Bioinformatics in Antifungal Design: Strategies To Overcome Resistance from a Proteomic Perspective

Abstract Objective of the Review Fungal resistance is a major public health concern that reduces the efficacy of antifungal therapies and increases hospital mortality rates. This review aims to discuss how bioinformatics tools contribute to understanding resistance mechanisms and to the rational design of novel antifungal agents. Recent Findings Bioinformatics approaches such as genomic analysis, protein structural modeling, and multi-omics integration have advanced the comprehension of fungal pathogen biology. These methods facilitate the identification of molecular targets and the strategic design of antifungal drugs. In silico techniques, including molecular docking and molecular modeling, have shown great potential for discovering and optimizing antifungal and adjuvant molecules that enhance existing therapies. Nevertheless, the limited availability of experimental data, high computational costs, and difficulties in clinical validation remain major barriers to translating these findings into therapeutic applications. Summary The integration of bioinformatics into antifungal research provides valuable insights into resistance mechanisms and drug development strategies. Despite current limitations, continuous investment in research and technological innovation is crucial to overcoming these challenges and broadening the antifungal therapeutic arsenal.

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Publication Details

Journal
Current Fungal Infection Reports
Published
2026-02-24
DOI
https://doi.org/10.1007/s12281-026-00523-4
Primary Topic
Antifungal resistance and susceptibility
Type
article
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article

Bioinformatics in Antifungal Design: Strategies To Overcome Resistance from a Proteomic Perspective

Vitória Marina Abrantes Batista, Sonaly Lima Albino, Ricardo Olímpio de Moura, Diego Romario-Silva et al.
Current Fungal Infection Reports
Antifungal resistance and susceptibility
article

Bioinformatics in Antifungal Design: Strategies To Overcome Resistance from a Proteomic Perspective

Vitória Marina Abrantes Batista, Sonaly Lima Albino, Ricardo Olímpio de Moura, Diego Romario-Silva, Letícia Targino Campos, Arthur Gabriel Corrêa de Farias, Igor José dos Santos Nascimento, Joanilda Paolla Raimundo Silva, Camila Vital de Araújo, Edja Maria Melo de Brito Costa
article en

Abstract

Abstract Objective of the Review Fungal resistance is a major public health concern that reduces the efficacy of antifungal therapies and increases hospital mortality rates. This review aims to discuss how bioinformatics tools contribute to understanding resistance mechanisms and to the rational design of novel antifungal agents. Recent Findings Bioinformatics approaches such as genomic analysis, protein structural modeling, and multi-omics integration have advanced the comprehension of fungal pathogen biology. These methods facilitate the identification of molecular targets and the strategic design of antifungal drugs. In silico techniques, including molecular docking and molecular modeling, have shown great potential for discovering and optimizing antifungal and adjuvant molecules that enhance existing therapies. Nevertheless, the limited availability of experimental data, high computational costs, and difficulties in clinical validation remain major barriers to translating these findings into therapeutic applications. Summary The integration of bioinformatics into antifungal research provides valuable insights into resistance mechanisms and drug development strategies. Despite current limitations, continuous investment in research and technological innovation is crucial to overcoming these challenges and broadening the antifungal therapeutic arsenal.

Current Fungal Infection ReportsVol. 20(1)
Universidade Estadual da Paraíba (BR), Universidade de Cuiabá (BR)
Openalex Percentile: Top 45%
Antifungal resistance and susceptibility
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