ArticleJournal of chemical information and modeling2021
Ligand Strain Energy in Large Library Docking.
Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed, 55 citations in OpenAlex.
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- Attracting Cavities 3.0: faster and more versatile molecular docking for the SwissDock webserver.Bioinformatics (Oxford, England) · 2026Article
- Modeling the Sensitivity of Large-Scale Virtual Screening to Scoring Function Accuracy, Artifacts, and Library Composition.Journal of chemical information and modeling · 2026Article
- Library Docking for Cannabinoid-2 Receptor Ligands.Journal of medicinal chemistry · 2026Article
- Prioritizing neuroactive ligands using motif-guided virtual discovery and zebrafish profiling.npj drug discovery · 2026Article
- MolPIF: a parameter interpolation flow model for molecule generation.Bioinformatics (Oxford, England) · 2026Article
- Discovery of Novel Chemotype LRRK2 Inhibitors Through AlphaFold2-Generated Structure-Based Docking Screen.International journal of molecular sciences · 2026Article
- Library docking for Cannabinoid-2 Receptor ligands.bioRxiv : the preprint server for biology · 2026Article
- Highly enantioselective reduction of benzophenones by engineered Geotrichum candidum alcohol dehydrogenase.Applied microbiology and biotechnology · 2026Article
- Prioritizing Neuroactive Ligands Using Motif-Guided Virtual Discovery and Zebrafish Profiling.bioRxiv : the preprint server for biology · 2026Article
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- Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments.bioRxiv : the preprint server for biology · 2025Article
- Discriminating High from Low Energy Conformers of Druglike Molecules: An Assessment of Machine Learning Potentials and Quantum Chemical Methods.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025Article
- An ANI-2 enabled open-source protocol to estimate ligand strain after docking.Journal of computational chemistry · 2025Article
- Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches.npj drug discovery · 2025Review
- Large library docking identifies positive allosteric modulators of the calcium-sensing receptor.Science (New York, N.Y.) · 2024Article
- AlphaFold2 structures guide prospective ligand discovery.Science (New York, N.Y.) · 2024Article
- The Science and Art of Structure-Based Virtual Screening.ACS medicinal chemistry letters · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
While small molecule internal strain is crucial to molecular docking, using it in evaluating ligand scores has remained elusive. Here, we investigate a technique that calculates strain using relative torsional populations in the Cambridge Structural Database, enabling fast precalculation of these energies. In retrospective studies of large docking screens of the dopamine D4 receptor and of AmpC β-lactamase, where close to 600 docking hits were tested experimentally, including such strain energies improved hit rates by preferentially reducing the ranks of strained high-scoring decoy molecules. In a 40-target subset of the DUD-E benchmark, we found two thresholds that usefully distinguished between ligands and decoys: one based on the total strain energy of the small molecules and another based on the maximum strain allowed for any given torsion within them. Using these criteria, about 75% of the benchmark targets had improved enrichment after strain filtering. Relying on precalculated population distributions, this approach is rapid, taking less than 0.04 s to evaluate a conformation on a standard core, making it pragmatic for precalculating strain in even ultralarge libraries. Since it is scoring function agnostic, it may be useful to multiple docking approaches; it is openly available at http://tldr.docking.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.