ArticleNucleic acids research2010
PCRPi: Presaging Critical Residues in Protein interfaces, a new computational tool to chart hot spots in protein interfaces.
Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- PPI-hotspoteLife · 2024Article
- Inhibition of Viral Membrane Fusion by Peptides and Approaches to Peptide Design.Pathogens (Basel, Switzerland) · 2021Review
- Nabe: an energetic database of amino acid mutations in protein-nucleic acid binding interfaces.Database : the journal of biological databases and curation · 2021Article
- A cell-based screening method using an intracellular antibody for discovering small molecules targeting the translocation protein LMO2.Science advances · 2021Article
- Evaluation of Computationally Designed Peptides against TWEAK, a Cytokine of the Tumour Necrosis Factor Ligand Family.International journal of molecular sciences · 2021Article
- Review
- Hot Spots and Their Contribution to the Self-Assembly of the Viral Capsid: In Silico Prediction and Analysis.International journal of molecular sciences · 2019Article
- Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Machine Learning Approaches for Protein⁻Protein Interaction Hot Spot Prediction: Progress and Comparative Assessment.Molecules (Basel, Switzerland) · 2018Review
- Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting.Scientific reports · 2018Article
- Article
- A boosting approach for prediction of protein-RNA binding residues.BMC bioinformatics · 2017Article
- Genetic and functional characterization of disease associations explains comorbidity.Scientific reports · 2017Article
- PredPhos: an ensemble framework for structure-based prediction of phosphorylation sites.Journal of biological research (Thessalonike, Greece) · 2016Article
- Interolog interfaces in protein-protein docking.Proteins · 2015Article
- Genome-wide prediction of prokaryotic two-component system networks using a sequence-based meta-predictor.BMC bioinformatics · 2015Article
- Article
- ECMIS: computational approach for the identification of hotspots at protein-protein interfaces.BMC bioinformatics · 2014Article
- Prediction of hot spots in protein interfaces using extreme learning machines with the information of spatial neighbour residues.IET systems biology · 2014Article
- PredHS: a web server for predicting protein-protein interaction hot spots by using structural neighborhood properties.Nucleic acids research · 2014Article
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Authors and funding
4 authors.
Funding
Abstract
Protein-protein interactions (PPIs) are ubiquitous in Biology, and thus offer an enormous potential for the discovery of novel therapeutics. Although protein interfaces are large and lack defining physiochemical traits, is well established that only a small portion of interface residues, the so-called hot spot residues, contribute the most to the binding energy of the protein complex. Moreover, recent successes in development of novel drugs aimed at disrupting PPIs rely on targeting such residues. Experimental methods for describing critical residues are lengthy and costly; therefore, there is a need for computational tools that can complement experimental efforts. Here, we describe a new computational approach to predict hot spot residues in protein interfaces. The method, called Presaging Critical Residues in Protein interfaces (PCRPi), depends on the integration of diverse metrics into a unique probabilistic measure by using Bayesian Networks. We have benchmarked our method using a large set of experimentally verified hot spot residues and on a blind prediction on the protein complex formed by HRAS protein and a single domain antibody. Under both scenarios, PCRPi delivered consistent and accurate predictions. Finally, PCRPi is able to handle cases where some of the input data is either missing or not reliable (e.g. evolutionary information).
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Registered trials
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