AI Article Synopsis

  • Significant fungal pathogens pose a risk for human infections, and there's an urgent need for new antifungal treatments due to the rise of drug-resistant strains.
  • A thorough screening of 297 natural compounds was conducted using computational methods to evaluate their potential effectiveness against specific proteins associated with these fungi.
  • The study identified promising antifungal candidates, with further validation needed, which could lead to innovative treatment options for resistant fungal infections.

Article Abstract

and are recognized as significant fungal pathogens, responsible for various human infections. The rapid emergence of drug-resistant strains among these fungi requires the identification and development of innovative antifungal therapies. We undertook a comprehensive screening of 297 naturally occurring compounds to address this challenge. Using computational docking techniques, we systematically analyzed the binding affinity of each compound to key proteins from (PDB ID: 1EAG) and (PDB ID: 3DJE). This rigorous in silico examination aimed to unveil compounds that could potentially inhibit the activity of these fungal infections. This was followed by an ADMET analysis of the top-ranked compound, providing valuable insights into the pharmacokinetic properties and potential toxicological profiles. To further validate our findings, the molecular reactivity and stability were computed using the DFT calculation and molecular dynamics simulation, providing a deeper understanding of the stability and behavior of the top-ranking compounds in a biological environment. The outcomes of our study identified a subset of natural compounds that, based on our analysis, demonstrate notable potential as antifungal candidates. With further experimental validation, these compounds could pave the way for new therapeutic strategies against drug-resistant fungal pathogens.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11279552PMC
http://dx.doi.org/10.3390/ph17070886DOI Listing

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