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  • Assessment of Binding Affin...
    Kuhn, Maximilian; Firth-Clark, Stuart; Tosco, Paolo; Mey, Antonia S J S; Mackey, Mark; Michel, Julien

    Journal of chemical information and modeling, 06/2020, Letnik: 60, Številka: 6
    Journal Article

    Free-energy calculations have seen increased usage in structure-based drug design. Despite the rising interest, automation of the complex calculations and subsequent analysis of their results are still hampered by the restricted choice of available tools. In this work, an application for automated setup and processing of free-energy calculations is presented. Several sanity checks for assessing the reliability of the calculations were implemented, constituting a distinct advantage over existing open-source tools. The underlying workflow is built on top of the software Sire, SOMD, BioSimSpace, and OpenMM and uses the AMBER 14SB and GAFF2.1 force fields. It was validated on two datasets originally composed by Schrödinger, consisting of 14 protein structures and 220 ligands. Predicted binding affinities were in good agreement with experimental values. For the larger dataset, the average correlation coefficient was 0.70 ± 0.05 and average Kendall's τ was 0.53 ± 0.05, which are broadly comparable to or better than previously reported results using other methods.