Coupling enhanced sampling of the apo-receptor with template-based ligand conformers selection: performance in pose prediction in the D3R Grand Challenge 4
- 97 Downloads
We report the performance of our newly introduced Ensemble Docking with Enhanced sampling of pocket Shape (EDES) protocol coupled to a template-based algorithm to generate near-native ligand conformations in the 2019 iteration of the Grand Challenge (GC4) organized by the D3R consortium. Using either AutoDock4.2 or HADDOCK2.2 docking programs (each software in two variants of the protocol) our method generated native-like poses among the top 5 submitted for evaluation for most of the 20 targets with similar performances. The protein selected for GC4 was the human beta-site amyloid precursor protein cleaving enzyme 1 (BACE-1), a transmembrane aspartic-acid protease. We identified at least one pose whose heavy-atoms RMSD was less than 2.5 Å from the native conformation for 16 (80%) and 17 (85%) of the 20 targets using AutoDock and HADDOCK, respectively. Dissecting the possible sources of errors revealed that: (i) our EDES protocol (with minor modifications) was able to sample sub-ångstrom conformations for all 20 protein targets, reproducing the correct conformation of the binding site within ~ 1 Å RMSD; (ii) as already shown by some of us in GC3, even in the presence of near-native protein structures, a proper selection of ligand conformers is crucial for the success of ensemble-docking calculations. Importantly, our approach performed best among the protocols exploiting only structural information of the apo protein to generate conformations of the receptor for ensemble-docking calculations.
KeywordsMolecular docking Metadynamics EDES HADDOCK AutoDock BACE-1
A.B. gratefully acknowledges the Sardinia Regional Government for the financial support of his Ph.D. scholarship (P.O.R. Sardegna F.SE., Operational Programme of the Autonomous Region of Sardinia, European Social Fund 2014–2020—Axis III Education and Training, Thematic Goal 10, Priority of Investment 10ii, Specific Goal 10.5., Action Partnership Agreement 10.5.12). This work was done as part of the BioExcel CoE (www.bioexcel.eu), a project funded by the European Union Horizon 2020 Program under Grant Agreements 675728 and 823830 (to A. M. J. J. B.) with financial support from the Dutch Foundation for Scientific Research (NWO) (TOP-PUNT Grant 718.015.001.
- 19.Hawkins PCD, Skillman AG, Warren GL et al (2010) Conformer generation with OMEGA: algorithm and validation using high quality structures from the protein databank and cambridge structural database. J Chem Inf Model 50:572–584. https://doi.org/10.1021/ci100031x CrossRefPubMedPubMedCentralGoogle Scholar
- 29.Case DA, Ben-Shalom IY, Brozell SR et al (2018) AMBER18. University of California, San FranciscoGoogle Scholar