ArticleJournal of computational chemistry2016
Flexibility-rigidity index for protein-nucleic acid flexibility and fluctuation analysis.
Article in Journal of computational chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 24 citations in OpenAlex.
- Predicting protein-nucleic acid flexibility using persistent sheaf Laplacians.Physical chemistry chemical physics : PCCP · 2026Article
- Machine Learning Approaches for Interpretable Antibody Property Prediction Using Structural Data.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Structural analysis of antigenic variation and adaptive evolution of the H5N1 neuraminidase gene.PLoS computational biology · 2026Article
- A review of mathematical representations of biomolecular data.Physical chemistry chemical physics : PCCP · 2020Review
- Atom-specific persistent homology and its application to protein flexibility analysis.Computational and mathematical biophysics · 2020Article
- Blind prediction of protein B-factor and flexibility.The Journal of chemical physics · 2018Article
- Advances in coarse-grained modeling of macromolecular complexes.Current opinion in structural biology · 2018Review
- Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones.Scientific reports · 2018Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Protein-nucleic acid complexes are important for many cellular processes including the most essential functions such as transcription and translation. For many protein-nucleic acid complexes, flexibility of both macromolecules has been shown to be critical for specificity and/or function. The flexibility-rigidity index (FRI) has been proposed as an accurate and efficient approach for protein flexibility analysis. In this article, we introduce FRI for the flexibility analysis of protein-nucleic acid complexes. We demonstrate that a multiscale strategy, which incorporates multiple kernels to capture various length scales in biomolecular collective motions, is able to significantly improve the state of art in the flexibility analysis of protein-nucleic acid complexes. We take the advantage of the high accuracy and O(N) computational complexity of our multiscale FRI method to investigate the flexibility of ribosomal subunits, which are difficult to analyze by alternative approaches. An anisotropic FRI approach, which involves localized Hessian matrices, is utilized to study the translocation dynamics in an RNA polymerase.
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