An explicit-solvent conformation search method using open software
A peer-reviewed article of this Preprint also exists.
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Abstract
Computer modeling is a popular tool to identify the most-probable conformers of a molecule. Although the solvent can have a large effect on the stability of a conformation, many popular conformational search methods are only capable of describing molecules in the gas phase or with an implicit solvent model. We have developed a work-flow for performing a conformation search on explicitly-solvated molecules using open source software. This method uses replica exchange molecular dynamics to sample the conformational states of the molecule efficiently. Cluster analysis is used to identify the most probable conformations from the simulated trajectory. This work-flow was tested on drug molecules a-amanitin and cabergoline to illustrate its capabilities and effectiveness. The preferred conformations of these molecules in gas phase, implicit solvent, and explicit solvent are significantly different.
Cite this as
2016. An explicit-solvent conformation search method using open software. PeerJ Preprints 4:e1931v1 https://doi.org/10.7287/peerj.preprints.1931v1note This preprint is not peer-reviewed. You may wish to reference the subsequent peer-reviewed version of this article.
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This is a submission to PeerJ for review.
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Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Kari Gaalswyk conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Christopher N Rowley conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
GitHub
3edd8a8
https://github.com/RowleyGroup/fluxionalize
Funding
The authors thank NSERC of Canada for funding through the Discovery Grant program (Application 418505-2012). Kari Gaalswyk thanks Memorial University for funding. Computational resources were provided by Compute Canada (RAPI: djk-615-ab) through the Calcul Quebec and ACEnet consortia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
