ArticleJournal of computer-aided molecular design2015
Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock.
Article in Journal of computer-aided molecular design, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands.Journal of computer-aided molecular design · 2024Article
- Bridging Structure- and Ligand-Based Virtual Screening through Fragmented Interaction Fingerprint.ACS omega · 2024Article
- QSAR Study, Molecular Docking and Molecular Dynamic Simulation of Aurora Kinase Inhibitors Derived from Imidazo[4,5-Molecules (Basel, Switzerland) · 2024Article
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- Pongol Methyl Ether Inhibits Akt and Suppresses Cancer Stem Cell Phenotypes in Lung Cancer Cells.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Molecular modeling for potential cathepsin L inhibitor identification as new anti-photoaging agents from tropical medicinal plants.Journal of bioenergetics and biomembranes · 2021Article
- Insight into Inhibitory Mechanism of PDE4D by Dietary Polyphenols Using Molecular Dynamics Simulations and Free Energy Calculations.Biomolecules · 2021Article
- Biased Docking for Protein-Ligand Pose Prediction.Methods in molecular biology (Clifton, N.J.) · 2021Article
- DUBS: A Framework for DevelopingJournal of chemical information and modeling · 2020Article
- ELA/APELA precursor cleaved by furin displays tumor suppressor function in renal cell carcinoma through mTORC1 activation.JCI insight · 2020Article
- CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials.Journal of chemical information and modeling · 2020Article
- Electrostatic-field and surface-shape similarity for virtual screening and pose prediction.Journal of computer-aided molecular design · 2019Article
- AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.Bioinformatics (Oxford, England) · 2019Article
- Practical Model Selection for Prospective Virtual Screening.Journal of chemical information and modeling · 2019Article
- Solvents to Fragments to Drugs: MD Applications in Drug Design.Molecules (Basel, Switzerland) · 2018Review
- Rescoring of docking poses under Occam's Razor: are there simpler solutions?Journal of computer-aided molecular design · 2018Article
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2 authors.
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Abstract
Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.
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