ArticlePLoS computational biology2013
Protein-protein interactions in a crowded environment: an analysis via cross-docking simulations and evolutionary information.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- SENSE-PPI reconstructs interactomes within, across, and between species at the genome scale.iScience · 2024Article
- Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.Chemical reviews · 2024Review
- Soft disorder modulates the assembly path of protein complexes.PLoS computational biology · 2022Article
- Deep Local Analysis evaluates protein docking conformations with locally oriented cubes.Bioinformatics (Oxford, England) · 2022Article
- Topsy-Turvy: integrating a global view into sequence-based PPI prediction.Bioinformatics (Oxford, England) · 2022Article
- From complete cross-docking to partners identification and binding sites predictions.PLoS computational biology · 2022Article
- An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants.Structure (London, England : 1993) · 2021Article
- Article
- Identification and visualization of protein binding regions with the ArDock server.Nucleic acids research · 2018Article
- Protein-protein interaction specificity is captured by contact preferences and interface composition.Bioinformatics (Oxford, England) · 2018Article
- Structure-based cross-docking analysis of antibody-antigen interactions.Scientific reports · 2017Article
- Non-interacting proteins may resemble interacting proteins: prevalence and implications.Scientific reports · 2017Article
- JET2 Viewer: a database of predicted multiple, possibly overlapping, protein-protein interaction sites for PDB structures.Nucleic acids research · 2017Article
- Protein social behavior makes a stronger signal for partner identification than surface geometry.Proteins · 2017Article
- Great interactions: How binding incorrect partners can teach us about protein recognition and function.Proteins · 2016Article
- Combining structure probing data on RNA mutants with evolutionary information reveals RNA-binding interfaces.Nucleic acids research · 2016Article
- Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins.Scientific reports · 2016Article
- Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions.PLoS computational biology · 2015Article
- Accurate Prediction of Docked Protein Structure Similarity.Journal of computational biology : a journal of computational molecular cell biology · 2015Article
- Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.Molecules (Basel, Switzerland) · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/
Indexed as
Identifiers
What OpenQuestion holds
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.