ArticlePloS one2014
How structure defines affinity in protein-protein interactions.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
45 citing papers in PubMed.
- Article
- Structural ontogeny of protein-protein interactions.Science (New York, N.Y.) · 2026Article
- PPAC: Predicting Protein-Protein Affinity Changes Induced by Amino Acid Mutations Using Protein Large Language Models.ACS omega · 2025Article
- In silico prediction method for plant Nucleotide-binding leucine-rich repeat- and pathogen effector interactions.The Plant journal : for cell and molecular biology · 2025Article
- Structural recognition and stabilization of tyrosine hydroxylase by the J-domain protein DNAJC12.Nature communications · 2025Article
- Bioinformatic Resources for Exploring Human-virus Protein-protein Interactions Based on Binding Modes.Genomics, proteomics & bioinformatics · 2024Review
- DDAffinity: predicting the changes in binding affinity of multiple point mutations using protein 3D structure.Bioinformatics (Oxford, England) · 2024Article
- Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.Chemical reviews · 2024Review
- Article
- Predictive Models and Impact of Interfacial Contacts and Amino Acids on Protein-Protein Binding Affinity.ACS omega · 2024Article
- Exploring LDLR-APOB Interactions in Familial Hypercholesterolemia in the Vietnamese Population: A Protein-Protein Docking Approach.Bioinformatics and biology insights · 2024Article
- Comprehensive comparative assessment of the Arabidopsis thaliana MLO2-CALMODULIN2 interaction by various in vitro and in vivo protein-protein interaction assays.The Biochemical journal · 2023Article
- Designed Loop Extension Followed by Combinatorial Screening Confers High Specificity to a Broad Matrix MetalloproteinaseInhibitor.Journal of molecular biology · 2023Article
- Targeting Ras with protein engineering.Oncotarget · 2023Review
- Electrostatic complementarity at the interface drives transient protein-protein interactions.Scientific reports · 2023Article
- Article
- Comprehensive comparative assessment of thebioRxiv : the preprint server for biology · 2023Article
- Juno and CD9 protein network organization in oolemma of mouse oocyte.Frontiers in cell and developmental biology · 2023Article
- Structural modelling of human complement FHR1 and two of its synthetic derivatives provides insight into their in-vivo functions.Computational and structural biotechnology journal · 2023Article
- The Role of PARP1 and PAR in ATP-Independent Nucleosome Reorganisation during the DNA Damage Response.Genes · 2022Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins.
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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.