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Effect of sampling on BACE-1 ligands binding free energy predictions via MM-PBSA calculations

Abstract : The BACE-1 enzyme is a prime target to find a cure to Alzheimer's disease. In this paper, we used the MM-PBSA approach to compute the binding free energies of 46 reported ligands to this enzyme. After showing that the most probable protonation state of the catalytic dyad is mono-protonated (on ASP32), we performed a thorough analysis of the parameters influencing the sampling of the conformational space (in total, more than 35 s of simulations were performed). We show that ten simulations of 2ns gives better results than one of 50ns. We also investigated the influence of the protein force field, the water model, the periodic boundary conditions artifacts (box size), as well as the ionic strength. Amber03 with TIP3P, a minimal distance of 1.0nm between the protein and the box edges and a ionic strength of I=0.2M provides the optimal correlation with experiments. Overall, when using these parameters, a Pearson correlation coefficient of R=0.84 (R 2 =0.71) is obtained for the 46 ligands, spanning 8 orders of magnitude of Kd (from 0.017nm to 2000M i.e. from-14.7 to-3.7 kcal/mol), with a ligand size from 22 to 136 atoms (from 138 to 937 g/mol). After a two-parameter fit of the binding affinities for 12 of the ligands, an error of RMSD = 1.7 kcal/mol was obtained for the remaining ligands.
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Contributor : Nicolas Chéron <>
Submitted on : Wednesday, October 21, 2020 - 2:19:46 PM
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Nicolas Chéron, Eugene Shakhnovich. Effect of sampling on BACE-1 ligands binding free energy predictions via MM-PBSA calculations. Journal of Computational Chemistry, Wiley, 2017, 38 (22), pp.1941-1951. ⟨10.1002/jcc.24839⟩. ⟨hal-02973957⟩



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