Harnessing Machine Learning to Uncover Hidden Patterns in Azole-Resistant CYP51/ERG11 Proteins.

ABSTRACT: Fungal resistance is a public health concern due to the limited availability of antifungal resources and the complexities associated with treating persistent fungal infections. Azoles are thus far the primary line of defense against fungi. Specifically, azoles inhibit the conversion of lanosterol to ergosterol, producing defective sterols and impairing fluidity in fungal plasmatic membranes. Studies on azole resistance have emphasized specific point mutations in CYP51/ERG11 proteins linked to resistance. Although very insightful, the traditional approach to studying azole resistance is time-consuming and prone to errors during meticulous alignment evaluation. It relies on a reference-based method using a specific protein sequence obtained from a wild-type (WT) phenotype. Therefore, this st

SUBMITTER: Almeida OGG 

PROVIDER: S-EPMC11356363 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature