ArticleNature biotechnology2012
Three-dimensional reconstruction of protein networks provides insight into human genetic disease.
Article in Nature biotechnology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 225 papers.
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Who cites it
225 citing papers in PubMed.
- Function-based OBOC screening for the direct discovery of potent protein-protein interaction inhibitors.RSC chemical biology · 2026Article
- Phenotypic prediction of missense variants via deep contrastive learning.Nature biomedical engineering · 2026Article
- Interactome mapping in human excitatory neurons reveals novel risk genes and pathways in Alzheimer's disease.bioRxiv : the preprint server for biology · 2026Article
- Predicting interaction-specific protein-protein interaction perturbations by missense variants with MutPred-PPI.bioRxiv : the preprint server for biology · 2026Article
- Functional assessment of protein variants in structured domains by fluorescence cross-correlation spectroscopy.Scientific reports · 2026Article
- Missense mutations in intrinsically disordered protein regions link pathogenicity and phase separation.The Journal of biological chemistry · 2025Article
- Dynamic Allostery: Evolution's Double-Edged Sword in Protein Function and Disease.Journal of molecular biology · 2025Review
- Global profiling of protein complex dynamics with an experimental library of protein interaction markers.Nature biotechnology · 2025Article
- A structurally informed human protein-protein interactome reveals proteome-wide perturbations caused by disease mutations.Nature biotechnology · 2025Article
- Integrated omics identifies molecular networks of brain-body interactions of brain injury.iScience · 2025Article
- Capturing Unanticipated Drug Toxicities Using an Ensemble Machine Learning Approach.Research square · 2025Article
- Thermal Proteome Profiling Reveals Meltome Upon NLRP3 Inflammasome Activation.Molecular & cellular proteomics : MCP · 2025Article
- Challenges in bridging the gap between protein structure prediction and functional interpretation.Proteins · 2025Article
- Genetic variants associated with age-related episodic memory decline implicate distinct memory pathologies.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Uncovering cell-type-specific immunomodulatory variants and molecular phenotypes in COVID-19 using structurally resolved protein networks.Cell reports · 2024Article
- Article
- Structural analysis of genomic and proteomic signatures reveal dynamic expression of intrinsically disordered regions in breast cancer.iScience · 2024Article
- The mouse multi-organ proteome from infancy to adulthood.Nature communications · 2024Article
- Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry.Journal of proteome research · 2024Article
- Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations.bioRxiv : the preprint server for biology · 2024Article
165 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies.
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