ArticleBioinformatics (Oxford, England)2019
Insights on protein thermal stability: a graph representation of molecular interactions.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed, 102 citations in OpenAlex.
- Exploring proteins and protein-ligand complexes through residue interaction networks.Nature protocols · 2026Review
- Advances and opportunities for computational interrogation of plant proteins.The Plant journal : for cell and molecular biology · 2026Review
- Preventing Pathogenic Dimerization in a Misfolded Antibody Light Chain through the Design of an Inhibitory Peptide.The journal of physical chemistry. B · 2026Article
- Molecular Cloning, Optimization of Expression and Functional Characterization of the Global Transcriptional Regulator MosR (Rv0348) of Mycobacterium tuberculosis.Applied biochemistry and biotechnology · 2025Article
- Bioinformatic Analysis of the Leptin-Ob-R Interface: Structural Modeling, Thermodynamic Profiling, and Stability in Diverse Microenvironments.International journal of molecular sciences · 2025Article
- Interplay of protein fluctuation and associated water dynamics in osmolyte-induced stabilization.Biophysical journal · 2025Article
- Multi-step pathway engineering in probioticMetabolic engineering communications · 2025Article
- Discovery andACS omega · 2025Article
- Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.Journal of chemical information and modeling · 2025Article
- Computer-aided engineering of stabilized fibroblast growth factor 21.Computational and structural biotechnology journal · 2024Article
- Osmolyte-induced protein stability changes explained by graph theory.Computational and structural biotechnology journal · 2024Article
- Revealing SARS-CoV-2 MComputational and structural biotechnology journal · 2024Article
- Using residue interaction networks to understand protein function and evolution and to engineer new proteins.Current opinion in structural biology · 2024Review
- Prediction of mutation-induced protein stability changes based on the geometric representations learned by a self-supervised method.BMC bioinformatics · 2024Article
- Fabrication and characterization of polyvinyl alcohol-chitosan composite nanofibers for carboxylesterase immobilization to enhance the stability of the enzyme.Scientific reports · 2024Article
- Rheostatic contributions to protein stability can obscure a position's functional role.Protein science : a publication of the Protein Society · 2024Article
- Molecular Mechanisms Involved in the B Cell Growth and Clonogenic Activity of HIV-1 Matrix Protein p17 Variants.Viruses · 2024Article
- High-throughput system for the thermostability analysis of proteins.Protein science : a publication of the Protein Society · 2024Article
- Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.Chemical reviews · 2024Review
- Cellular and epigenetic perspective of protein stability and its implications in the biological system.Epigenomics · 2024Review
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationUnderstanding the molecular mechanisms of thermal stability is a challenge in protein biology. Indeed, knowing the temperature at which proteins are stable has important theoretical implications, which are intimately linked with properties of the native fold, and a wide range of potential applications from drug design to the optimization of enzyme activity.
resultsHere, we present a novel graph-theoretical framework to assess thermal stability based on the structure without any a priori information. In this approach we describe proteins as energy-weighted graphs and compare them using ensembles of interaction networks. Investigating the position of specific interactions within the 3D native structure, we developed a parameter-free network descriptor that permits to distinguish thermostable and mesostable proteins with an accuracy of 76% and area under the receiver operating characteristic curve of 78%. AVAILABILITY AND IMPLEMENTATION: Code is available upon request to edoardo.milanetti@uniroma1.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.