AJOU Central Library Repository: Toward 3D Structure Augmented Deep Molecular Generation

Graduate School of Ajou University Department of Artificial Intelligence 3. Theses(Master)

Toward 3D Structure Augmented Deep Molecular Generation

Alternative Abstract: Which molecular generation method is best for large molecular generations? Finding a good lead molecule is an important task in drug discovery. Recently several deep graph generative models have been developed for generating novel molecules that can be further tested for synthesizability in the drug development process. Most of the developed models are trained on small molecules with a maximum length of thirty. However, there is a need for the generation of larger molecules. We tested six recently proposed graph neural network-based molecular generation methods on their large molecular generation performance using two datasets from the LigandBox database, which contain larger molecules than typically used ZINC250k and QM9 datasets. In addition, we propose a modified model using 3D coordinate information of molecules and evaluate this model together with recent models. We use twelve evaluation measures to evaluate the quality of the generated molecules, including stability measures such as logP values and QEDs.

Appears in Collections:: Graduate School of Ajou University > Department of Artificial Intelligence > 3. Theses(Master)

qrcode

AJOU Central Library Repository는 국립중앙도서관 OAK 보급사업으로 구축되었습니다.