ArticleJournal of cheminformatics2020
LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates.
Article in Journal of cheminformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 20 citations in OpenAlex.
- Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.Journal of cheminformatics · 2026Article
- Computational and experimental exploration of statin and statin-like compounds as potential treatment of schistosomiasis.PLoS neglected tropical diseases · 2025Article
- Innovative Approaches in Molecular Docking for the Discovery of Novel Inhibitors Against Alzheimer's Disease.Current Alzheimer research · 2025Review
- The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges.Molecular therapy. Nucleic acids · 2024Review
- Targeting the hSSB1-INTS3 Interface: A Computational Screening Driven Approach to Identify Potential Modulators.ACS omega · 2024Article
- Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges.Pharmaceutics · 2024Review
- VSpipe-GUI, an Interactive Graphical User Interface for Virtual Screening and Hit Selection.International journal of molecular sciences · 2024Article
- Article
- Development of Antiepileptic Drugs throughout History: From Serendipity to Artificial Intelligence.Biomedicines · 2023Review
- Ringtail: A Python Tool for Efficient Management and Storage of Virtual Screening Results.Journal of chemical information and modeling · 2023Article
- Artificial Intelligence and Machine Learning Based Intervention in Medical Infrastructure: A Review and Future Trends.Healthcare (Basel, Switzerland) · 2023Review
- The Impact of Software Used and the Type of Target Protein on Molecular Docking Accuracy.Molecules (Basel, Switzerland) · 2022Article
- Design, Synthesis, and Biological Evaluation of 4,4'-Difluorobenzhydrol Carbamates as Selective MPharmaceuticals (Basel, Switzerland) · 2022Article
- Artificial intelligence unifies knowledge and actions in drug repositioning.Emerging topics in life sciences · 2021Review
- A Deep-Learning Proteomic-Scale Approach for Drug Design.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study.Journal of chemical information and modeling · 2021Article
- Artificial intelligence to deep learning: machine intelligence approach for drug discovery.Molecular diversity · 2021Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predicting the geometry with which a given compound might bind a target receptor (e.g., the docked "pose" relative to a protein target). Candidate ligands predicted to participate in the same intermolecular interactions typical of known ligands (or ligands that bind related proteins) are arguably more likely to be true binders. Some docking programs allow users to apply constraints during the docking process with the goal of prioritizing these critical interactions. But these programs often have restrictive and/or expensive licenses, and many popular open-source docking programs (e.g., AutoDock Vina) lack this important functionality. We present LigGrep, a free, open-source program that addresses this limitation. As input, LigGrep accepts a protein receptor file, a directory containing many docked-compound files, and a list of user-specified filters describing critical receptor/ligand interactions. LigGrep evaluates each docked pose and outputs the names of the compounds with poses that pass all filters. To demonstrate utility, we show that LigGrep can improve the hit rates of test VS targeting H. sapiens poly(ADPribose) polymerase 1 (HsPARP1), H. sapiens peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (HsPin1p), and S. cerevisiae hexokinase-2 (ScHxk2p). We hope that LigGrep will be a useful tool for the computational biology community. A copy is available free of charge at http://durrantlab.com/liggrep/ .
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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.