Machine learning accelerates MD-based binding pose prediction between ligands and proteins

@inproceedings{Terayama2018MachineLA,
  title={Machine learning accelerates MD-based binding pose prediction between ligands and proteins},
  author={Kei Terayama and Hiroaki Iwata and Mitsugu Araki and Yasushi Okuno and Koji Tsuda},
  booktitle={Bioinformatics},
  year={2018}
}
Motivation Fast and accurate prediction of protein-ligand binding structures is indispensable for structure-based drug design and accurate estimation of binding free energy of drug candidate molecules in drug discovery. Recently, accurate pose prediction methods based on short Molecular Dynamics (MD) simulations, such as MM-PBSA and MM-GBSA, among generated… CONTINUE READING