GENERATIVE AI FOR DE NOVO DRUG DESIGN: NEW CHALLENGES IN MOLECULE

Adilova, F.T., Davronov, R.R., Адылова, Ф.Т., Давронов, Р.Р.

Ҳисоблаш ва амалий математика муаммолари · 2024-yil

Annotatsiya

Artificial intelligence-based methods can significantly improve the traditional expen sive drug development process, given the fact that various generative models are already widely used in chemistry. Generative models for de novo drug design are focused on cre ating new biological compounds completely from scratch, which represents a promising direction in the future. The rapid development in this field, combined with the inherent complexity of the drug design process, creates difficult conditions for researchers. Within the framework of the topic of creating small molecules, we define many subtasks and applications, highlighting important datasets, benchmarks, model architecture and com paring the performance of the best models. The review presents key advances in this f ield, including the advent of quantum computing, which promises to further accelerate the application of deep QSAR to support computer-aided drug design in the field of molecules.

Maqola ma’lumotlari
MualliflarAdilova, F.T., Davronov, R.R., Адылова, Ф.Т., Давронов, Р.Р.
JurnalҲисоблаш ва амалий математика муаммолари
Nashr sanasi2024-05-22
Son2
Betlar85-98
TilRus

Kalit so‘zlar

generative models, biological compounds, small molecules, datasets, bench marks, model architecture, quantum computing, QSAR, генеративные модели, биологические соединения, малые молекулы, наборы данных, контрольные показатели, архитектура моделей, квантовые вычисления, QSAR

Ilmiy soha

Ҳисоблаш ва амалий математика муаммолари jurnalidan boshqa maqolalar

Ҳисоблаш ва амалий математика муаммолари — barcha maqolalar