Abstract
We give an overview of the role of “quantum-chemoinformatics” in drug development. Quantum- chemoinformatics is a data-driven chemistry using descriptors on the basis of theoretical chemistry, especially quantum chemistry (QC) and ab initio molecular dynamics (MD) simulations. We focus especially on quantum-chemoinformatics for chemical reaction design and prediction, which is one of the important processes in basic research of drug development. We start with a brief historical overview and then introduces two projects of quantum-cheminformatics. The RMap project uses QC-based chemical reaction route networks for discovery and design of new molecules and reactions. The other project is related to environmental pollution by drug molecules, a property which should be taken into account in drug design and evaluation. The last section describes our recent attempt to accelerate QC-data acquisition by utilizing a limited amount of experimental data and machine learning (ML) technology.



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