Article Info Vol. 2. Issue 1 (2023)

Open Access Received:   |   Accepted:   |   Published:

DESIGN OF NEW DRUGS BASED ON ARTIFICIAL INTELLIGENCE: THE POSSIBILITIES OF LANGUAGE MODELS

Adilova F.T., Davronov R.R.

V.I. Romanovsky Institute of Mathematics of the Academy of Sciences of the Republic of Uzbekistan

Abstract. Generative deep learning accelerates de novo drug design by enabling the creation of molecules with desired properties on demand. Chemical language models that generate new molecules in the form of chains have proved particularly successful. It is expected that, due to advances in natural language processing techniques and interdisciplinary collaboration, chemical language models will become increasingly relevant in drug design. This mini-review provides an overview of the current state of chemical language models for de novo design, as well as analyzes current limitations, challenges and opportunities. In the future, chemical language models will have a wider application. Specially developed molecular solutions have the potential to revolutionize fields such as medicine and materials science


Key words. computer-aided drug design, drug discovery, artificial intelligence, chemical language models


DOI: http://uzpolymerjournal.com/articles/article.php?id=230105


*Corresponding author: Adilova F.T., V.I. Romanovsky Institute of Mathematics of the Academy of Sciences of the Republic of Uzbekistan

Citation: Adilova F.T., Davronov R.R., DESIGN OF NEW DRUGS BASED ON ARTIFICIAL INTELLIGENCE: THE POSSIBILITIES OF LANGUAGE MODELS. Uzbekistan Journal of Polymers, Vol. 2(1) 2023: pp.56-62. DOI: http://uzpolymerjournal.com/articles/article.php?id=230105

©2023 Uzbekistan Journal of Polymers

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Uzbekistan Journal of Polymers Vol. 1. Issue 1. (2022) 220101

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