ArticleJournal of chemical information and modeling2024
AutoDock-SS: AutoDock for Multiconformational Ligand-Based Virtual Screening.
Article in Journal of chemical information and modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Anticancer effects of bisabolol oxide A-Loaded Micellar/Liposomal nanoparticles on DU-145 cells with deregulation of miR-34a and miR-181a: in silico and in vitro studies.BMC biotechnology · 2026Article
- DeepDrugDiscovery identifies blood-brain barrier permeable autophagy enhancers for Alzheimer's disease.Nature biomedical engineering · 2026Article
- AnCurrent drug targets · 2026Article
- Mechanistic Insights into the Ferroptosis-Regulating Effects of EF in the Treatment of Chronic Renal Failure.Current medicinal chemistry · 2026Article
- Design, Synthesis and Anti-Alzheimer's Activity of Some Hybrid Molecule of Oxymatrine Through TGF-β.Current topics in medicinal chemistry · 2026Article
- Network Pharmacology and Molecular Docking Identify Medicarpin as a Potent CASP3 and ESR1 Binder Driving Apoptotic and Hormone-Dependent Anticancer Activity.International journal of molecular sciences · 2025Article
- Computational Investigation Identifies mTOR as a Primary Binding Target of Medicarpin in Cholangiocarcinoma: Insights from Network Pharmacology and Molecular Docking.Life (Basel, Switzerland) · 2025Article
- UPLC-Q-TOF-MS and network pharmacology to reveal the mechanism of Guizhi Gegen decoction against type 2 diabetes mellitus.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Exploring the molecular mechanisms underlying intervertebral disc degeneration by analysing multiple datasets.Scientific reports · 2025Article
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5 authors.
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Abstract
Ligand-based virtual screening (LBVS) can be pivotal for identifying potential drug leads, especially when the target protein's structure is unknown. However, current LBVS methods are limited in their ability to consider the ligand conformational flexibility. This study presents AutoDock-SS (Similarity Searching), which adapts protein-ligand docking for use in LBVS. AutoDock-SS integrates novel ligand-based grid maps and AutoDock-GPU into a novel three-dimensional LBVS workflow. Unlike other approaches based on pregenerated conformer libraries, AutoDock-SS's built-in conformational search optimizes conformations dynamically based on the reference ligand, thus providing a more accurate representation of relevant ligand conformations. AutoDock-SS supports two modes: single and multiple ligand queries, allowing for the seamless consideration of multiple reference ligands. When tested on the Directory of Useful Decoys─Enhanced (DUD-E) data set, AutoDock-SS surpassed alternative 3D LBVS methods, achieving a mean AUROC of 0.775 and an EF
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