Machine learning accelerates MD-based binding pose prediction between ligands and proteins.
Kei TerayamaHiroaki IwataMitsugu ArakiYasushi OkunoKoji TsudaPublished in: Bioinform. (2018)
Keyphrases
- drug design
- machine learning
- subcellular localization
- hiv protease
- prediction accuracy
- protein structure prediction
- mhc class ii
- protein protein interactions
- pose estimation
- protein secondary structure
- prediction model
- protein sequences
- computational methods
- protein secondary structure prediction
- protein interaction
- predicting protein
- contact map
- protein function prediction
- machine learning algorithms
- dna binding
- machine learning methods
- protein classification
- computational biology
- statistical methods
- feature selection
- computer vision
- learning algorithm
- facial expressions
- protein protein interaction networks
- sequence analysis
- protein function
- protein interaction networks
- functional modules
- drug discovery
- protein structure
- contact maps
- binding peptides
- high precision