ArticlePloS one2011
Computational prediction of heme-binding residues by exploiting residue interaction network.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond.Briefings in bioinformatics · 2024Review
- Ginger ring compounds as an inhibitor of spike binding protein of alpha, beta, gamma and delta variants of SARS-CoV-2: AnNarra J · 2023Article
- Exploring the cause of the dual allosteric targeted inhibition attaching to allosteric sites enhancing SHP2 inhibition.Molecular diversity · 2022Article
- Prediction of DNA-Binding Protein-Drug-Binding Sites Using Residue Interaction Networks and Sequence Feature.Frontiers in bioengineering and biotechnology · 2022Article
- Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities.Communications biology · 2021Article
- Centrality Measures in Residue Interaction Networks to Highlight Amino Acids in Protein-Protein Binding.Frontiers in bioinformatics · 2021Article
- A Novel Interaction of Translocator Protein 18 kDa (TSPO) with NADPH Oxidase in Microglia.Molecular neurobiology · 2020Article
- SARS-CoV and SARS-CoV-2 main protease residue interaction networks change when bound to inhibitor N3.Journal of structural biology · 2020Article
- HeMoQuest: a webserver for qualitative prediction of transient heme binding to protein motifs.BMC bioinformatics · 2020Article
- Dynamical important residue network (DIRN): network inference via conformational change.Bioinformatics (Oxford, England) · 2019Article
- Modulation of Human Hsp90α Conformational Dynamics by Allosteric Ligand Interaction at the C-Terminal Domain.Scientific reports · 2019Article
- The molecular basis of transient heme-protein interactions: analysis, concept and implementation.Bioscience reports · 2019Review
- In silico prediction of novel residues involved in amyloid primary nucleation of human I56T and D67H lysozyme.BMC structural biology · 2018Article
- Network topology of NaV1.7 mutations in sodium channel-related painful disorders.BMC systems biology · 2017Article
- PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context.Scientific reports · 2016Article
- Molecular docking as a popular tool in drug design, an in silico travel.Advances and applications in bioinformatics and chemistry : AABC · 2016Review
- Classification epitopes in groups based on their protein family.BMC bioinformatics · 2015Article
- SCMHBP: prediction and analysis of heme binding proteins using propensity scores of dipeptides.BMC bioinformatics · 2014Article
- Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.Pharmacology & therapeutics · 2013Review
- Small world network strategies for studying protein structures and binding.Computational and structural biotechnology journal · 2013Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM) based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based features significantly improved the prediction performance. We also compared the residue interaction networks of heme proteins before and after heme binding and found that the topological features can well characterize the heme-binding sites of apo structures as well as those of holo structures, which led to reliable performance improvement as we applied HemeNet to predicting the binding residues of proteins in the heme-free state. HemeNet web server is freely accessible at http://mleg.cse.sc.edu/hemeNet/.
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