ArticleFrontiers in molecular biosciences2022
Integrative Conformational Ensembles of Sic1 Using Different Initial Pools and Optimization Methods.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Topological Entanglement in Intrinsically Disordered Proteins: Sequence, Structural, and Functional Determinants.The journal of physical chemistry. B · 2026Article
- In Search of Shape in the Unshaped: Constructing Ensembles of Intrinsically Disordered Proteins.Biophysics reviews · 2026Article
- Topological Entanglement in Intrinsically Disordered Proteins: Sequence, Structural, and Functional Determinants.bioRxiv : the preprint server for biology · 2026Article
- Structural and Functional Relevance of Charge-Based Transient Interactions inside Intrinsically Disordered Proteins.ACS physical chemistry Au · 2025Article
- Structural and Functional Relevance of Charge Based Transient Interactions inside Intrinsically Disordered Proteins.bioRxiv : the preprint server for biology · 2024Article
- Delineating Structural Propensities of the 4E-BP2 Protein via Integrative Modeling and Clustering.The journal of physical chemistry. B · 2023Article
- Interpreting Transient Interactions of Intrinsically Disordered Proteins.The journal of physical chemistry. B · 2023Article
- Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery.Biomolecules · 2023Review
- Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology.Biomolecules · 2023Review
- Incorporation of DThe journal of physical chemistry. B · 2022Article
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Abstract
Intrinsically disordered proteins play key roles in regulatory protein interactions, but their detailed structural characterization remains challenging. Here we calculate and compare conformational ensembles for the disordered protein Sic1 from yeast, starting from initial ensembles that were generated either by statistical sampling of the conformational landscape, or by molecular dynamics simulations. Two popular, yet contrasting optimization methods were used, ENSEMBLE and Bayesian Maximum Entropy, to achieve agreement with experimental data from nuclear magnetic resonance, small-angle X-ray scattering and single-molecule Förster resonance energy transfer. The comparative analysis of the optimized ensembles, including secondary structure propensity, inter-residue contact maps, and the distributions of hydrogen bond and pi interactions, revealed the importance of the physics-based generation of initial ensembles. The analysis also provides insights into designing new experiments that report on the least restrained features among the optimized ensembles. Overall, differences between ensembles optimized from different priors were greater than when using the same prior with different optimization methods. Generating increasingly accurate, reliable and experimentally validated ensembles for disordered proteins is an important step towards a mechanistic understanding of their biological function and involvement in various diseases.
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