ArticleNature2012
Structure-based prediction of protein-protein interactions on a genome-wide scale.
Article in Nature, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 335 papers, 1 of them a synthesis that pooled it.
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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
335 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advances in the Application of Protein Language Modeling for Nucleic Acid Protein Binding Site Prediction.Genes · 2024Pooled it
- PrePPI - Structure-based Prediction of Protein-protein Interactomes and Networks.Journal of molecular biology · 2026Article
- DyProL: Dynamic Ensemble Representation Learning for Protein-Nucleic Acid Binding Site Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- SoPPIs: a highly parallelized protein-protein-interaction screening method in prokaryotic and eukaryotic hosts.Nucleic acids research · 2026Article
- xBind: an integrated webserver for large language model-enabled cross-molecular protein binding site prediction.Nucleic acids research · 2026Article
- A tri-modal contrastive learning framework for protein representation learning.Cell reports methods · 2026Article
- Proteome-wide prediction of interactions between structured domains and peptide motifs reveals functionally coherent subnetworks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks.Nature communications · 2026Article
- Exploring neural networks to uncover information-richer features for protein interaction prediction.European biophysics journal : EBJ · 2026Article
- Causal modeling reveals cell-cell communication dynamics in the tumor microenvironment during anti-PD-1 therapy in breast cancer patients.Briefings in bioinformatics · 2026Article
- Approximate Bayesian inference of directed acyclic graphs in biology with flexible priors on edge states.PLoS computational biology · 2026Article
- Accurate Identification of Protein Binding Sites for All Drug Modalities Using ALLSites.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Dual Cross-Attention Network for Hierarchical Feature Fusion in Protein-Protein Interaction Prediction.Computational and structural biotechnology journal · 2026Article
- Enzyme Assemblies in Nucleotide Metabolism: Structure, Regulation, and Disease Implications.Advances in experimental medicine and biology · 2026Review
- How Klebsiella pneumoniae controls its virulence.PLoS pathogens · 2025Review
- MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models.BMC biology · 2025Article
- Capturing Unanticipated Drug Toxicities Using an Ensemble Machine Learning Approach.Research square · 2025Article
- DensePPI-2: a bio-inspired update for sequence-based PPI prediction leveraging mutation rates.Briefings in bioinformatics · 2025Article
- Article
- Negative sampling strategies impact the prediction of scale-free biomolecular network interactions with machine learning.BMC biology · 2025Article
275 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on byPredicting PPIs.2012
- Erratum issued
Authors and funding
13 authors.
Funding
Abstract
The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. Much of our present knowledge derives from high-throughput techniques such as the yeast two-hybrid assay and affinity purification, as well as from manual curation of experiments on individual systems. A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein-protein interactions (PPIs). Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages. Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence. Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human. Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins.
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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.