ArticleFrontiers in chemistry2019
CherryPicker: An Algorithm for the Automated Parametrization of Large Biomolecules for Molecular Simulation.
Article in Frontiers in chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- OFraMP: a fragment-based tool to facilitate the parametrization of large molecules.Journal of computer-aided molecular design · 2023Article
- GRAPES-DD: exploiting decision diagrams for index-driven search in biological graph databases.BMC bioinformatics · 2021Article
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Authors and funding
2 authors.
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Abstract
Molecular simulations allow investigation of the structure, dynamics and thermodynamics of molecules at an atomic level of detail, and as such, are becoming increasingly important across many areas of science. As the range of applications increases, so does the variety of molecules. Simulation of a new type of molecule requires generation of parameters that result in accurate representation of the behavior of that molecule, and, in most cases, are compatible with existing parameter sets. While many automated parametrization methods exist, they are in general not well suited to large and conformationally dynamic molecules. We present here a method for automated assignment of parameters for large, novel biomolecules, and demonstrate its usage for peptides of varying degrees of complexity. Our method uses a graph theoretic representation to facilitate matching of the target molecule to molecular fragments for which reliable parameters are available. It requires minimal user input and creates parameter files compatible with the widely-used GROMACS simulation software.
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