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Performance evaluation of molecular docking and free energy calculations protocols using the D3R Grand Challenge 4 dataset

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Abstract

Using the D3R Grand Challenge 4 dataset containing Beta-secretase 1 (BACE) and Cathepsin S (CatS) inhibitors, we have evaluated the performance of our in-house docking workflow that involves in the first step the selection of the most suitable docking software for the system of interest based on structural and functional information available in public databases, followed by the docking of the dataset to predict the binding modes and ranking of ligands. The macrocyclic nature of the BACE ligands brought additional challenges, which were dealt with by a careful preparation of the three-dimensional input structures for ligands. This provided top-performing predictions for BACE, in contrast with CatS, where the predictions in the absence of guiding constraints provided poor results. These results highlight the importance of previous structural knowledge that is needed for correct predictions on some challenging targets. After the end of the challenge, we also carried out free energy calculations (i.e. in a non-blinded manner) for CatS using the pmx software and several force fields (AMBER, Charmm). Using knowledge-based starting pose construction allowed reaching remarkable accuracy for the CatS free energy estimates. Interestingly, we show that the use of a consensus result, by averaging the results from different force fields, increases the prediction accuracy.

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Funding

The funding was provided by Agence Nationale de la Recherche (FR) (Grant Nos. ANR-10-LABX-33, ANR-14-JAMR-0002); Conseil Régional, Île-de-France (DIM Malinf); Université Paris-Saclay (Globetalkers 2019); H2020 European Research Council (ERC-2012-ADG_20120314, Grant Agreement 322947).

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Authors and Affiliations

  1. Institut de Chimie des Substances Naturelles, CNRS UPR 2301, Université Paris-Saclay, Labex LERMIT, Gif-sur-Yvette, France

    Eddy Elisée, Nawel Mele, Ludovic Chaput, Edithe Selwa & Bogdan I. Iorga

  2. Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

    Vytautas Gapsys & Bert L. de Groot

  3. Sorbonne Université, UPMC Paris 06, Institut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche S 1155, Paris, France

    Ludovic Chaput

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  1. Eddy Elisée
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  2. Vytautas Gapsys
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  3. Nawel Mele
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  4. Ludovic Chaput
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  5. Edithe Selwa
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  6. Bert L. de Groot
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  7. Bogdan I. Iorga
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Correspondence to Bert L. de Groot or Bogdan I. Iorga.

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Research reported in this publication was supported by grants ANR-10-LABX-33 (LabEx LERMIT) and ANR-14-JAMR-0002 (JPIAMR) from the French National Research Agency (ANR), by the Région Ile-de-France (DIM Malinf), by the Université Paris-Saclay (Globetalkers 2019) and by European Research Council grant ERC-2012-ADG_20120314 (Grant Agreement 322947).

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Elisée, E., Gapsys, V., Mele, N. et al. Performance evaluation of molecular docking and free energy calculations protocols using the D3R Grand Challenge 4 dataset. J Comput Aided Mol Des 33, 1031–1043 (2019). https://doi.org/10.1007/s10822-019-00232-w

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