Unveiling Moroccan Nature's Arsenal: A Computational Molecular Docking, Density Functional Theory, and Molecular Dynamics Study of Natural Compounds against Drug-Resistant Fungal Infections.
Imane YamariOussama AbchirHassan NourMeriem KhedraouiBouchra RossafiAbdelkbir ErrouguiMohammed TalbiAbdelouahid SamadiMHammed El KoualiSamir ChtitaPublished in: Pharmaceuticals (Basel, Switzerland) (2024)
Candida albicans and Aspergillus fumigatus 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 Candida albicans (PDB ID: 1EAG) and Aspergillus fumigatus (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.
Keyphrases
- drug resistant
- candida albicans
- molecular docking
- molecular dynamics
- density functional theory
- molecular dynamics simulations
- multidrug resistant
- acinetobacter baumannii
- biofilm formation
- gram negative
- endothelial cells
- escherichia coli
- type diabetes
- magnetic resonance imaging
- cell wall
- mass spectrometry
- skeletal muscle
- insulin resistance
- human health
- protein protein
- transcription factor
- single molecule