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Computational targeting of iron uptake proteins in Covid-19 induced mucormycosis to identify inhibitors via molecular
Manjima Sen1, B M Priyanka2, D Anusha3
1Department of Public Health Dentistry, DAPM RV Dental College, Bangalore, 560078 India.
Abstract:
Mucormycosis is a concerning invasive fungal infection with difficult diagnosis, high mortality rates, and limited treatment options. Iron availability is crucial for fungal growth that causes this disease. This study aimed to computationally target iron uptake proteins in Rhizopus arrhizus, Lichtheimia corymbifera, and Mucor circinelloides to identify inhibitors, thereby halting fungal growth and intervening in mucormycosis pathogenesis. Seven important iron uptake proteins were identified, modeled, and validated using Ramachandran plots. An in-house antifungal library of ~ 15,401 compounds was screened in molecular docking studies with these proteins. The best small molecule-protein complexes were simulated at 100 ns using Maestro, Schrodinger. Toxicity predictions suggested all six molecules, identified as the best binding compounds to seven proteins, belonged to lower toxicity levels per GHS classification. A molecular mechanics GBSA study for all seven complexes indicated low standard deviations after calculating free binding energies every 10 ns of the 100 ns trajectory. Density functional theory via quantum mechanics approaches highlighted the HOMO, LUMO, and other properties of the six best-bound molecules, revealing their binding capabilities and behaviour. This study sheds light on the molecular mechanisms and protein-ligand interactions, providing a multi-dimensional view towards the use of FDBD01920, FDBD01923, and FDBD01848 as stable antifungal ligands.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s40203-024-00264-7.
Insights
This study computationally identified novel small molecules targeting iron uptake proteins in key fungi responsible for mucormycosis. These potential new antifungal drugs show promise for treating this dangerous infection.
Area of Science:
- Mycology
- Computational Chemistry
- Drug Discovery
Background:
- Mucormycosis is a severe fungal infection with high mortality and limited treatments.
- Iron is essential for the growth of fungi causing mucormycosis.
- Targeting fungal iron uptake presents a promising therapeutic strategy.
Purpose of the Study:
- To computationally identify inhibitors of iron uptake proteins in Rhizopus arrhizus, Lichtheimia corymbifera, and Mucor circinelloides.
- To explore novel therapeutic strategies against mucormycosis by disrupting fungal iron metabolism.
- To provide a multi-dimensional understanding of protein-ligand interactions for antifungal drug development.
Main Methods:
- Identification, modeling, and validation of seven key iron uptake proteins.
- Screening of an in-house library (~15,401 compounds) using molecular docking.
- Molecular dynamics simulations (100 ns) and toxicity predictions (GHS classification).
- Free binding energy calculations (MM-GBSA) and quantum mechanics (DFT) analysis.
Main Results:
- Six compounds demonstrated strong binding to the targeted iron uptake proteins.
- Predicted low toxicity levels for the identified lead compounds.
- Molecular simulations confirmed stable protein-ligand complexes and provided insights into binding mechanisms.
- DFT analysis revealed favorable electronic properties and binding capabilities of the top ligands.
Conclusions:
- FDBD01920, FDBD01923, and FDBD01848 are identified as stable and promising antifungal ligands.
- The study provides a rational basis for developing new mucormycosis treatments targeting iron uptake.
- Computational approaches are effective for identifying novel antifungal drug candidates.
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