Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins.

Abstract

Motivation Fast and accurate prediction of protein-ligand binding structures is indispensable for structure-based drug design (SBDD) and accurate estimation of binding free energy of drug candidate molecules in drug discovery. Recently, accurate pose prediction methods based on short-MD simulations such as MM-PBSA and MM-GBSA among generated docking poses… (More)
DOI: 10.1093/bioinformatics/btx638

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Cite this paper

@article{Terayama2017MachineLA, 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}, journal={Bioinformatics}, year={2017} }