Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Babbitt, Gregory A., Fokoue, Ernest P., Srivastava, Harsh R., Callahan, Breanna, Rajendran, Madhusudan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
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
Descripción
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).