ArticleJournal of computer-aided molecular design2016
A pose prediction approach based on ligand 3D shape similarity.
Article in Journal of computer-aided molecular design, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- CB-Dock3: an enhanced web server for protein-ligand blind docking.Nucleic acids research · 2026Article
- TEMPL: A Template-Based Protein-Ligand Pose Prediction Baseline.Journal of chemical information and modeling · 2025Article
- Building shape-focused pharmacophore models for effective docking screening.Journal of cheminformatics · 2024Article
- Biased Docking for Protein-Ligand Pose Prediction.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches.Molecules (Basel, Switzerland) · 2020Review
- Improving ligand 3D shape similarity-based pose prediction with a continuum solvent model.Journal of computer-aided molecular design · 2019Article
- Binding mode information improves fragment docking.Journal of cheminformatics · 2019Article
- D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.Journal of computer-aided molecular design · 2019Article
- Shape similarity guided pose prediction: lessons from D3R Grand Challenge 3.Journal of computer-aided molecular design · 2019Article
- A cross docking pipeline for improving pose prediction and virtual screening performance.Journal of computer-aided molecular design · 2018Article
- Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery.Frontiers in chemistry · 2018Review
- D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions.Journal of computer-aided molecular design · 2016Article
- Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015.Journal of computer-aided molecular design · 2016Article
- Improved pose and affinity predictions using different protocols tailored on the basis of data availability.Journal of computer-aided molecular design · 2016Article
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2 authors.
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Abstract
Molecular docking predicts the best pose of a ligand in the target protein binding site by sampling and scoring numerous conformations and orientations of the ligand. Failures in pose prediction are often due to either insufficient sampling or scoring function errors. To improve the accuracy of pose prediction by tackling the sampling problem, we have developed a method of pose prediction using shape similarity. It first places a ligand conformation of the highest 3D shape similarity with known crystal structure ligands into protein binding site and then refines the pose by repacking the side-chains and performing energy minimization with a Monte Carlo algorithm. We have assessed our method utilizing CSARdock 2012 and 2014 benchmark exercise datasets consisting of co-crystal structures from eight proteins. Our results revealed that ligand 3D shape similarity could substitute conformational and orientational sampling if at least one suitable co-crystal structure is available. Our method identified poses within 2 Å RMSD as the top-ranking pose for 85.7 % of the test cases. The median RMSD for our pose prediction method was found to be 0.81 Å and was better than methods performing extensive conformational and orientational sampling within target protein binding sites. Furthermore, our method was better than similar methods utilizing ligand 3D shape similarity for pose prediction.
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