Bioactive structures for inhibitors of Candida auris polymerase enzyme by artificial intelligence

Present new bioactive compounds, created by De novo Drug Design and artificial intelligence (AI), as possible inhibitors of polymerase. MolAICal's AI module was configured to identify FDA-approved molecular fragments with therapeutic effectiveness against polymerase, where the model with optimi...

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Bibliographic Details
Published in:	Future medicinal chemistry Vol. 17; no. 8; p. 869
Main Authors:	Pinto, Francisco Das Chagas Lima, Cabongo, Sadrack Queque, João, Pedro Paulino, Lima, Maria Do Socorro Pereira Costa, Paiva, Maria Mabelle Pereira Costa, Madureira, Junilson Martinho Canjanja, Caluaco, Bernardino Joaquim, Colares, Regilany Paulo, Neto, Moises Maia, Dos Santos, Hélcio Silva, Marinho, Emmanuel Silva, da Fonseca, Aluísio Marques
Format:	Journal Article
Language:	English
Published:	England 18.04.2025
Subjects:	Antifungal Agents - chemistry Antifungal Agents - pharmacology Artificial Intelligence Candida - drug effects Candida - enzymology Drug Design Enzyme Inhibitors - chemistry Enzyme Inhibitors - pharmacology Humans Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure deep learning molecular docking molecular dynamics Protease superfungo
ISSN:	1756-8927, 1756-8927
Online Access:	Get more information
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