ReviewBriefings in bioinformatics2015
Predicting protein interface residues using easily accessible on-line resources.
Review in Briefings in bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
25 citing papers in PubMed.
- Phosphorylation landscape of dengue virus proteins and their implications in protein-protein interactions.PloS one · 2026Article
- N-Terminal Metal-Binding Domain of Arabidopsis IBR5 Is Important for Its in Planta Functions.International journal of molecular sciences · 2025Article
- DescribePROT Database of Residue-Level Protein Structure and Function Annotations.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Evolution and Expression of the Meprin and TRAF Homology Domain-Containing Gene Family in Solanaceae.International journal of molecular sciences · 2023Article
- Complementarity of the residue-level protein function and structure predictions in human proteins.Computational and structural biotechnology journal · 2022Article
- Dynamic, but Not Necessarily Disordered, Human-Virus Interactions Mediated through SLiMs in Viral Proteins.Viruses · 2021Review
- DescribePROT: database of amino acid-level protein structure and function predictions.Nucleic acids research · 2021Article
- Inter-protein residue covariation information unravels physically interacting protein dimers.BMC bioinformatics · 2020Article
- SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences.Bioinformatics (Oxford, England) · 2019Article
- The adaptor protein Ste50 directly modulates yeast MAPK signaling specificity through differential connections of its RA domain.Molecular biology of the cell · 2019Article
- Interactome of Glyceraldehyde-3-Phosphate Dehydrogenase Points to the Existence of Metabolons inFrontiers in microbiology · 2019Article
- Pattern to Knowledge: Deep Knowledge-Directed Machine Learning for Residue-Residue Interaction Prediction.Scientific reports · 2018Article
- Identification and visualization of protein binding regions with the ArDock server.Nucleic acids research · 2018Article
- Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.BMC bioinformatics · 2018Article
- Protein-protein interaction specificity is captured by contact preferences and interface composition.Bioinformatics (Oxford, England) · 2018Article
- Interactome INSIDER: a structural interactome browser for genomic studies.Nature methods · 2018Article
- Structure-based prediction of ligand-protein interactions on a genome-wide scale.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Different protein-protein interface patterns predicted by different machine learning methods.Scientific reports · 2017Article
- DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues.Nucleic acids research · 2017Article
- Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
It has been more than a decade since the completion of the Human Genome Project that provided us with a complete list of human proteins. The next obvious task is to figure out how various parts interact with each other. On that account, we review 10 methods for protein interface prediction, which are freely available as web servers. In addition, we comparatively evaluate their performance on a common data set comprising different quality target structures. We find that using experimental structures and high-quality homology models, structure-based methods outperform those using only protein sequences, with global template-based approaches providing the best performance. For moderate-quality models, sequence-based methods often perform better than those structure-based techniques that rely on fine atomic details. We note that post-processing protocols implemented in several methods quantitatively improve the results only for experimental structures, suggesting that these procedures should be tuned up for computer-generated models. Finally, we anticipate that advanced meta-prediction protocols are likely to enhance interface residue prediction. Notwithstanding further improvements, easily accessible web servers already provide the scientific community with convenient resources for the identification of protein-protein interaction sites.
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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.