D3R Grand Challenge 3: blind prediction of protein–ligand poses and affinity rankings
| Autor: | Scott D. Bembenek, W. Patrick Walters, Neysa Nevins, Zied Gaieb, Michael K. Gilson, Michael Chiu, Chenghua Shao, Stephen K. Burley, Tara Mirzadegan, Rommie E. Amaro, Conor Parks, Millard H. Lambert, Michael K. Ameriks, Huanwang Yang |
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| Rok vydání: | 2019 |
| Předmět: |
Protein Conformation
Computer science VEGF receptors Ligand ranking Crystallography X-Ray Ligands computer.software_genre 01 natural sciences Docking Theoretical and Computational Chemistry Drug Discovery Databases Protein Crystallography 010304 chemical physics biology Blinded prediction challenge Computer Science Applications Molecular Docking Simulation Thermodynamics Computer-Aided Design Pose prediction D3R Protein Binding Design data Medicinal & Biomolecular Chemistry Machine learning Article Databases Medicinal and Biomolecular Chemistry 0103 physical sciences Drug Design Data Resource Physical and Theoretical Chemistry Protein Kinase Inhibitors Binding Sites business.industry Protein Cathepsins 0104 chemical sciences 010404 medicinal & biomolecular chemistry Drug Design X-Ray biology.protein Generic health relevance Artificial intelligence business Protein Kinases computer Scoring Protein ligand |
| Zdroj: | Journal of computer-aided molecular design, vol 33, iss 1 |
| ISSN: | 1573-4951 0920-654X |
| DOI: | 10.1007/s10822-018-0180-4 |
| Popis: | The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling, by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017–2018, GC3 centered on the protein Cathepsin S and the kinases VEGFR2, JAK2, p38-α, TIE2, and ABL1; and included both pose-prediction and affinity-ranking components. GC3 was structured much like the prior challenges GC2015 and GC2. First, Stage 1 tested pose prediction and affinity ranking methods; then all available crystal structures were released, and Stage 2 tested only affinity rankings, now in the context of the available structures. Unique to GC3 was the addition of a Stage 1b self-docking subchallenge, in which the protein coordinates from all of the cocrystal structures used in the cross-docking challenge were released, and participants were asked to predict the pose of CatS ligands using these newly released structures. We provide an overview of the outcomes and discuss insights into trends and best-practices. |
| Databáze: | OpenAIRE |
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