Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2
| العنوان: | Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2 |
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| المؤلفون: | Veronica Salmaso, Stefano Moro, Alberto Cuzzolin, Mattia Sturlese |
| المصدر: | Journal of Computer-Aided Molecular Design. 32:251-264 |
| بيانات النشر: | Springer Science and Business Media LLC, 2017. |
| سنة النشر: | 2017 |
| مصطلحات موضوعية: | DockBench, 0301 basic medicine, Protein Conformation, Computer science, Receptors, Cytoplasmic and Nuclear, Ligands, Machine learning, computer.software_genre, 01 natural sciences, Self-docking, Small Molecule Libraries, Docking benchmark, 03 medical and health sciences, Software, D3R Grand Challenge 2, Drug Discovery, Humans, Physical and Theoretical Chemistry, Databases, Protein, Simulation, Lead Finder, Binding Sites, Cross-docking, Molecular docking, Drug Discovery3003 Pharmaceutical Science, business.industry, 0104 chemical sciences, Computer Science Applications, Molecular Docking Simulation, Benchmarking, 010404 medicinal & biomolecular chemistry, 030104 developmental biology, Protein–ligand docking, Docking (molecular), Drug Design, Computer-Aided Design, Thermodynamics, Pose prediction, Artificial intelligence, business, computer, Target binding, Protein Binding |
| الوصف: | Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions. |
| تدمد: | 1573-4951 0920-654X |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9441dff1d2f79a68506d6832151b3402 https://doi.org/10.1007/s10822-017-0051-4 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi.dedup.....9441dff1d2f79a68506d6832151b3402 |
| قاعدة البيانات: | OpenAIRE |
Find this article in full text from Springer Verlag. | تدمد: | 15734951 0920654X |
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