ArticleBioinformatics (Oxford, England)2009
EasyMIFS and SiteHound: a toolkit for the identification of ligand-binding sites in protein structures.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Explainable AI reveals the allosteric blind spot in protein-ligand binding predictions.Cell reports. Physical science · 2026Article
- Integrated Framework for Probing Multimodal Protein Foundation Models with Structure-Functional Interpretability Analysis in Detection of Allosteric Binding Sites.bioRxiv : the preprint server for biology · 2026Article
- Predicting and Decoding Allosteric Binding Sites Using Protein Language Models and Structure-Based Machine Learning: An Energy Landscape-Guided Explainable AI Framework.Journal of chemical theory and computation · 2026Article
- Identification of small molecule ligands for GPR83 that modulate morphine antinociception and reward.Molecular pharmacology · 2026Article
- Evaluation of Small-Molecule Binding Site Prediction Methods on Membrane-Embedded Protein Interfaces.Journal of chemical information and modeling · 2025Article
- Comparative evaluation of methods for the prediction of protein-ligand binding sites.Journal of cheminformatics · 2024Article
- LVPocket: integrated 3D global-local information to protein binding pockets prediction with transfer learning of protein structure classification.Journal of cheminformatics · 2024Article
- Article
- SiteFerret: Beyond Simple Pocket Identification in Proteins.Journal of chemical theory and computation · 2023Article
- From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches.International journal of molecular sciences · 2023Review
- In Silico Structure-Based Vaccine Design.Methods in molecular biology (Clifton, N.J.) · 2023Review
- A multilayer dynamic perturbation analysis method for predicting ligand-protein interactions.BMC bioinformatics · 2022Article
- Estimating the Similarity between Protein Pockets.International journal of molecular sciences · 2022Review
- Sequence-based prediction of protein binding regions and drug-target interactions.Journal of cheminformatics · 2022Article
- Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions.Briefings in bioinformatics · 2022Review
- PUResNet: prediction of protein-ligand binding sites using deep residual neural network.Journal of cheminformatics · 2021Article
- Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods with a Focus on FunFOLD3.Methods in molecular biology (Clifton, N.J.) · 2021Article
- An Information-Theory-Based Approach for Optimal Model Reduction of Biomolecules.Journal of chemical theory and computation · 2020Article
- A Multi-Pronged Computational Pipeline for Prioritizing Drug Target Strategies for Latent Tuberculosis.Frontiers in chemistry · 2020Article
- P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure.Journal of cheminformatics · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
unlabelledSiteHound uses Molecular Interaction Fields (MIFs) produced by EasyMIFs to identify protein structure regions that show a high propensity for interaction with ligands. The type of binding site identified depends on the probe atom used in the MIF calculation. The input to EasyMIFs is a PDB file of a protein structure; the output MIF serves as input to SiteHound, which in turn produces a list of putative binding sites. Extensive testing of SiteHound for the detection of binding sites for drug-like molecules and phosphorylated ligands has been carried out. AVAILABILITY: EasyMIFs and SiteHound executables for Linux, Mac OS X, and MS Windows operating systems are freely available for download from http://sitehound.sanchezlab.org/download.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.