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

Autor(es)

de Almeida, Otavio Guilherme Goncalves ; Kress, Marcia Regina von Zeska

• Tipo de documento: Artigo Científico
• Fonte: MICROORGANISMS; v. 12, n. 8, p. 17-pg., 2024-08-01.

Resumo

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 study introduces a machine learning (ML)-based approach utilizing molecular descriptors representing the physiochemical attributes of CYP51/ERG11 protein isoforms. This approach aims to unravel hidden patterns associated with azole resistance. The results highlight that descriptors related to amino acid composition and their combination of hydrophobicity and hydrophilicity effectively explain the slight differences between the resistant non-wild-type (NWT) and WT (nonresistant) protein sequences. This study underscores the potential of ML to unravel nuanced patterns in CYP51/ERG11 sequences, providing valuable molecular signatures that could inform future endeavors in drug development and computational screening of resistant and nonresistant fungal lineages. (AU)

• Processo FAPESP: 22/00754-4 - Análise genômica de isolados clínicos de Fusarium spp. e de determinantes genéticos de resistência aos azóis utilizando métodos de machine learning
• Beneficiário: Otávio Guilherme Gonçalves de Almeida
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 20/07546-2 - Estudo da resistência de isolados clínicos de Fusarium spp. à anfotericina B e aos azóis
• Beneficiário: Marcia Regina von Zeska Kress
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 23/12463-7 - Estudo da resistência de isolados clínicos de Fusarium e Aspergillus aos antifúngicos azólicos e a biossíntese de nanopartículas metálicas como alternativa terapêutica antifúngica
• Beneficiário: Marcia Regina von Zeska Kress
• Modalidade de apoio: Auxílio à Pesquisa - Regular