ArticlePLoS computational biology2017
Conformational diversity analysis reveals three functional mechanisms in proteins.
Article in PLoS computational biology, 2017. 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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21 citing papers in PubMed.
- Disentangling coevolutionary constraints for modeling protein conformational heterogeneity.Communications chemistry · 2026Article
- Effects of acetylation on human insulin structure, and dynamics at different temperatures: A molecular dynamics simulation study.Journal of biosciences · 2026Article
- Water Migration through Enzyme Tunnels Is Sensitive to the Choice of Explicit Water Model.Journal of chemical information and modeling · 2025Article
- Reinforcing Tunnel Network Exploration in Proteins Using Gaussian Accelerated Molecular Dynamics.Journal of chemical information and modeling · 2024Article
- Regulation of Human Sortilin Alternative Splicing by Glucagon-like Peptide-1 (GLP1) in Adipocytes.International journal of molecular sciences · 2023Article
- Easy Not Easy: Comparative Modeling with High-Sequence Identity Templates.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A multilayer dynamic perturbation analysis method for predicting ligand-protein interactions.BMC bioinformatics · 2022Article
- Structure and dynamics of membrane protein in SARS-CoV-2.Journal of biomolecular structure & dynamics · 2022Article
- Identification of Sortilin Alternatively Spliced Variants in Mouse 3T3L1 Adipocytes.International journal of molecular sciences · 2021Article
- Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies.Computational and structural biotechnology journal · 2021Article
- "Protein" no longer means what it used to.Current research in structural biology · 2021Review
- Exploring conformational preferences of proteins: ionic liquid effects on the energy landscape of avidin.Chemical science · 2020Article
- Network analysis of dynamically important residues in protein structures mediating ligand-binding conformational changes.European biophysics journal : EBJ · 2019Article
- Coarse-grain simulations on NMR conformational ensembles highlight functional residues in proteins.Journal of the Royal Society, Interface · 2019Article
- Computer aided analysis of disease linked protein networks.Bioinformation · 2019Article
- P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure.Journal of cheminformatics · 2018Article
- Ensemble allosteric model: energetic frustration within the intrinsically disordered glucocorticoid receptor.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Review
- In silico mutational analysis and identification of stability centers in human interleukin-4.Molecular biology research communications · 2018Article
- Large scale analysis of protein conformational transitions from aqueous to non-aqueous media.BMC bioinformatics · 2018Article
- Ensemblator v3: Robust atom-level comparative analyses and classification of protein structure ensembles.Protein science : a publication of the Protein Society · 2018Article
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7 authors.
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Abstract
Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call "rigid" (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.
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