identification and classification
/ Ligands
/ Lymphoma
/ Modules
/ Molecular Docking Simulation - methods
/ Molecular Dynamics Simulation
/ Mutation
/ Novels
/ Proteins
/ Residues
/ Software
/ Workflow
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