Replica-Exchange Enveloping Distribution Sampling Using Generalized AMBER Force-Field Topologies: Application to Relative Hydration Free-Energy Calculations for Large Sets of Molecules
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Date
2022-06-27
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Journal Article
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Abstract
Free-energy differences between pairs of end-states can be estimated based on molecular dynamics (MD) simulations using standard pathway-dependent methods such as thermodynamic integration (TI), free-energy perturbation, or Bennett's acceptance ratio. Replica-exchange enveloping distribution sampling (RE-EDS), on the other hand, allows for the sampling of multiple end-states in a single simulation without the specification of any pathways. In this work, we use the RE-EDS method as implemented in GROMOS together with generalized AMBER force-field (GAFF) topologies, converted to a GROMOS-compatible format with a newly developed GROMOS++ program amber2gromos, to compute relative hydration free energies for a series of benzene derivatives. The results obtained with RE-EDS are compared to the experimental data as well as calculated values from the literature. In addition, the estimated free-energy differences in water and in vacuum are compared to values from TI calculations carried out with GROMACS. The hydration free energies obtained using RE-EDS for multiple molecules are found to be in good agreement with both the experimental data and the results calculated using other free-energy methods. While all considered free-energy methods delivered accurate results, the RE-EDS calculations required the least amount of total simulation time. This work serves as a validation for the use of GAFF topologies with the GROMOS simulation package and the RE-EDS approach. Furthermore, the performance of RE-EDS for a large set of 28 end-states is assessed with promising results.
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published
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Journal / series
Volume
62 (12)
Pages / Article No.
3043 - 3056
Publisher
American Chemical Society
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Organisational unit
09458 - Riniker, Sereina Z. / Riniker, Sereina Z.
08820 - Hünenberger, Philippe (Tit.-Prof.)
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Funding
178762 - Passive Membrane-Permeability Prediction for Peptides and Peptidomimetics Using Computational Methods (SNF)
175944 - A Combinatorial Computational Chemistry Approach to Force-Field Development (SNF)
175944 - A Combinatorial Computational Chemistry Approach to Force-Field Development (SNF)