ClustENMD: efficient sampling of biomolecular conformational space at atomic resolution
| Autor: | Pemra Doruker, Burak Tevfik Kaynak, She Zhang, Ivet Bahar |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Statistics and Probability AcademicSubjects/SCI01060 Computer science 01 natural sciences Biochemistry Computational science 03 medical and health sciences Molecular dynamics 0103 physical sciences MIT License Cluster analysis Molecular Biology 010304 chemical physics business.industry Sampling (statistics) Applications Notes Structural Bioinformatics Automation Computer Science Applications Visualization Computational Mathematics 030104 developmental biology Computational Theory and Mathematics Table (database) business Subspace topology |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/btab496 |
| Popis: | Summary Efficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe a new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model for deformations along global modes, followed by clustering and short molecular dynamics simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace. Availability and implementation ClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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