Bioactive structures for inhibitors of Candida auris polymerase enzyme by artificial intelligence
Francisco Das Chagas Lima Pinto1, Sadrack Queque Cabongo2, Pedro Paulino João2
1Sociobiodiversity and Sustainable Technologies - MASTS, Institute of Engineering and Sustainable Development, University of International Integration of Afro-Brazilian Lusophony, Acarape-CE, Brazil.
Aims:
Present new bioactive compounds, created by De novo Drug Design and artificial intelligence (AI), as possible inhibitors of C. auris polymerase.
Materials & Methods:
MolAICal's AI module was configured to identify FDA-approved molecular fragments with therapeutic effectiveness against C. auris polymerase, where the model with optimized synthetic accessibility and structural complexity was subjected to docking and molecular dynamics simulations and pharmacokinetic prediction.
Results:
Among 1,722 new forms, the Hit-960 compound stood out for its high bioaffinity and stability, with a binding energy of -9.12 kcal/mol and 75% synthetic accessibility.
Conclusions:
Clinical studies are recommended to test its efficacy, contributing to the development of new treatments for C. auris infections.
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