Abstract
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).
| Original language | English |
|---|---|
| Article number | 101194 |
| Journal | STAR Protocols |
| Volume | 3 |
| Issue number | 1 |
| DOIs | |
| State | Published - 18 Mar 2022 |
| Externally published | Yes |
Keywords
- Bioinformatics
- Biophysics
- Computer sciences
- Evolutionary biology
- Protein Biochemistry
- Structural Biology
- Systems biology
Fingerprint
Dive into the research topics of 'Statistical machine learning for comparative protein dynamics with the DROIDS/maxDemon software pipeline'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver