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Statistical machine learning for comparative protein dynamics with the DROIDS/maxDemon software pipeline
Comparative analysis of protein structure or sequence alignments often ignores the protein dynamics and function. We offer a graphical user interface to a computing pipeline, complete with molecular visualization, enabling the biophysical simulation and statistical comparison of two-state functional...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888980/ https://www.ncbi.nlm.nih.gov/pubmed/35252883 http://dx.doi.org/10.1016/j.xpro.2022.101194 |
Sumario: | Comparative analysis of protein structure or sequence alignments often ignores the protein dynamics and function. We offer a graphical user interface to a computing pipeline, complete with molecular visualization, enabling the biophysical simulation and statistical comparison of two-state functional protein dynamics (i.e., single unbound state vs. complex with a ligand, DNA, or protein). We utilize multi-agent machine learning classifiers to identify functionally conserved dynamic motions and compare them in genetic or drug-class variants. For complete details on the use and execution of this profile, please refer to Babbitt et al. (2020b, 2020a, 2018) and Rynkiewicz et al. (2021). |
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