ArticleProteins2011
Characterization of PDZ domain-peptide interaction interface based on energetic patterns.
Article in Proteins, 2011. 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 6 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
6 citing papers in PubMed.
- Molecular basis of Tick Born encephalitis virus NS5 mediated subversion of apico-basal cell polarity signalling.The Biochemical journal · 2022Article
- Systematic Modeling, Prediction, and Comparison of Domain-Peptide Affinities: Does it Work Effectively With the Peptide QSAR Methodology?Frontiers in genetics · 2021Article
- Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery.Scientific reports · 2016Article
- MIEC-SVM: automated pipeline for protein peptide/ligand interaction prediction.Bioinformatics (Oxford, England) · 2016Article
- Identification of methyllysine peptides binding to chromobox protein homolog 6 chromodomain in the human proteome.Molecular & cellular proteomics : MCP · 2013Article
- Characterization of small molecule binding. I. Accurate identification of strong inhibitors in virtual screening.Journal of chemical information and modeling · 2013Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
PDZ domain is one of the abundant modular domains that recognize short peptide sequences to mediate protein-protein interactions. To decipher the binding specificity of PDZ domain, we analyzed the interactions between 11 mouse PDZ domains and 217 [corrected] peptides using a method called MIEC-SVM, which energetically characterizes the domain-peptide interaction using molecular interaction energy components (MIECs) and predicts binding specificity using support vector machine (SVM). Cross-validation and leave-one-domain-out test showed that the MIEC-SVM using all 44 PDZ-peptide residue pairs at the interaction interface outperformed the sequence-based methods in the literature. A further feature (residue pair) selection procedure illustrated that 16 residue pairs were uninformative to the binding specificity, even though they contributed significantly (~50%) to the binding energy. If only using the 28 informative residue pairs, the performance of the MIEC-SVM on predicting the PDZ binding specificity was significantly improved. This analysis suggests that the informative and uninformative residue interactions between the PDZ domain and the peptide may represent those contributing to binding specificity and affinity, respectively. We performed additional structural and energetic analyses to shed light on understanding how the PDZ-peptide recognition is established. The success of the MIEC-SVM method on PDZ domains in this study and SH3 domains in our previous studies illustrates its generality on characterizing protein-peptide interactions and understanding protein recognition from a structural and energetic viewpoint.
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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.