Butein as a potential binder of human ACE2 receptor for interfering with SARS-CoV-2 entry: a computer-aided analysis.
Neha KapoorSoma Mondal GhoraiPrem Kumar KhuswahaRakeshwar BandichhorSimone BrogiPublished in: Journal of molecular modeling (2022)
Natural products have been included in our dietary supplements and have been shown to have numerous therapeutic properties. With the looming danger of many zoonotic agents and novel emerging pathogens mainly of viral origin, many researchers are launching various clinical trials, testing these compounds for their antiviral activity. The present work deals with some of the available natural compounds from the literature that have demonstrated activity in counteracting pathogen infections. Accordingly, we screened, using in silico methods, this subset of natural compounds for searching potential drug candidates able to interfere in the recognition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and its target human angiotensin-converting enzyme 2 (hACE2) receptor, leading to the viral entry. Disrupting that recognition is crucial for slowing down the entrance of viral particles into host cells. The selected group of natural products was examined, and their interaction profiles against the host cell target protein ACE2 were studied at the atomic level. Based on different computer-based procedures including molecular docking, physicochemical property evaluation, and molecular dynamics, butein was identified as a potential hit molecule able to bind the hACE2 receptor. The results indicate that herbal compounds can be effective for providing possible therapeutics for treating and managing coronavirus disease 2019 (COVID-19) infection.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- angiotensin converting enzyme
- molecular docking
- molecular dynamics
- angiotensin ii
- coronavirus disease
- endothelial cells
- clinical trial
- binding protein
- molecular dynamics simulations
- induced pluripotent stem cells
- systematic review
- density functional theory
- pluripotent stem cells
- deep learning
- randomized controlled trial
- machine learning
- protein protein
- oxidative stress
- candida albicans
- climate change
- data analysis
- pi k akt