ArticleProteins2013
Predicting permanent and transient protein-protein interfaces.
Article in Proteins, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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
23 citing papers in PubMed, 57 citations in OpenAlex.
- Structural basis for HIV-1 Rev recognition by the histone chaperone human Nap1.The Journal of biological chemistry · 2026Article
- Beyond contacts: The important role of the support region in protein complex assembly.Protein science : a publication of the Protein Society · 2026Article
- Systematic investigation of machine learning on limited data: A study on predicting protein-protein binding strength.Computational and structural biotechnology journal · 2024Article
- Electrostatic complementarity at the interface drives transient protein-protein interactions.Scientific reports · 2023Article
- Prediction of transient and permanent protein interactions using AI methods.Bioinformation · 2023Article
- Fast cross-linking by DOPA2 promotes the capturing of a stereospecific protein complex over nonspecific encounter complexes.Biophysics reports · 2022Article
- Are transient protein-protein interactions more dispensable?PLoS computational biology · 2022Article
- LZerD webserver for pairwise and multiple protein-protein docking.Nucleic acids research · 2021Article
- LZerD Protein-Protein Docking Webserver Enhanced WithFrontiers in molecular biosciences · 2021Review
- Structural analysis of ACE2 variant N720D demonstrates a higher binding affinity to TMPRSS2.Life sciences · 2020Article
- Article
- Delayed Comparison and Apriori Algorithm (DCAA): A Tool for Discovering Protein-Protein Interactions From Time-Series Phosphoproteomic Data.Frontiers in molecular biosciences · 2020Article
- Building Bridges Between Structural and Network-Based Systems Biology.Molecular biotechnology · 2019Review
- Using Peptidomimetics and Constrained Peptides as Valuable Tools for Inhibiting Protein⁻Protein Interactions.Molecules (Basel, Switzerland) · 2018Review
- From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.EURASIP journal on bioinformatics & systems biology · 2017Review
- DynaFace: Discrimination between Obligatory and Non-obligatory Protein-Protein Interactions Based on the Complex's Dynamics.PLoS computational biology · 2015Article
- Dimeric interactions and complex formation using direct coevolutionary couplings.Scientific reports · 2015Article
- Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.BMC bioinformatics · 2015Article
- Algorithmic approaches to protein-protein interaction site prediction.Algorithms for molecular biology : AMB · 2015Article
- A functional feature analysis on diverse protein-protein interactions: application for the prediction of binding affinity.Journal of computer-aided molecular design · 2014Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Protein-protein interactions (PPIs) are involved in diverse functions in a cell. To optimize functional roles of interactions, proteins interact with a spectrum of binding affinities. Interactions are conventionally classified into permanent and transient, where the former denotes tight binding between proteins that result in strong complexes, whereas the latter compose of relatively weak interactions that can dissociate after binding to regulate functional activity at specific time point. Knowing the type of interactions has significant implications for understanding the nature and function of PPIs. In this study, we constructed amino acid substitution models that capture mutation patterns at permanent and transient type of protein interfaces, which were found to be different with statistical significance. Using the substitution models, we developed a novel computational method that predicts permanent and transient protein binding interfaces (PBIs) in protein surfaces. Without knowledge of the interacting partner, the method uses a single query protein structure and a multiple sequence alignment of the sequence family. Using a large dataset of permanent and transient proteins, we show that our method, BindML+, performs very well in protein interface classification. A very high area under the curve (AUC) value of 0.957 was observed when predicted protein binding sites were classified. Remarkably, near prefect accuracy was achieved with an AUC of 0.991 when actual binding sites were classified. The developed method will be also useful for protein design of permanent and transient PBIs.
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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.