Journal of Computational Chemistry · 2014 · 288 citations · 31 references
EngineeringProtein AssemblyBiomolecular Structure PredictionStructural BioinformaticsMolecular BiologyComputational ChemistryMolecular DynamicsMolecular DesignAutomated Protein StructureProtein FoldingBiophysicsComputational Protein DesignBiochemistryAmino Acid MutationProtein ModelingProtein Structure PredictionStructural BiologyGromacs Simulation PackageSystems BiologyMedicineComputational Biophysics
Computational protein design requires methods to accurately estimate free energy changes in protein stability or binding upon an amino acid mutation. From the different approaches available, molecular dynamics-based alchemical free energy calculations are unique in their accuracy and solid theoretical basis. The challenge in using these methods lies in the need to generate hybrid structures and topologies representing two physical states of a system. A custom made hybrid topology may prove useful for a particular mutation of interest, however, a high throughput mutation analysis calls for a more general approach. In this work, we present an automated procedure to generate hybrid structures and topologies for the amino acid mutations in all commonly used force fields. The described software is compatible with the Gromacs simulation package. The mutation libraries are readily supported for five force fields, namely Amber99SB, Amber99SB*-ILDN, OPLS-AA/L, Charmm22*, and Charmm36.
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A smooth particle mesh Ewald method
Ulrich Essmann, L. Perera, Max L. Berkowitz et al. · The Journal of Chemical Physics · 1995 · 22.3K citations
William L. Jorgensen, David S. Maxwell, Julian Tirado‐Rives · Journal of the American Chemical Society · 1996 · 15K citations
Organic Molecules, Engineering, Conformational Energetics +13