ArticleNucleic acids research2014
PredHS: a web server for predicting protein-protein interaction hot spots by using structural neighborhood properties.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Surf2Spot: a surface-informed geometry-aware model for predicting partner-independent binder and nanobody design hotspots.Briefings in bioinformatics · 2026Article
- Predicting interacting hotspots for nanobodies' binding using triplets of residues.Protein science : a publication of the Protein Society · 2025Article
- PPI-hotspoteLife · 2024Article
- Computational Methods and Deep Learning for Elucidating Protein Interaction Networks.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Rational design of a potent macrocyclic peptide inhibitor targeting the PD-1/PD-L1 protein-protein interaction.RSC advances · 2021Article
- Rapid prediction of crucial hotspot interactions for icosahedral viral capsid self-assembly by energy landscape atlasing validated by mutagenesis.PLoS computational biology · 2020Article
- Computationally identifying hot spots in protein-DNA binding interfaces using an ensemble approach.BMC bioinformatics · 2020Article
- Support Vector Machine-Based Schizophrenia Classification Using Morphological Information from Amygdaloid and Hippocampal Subregions.Brain sciences · 2020Article
- Article
- Predicting and Experimentally Validating Hot-Spot Residues at Protein-Protein Interfaces.ACS chemical biology · 2019Article
- XGBPRH: Prediction of Binding Hot Spots at Protein⁻RNA Interfaces Utilizing Extreme Gradient Boosting.Genes · 2019Article
- Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing.Methods in molecular biology (Clifton, N.J.) · 2019Article
- PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine.BMC bioinformatics · 2018Article
- Machine Learning Approaches for Protein⁻Protein Interaction Hot Spot Prediction: Progress and Comparative Assessment.Molecules (Basel, Switzerland) · 2018Review
- Branched late-steps of the cytosolic iron-sulphur cluster assembly machinery of Trypanosoma brucei.PLoS pathogens · 2018Article
- Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting.Scientific reports · 2018Article
- EPO does not promote interaction between the erythropoietin and beta-common receptors.Scientific reports · 2018Article
- Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery.Molecules (Basel, Switzerland) · 2018Review
- SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins.International journal of molecular sciences · 2018Article
- Virtual screening for inhibitors of the human TSLP:TSLPR interaction.Scientific reports · 2017Article
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Authors and funding
6 authors.
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Abstract
Identifying specific hot spot residues that contribute significantly to the affinity and specificity of protein interactions is a problem of the utmost importance. We present an interactive web server, PredHS, which is based on an effective structure-based hot spot prediction method. The PredHS prediction method integrates many novel structural and energetic features with two types of structural neighborhoods (Euclidian and Voronoi), and combines random forest and sequential backward elimination algorithms to select an optimal subset of features. PredHS achieved the highest performance identifying hot spots compared with other state-of-the-art methods, as benchmarked by using an independent experimentally verified dataset. The input to PredHS is protein structures in the PDB format with at least two chains that form interfaces. Users can visualize their predictions in an interactive 3D viewer and download the results as text files. PredHS is available at http://www.predhs.org.
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