ArticleMolecules (Basel, Switzerland)2022
Analysis of Protein-Protein Interactions for Intermolecular Bond Prediction.
Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed.
- Article
- Biochemical and physiological characterization of Aedes aegypti midgut chymotrypsin.Scientific reports · 2025Article
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
- Protein allosteric site identification using machine learning and per amino acid residue reported internal protein nanoenvironment descriptors.Computational and structural biotechnology journal · 2024Article
- Article
- Polymers for Disrupting Protein-Protein Interactions: Where Are We and Where Should We Be?Biomacromolecules · 2024Review
- Is the TCA cycle malate dehydrogenase-citrate synthase metabolon an illusion?Essays in biochemistry · 2024Review
- Cold Spot SCANNER: Colab Notebook for predicting cold spots in protein-protein interfaces.BMC bioinformatics · 2024Article
- Article
- In vitro combination effects of plant-derived quercetin with synthetic bicalutamide on prostate cancer and normal cell lines: in silico comparison.In silico pharmacology · 2024Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Protein-protein interactions often involve a complex system of intermolecular interactions between residues and atoms at the binding site. A comprehensive exploration of these interactions can help reveal key residues involved in protein-protein recognition that are not obvious using other protein analysis techniques. This paper presents and extends DiffBond, a novel method for identifying and classifying intermolecular bonds while applying standard definitions of bonds in chemical literature to explain protein interactions. DiffBond predicted intermolecular bonds from four protein complexes: Barnase-Barstar, Rap1a-raf, SMAD2-SMAD4, and a subset of complexes formed from three-finger toxins and nAChRs. Based on validation through manual literature search and through comparison of two protein complexes from the SKEMPI dataset, DiffBond was able to identify intermolecular ionic bonds and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. DiffBond predictions on bond existence were also strongly correlated with observations of Gibbs free energy change and electrostatic complementarity in mutational experiments. DiffBond can be a powerful tool for predicting and characterizing influential residues in protein-protein interactions, and its predictions can support research in mutational experiments and drug design.
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Registered trials
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