ArticleScientific reports2016
Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis.
Article in Scientific reports, 2016. 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 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Network analysis of correlated conformational dynamics across the evolution of influenza A virus NS1.bioRxiv : the preprint server for biology · 2026Article
- RinPy, a Python Package for Residue Interaction Network Model to Analyze Protein Structures and Predict Ligand Binding Sites.Journal of chemical information and modeling · 2026Article
- TRAMbio: a flexible python package for graph rigidity analysis of macromolecules.BMC bioinformatics · 2025Article
- Evolution of the conformational ensemble and allosteric networks of apoptotic caspases in chordates.The Biochemical journal · 2025Article
- Article
- Network analysis uncovers the communication structure of SARS-CoV-2 spike protein identifying sites for immunogen design.iScience · 2023Article
- Repurposing of FDA-approved drugs against active site and potential allosteric drug-binding sites of COVID-19 main protease.Proteins · 2021Article
- Role of a high centrality residue in protein dynamics and thermal stability.Journal of structural biology · 2021Article
- Protein conformational switch discerned via network centrality properties.Computational and structural biotechnology journal · 2021Article
- A graph-based approach identifies dynamic H-bond communication networks in spike protein S of SARS-CoV-2.Journal of structural biology · 2020Article
- Exploring allosteric communication in multiple states of the bacterial ribosome using residue network analysis.Turkish journal of biology = Turk biyoloji dergisi · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Amino acid networks (AANs) abstract the protein structure by recording the amino acid contacts and can provide insight into protein function. Herein, we describe a novel AAN construction technique that employs the rigidity analysis tool, FIRST, to build the AAN, which we refer to as the residue geometry network (RGN). We show that this new construction can be combined with network theory methods to include the effects of allowed conformal motions and local chemical environments. Importantly, this is done without costly molecular dynamics simulations required by other AAN-related methods, which allows us to analyse large proteins and/or data sets. We have calculated the centrality of the residues belonging to 795 proteins. The results display a strong, negative correlation between residue centrality and the evolutionary rate. Furthermore, among residues with high closeness, those with low degree were particularly strongly conserved. Random walk simulations using the RGN were also successful in identifying allosteric residues in proteins involved in GPCR signalling. The dynamic function of these residues largely remain hidden in the traditional distance-cutoff construction technique. Despite being constructed from only the crystal structure, the results in this paper suggests that the RGN can identify residues that fulfil a dynamical function.
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