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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Veröffentlicht in:	Future medicinal chemistry Jg. 17; H. 8; S. 869
Hauptverfasser:	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
Sprache:	Englisch
Veröffentlicht:	England 18.04.2025
Schlagworte:	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-Zugang:	Weitere Angaben
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