Bioinformatic study to discover natural molecules with activity against COVID-19

Area of Science:

• Bioinformatics
• Computational drug discovery
• Virology

Background:

• The COVID-19 pandemic, caused by SARS-CoV-2, has had a significant global impact since 2019.
• As of September 2020, there were over 31 million cases and 960,000 deaths worldwide.
• No definitive cure or proven therapeutics were available for COVID-19 at the time of the study.

Purpose of the Study:

• To identify potential drug candidates for treating COVID-19 using bioinformatics approaches.
• To virtually screen natural compounds for their efficacy against SARS-CoV-2.

Main Methods:

• High-Throughput Virtual Screening (HTVS) was employed.
• Molecular docking studies were performed on the Zinc natural database.
• Analysis focused on identifying molecules with potential therapeutic applications against COVID-19.

Main Results:

• Ramipril benzyl ester, propafenone dimer, and Lariciresinol were identified as key drug candidates.
• Several other lead molecules, including stylopine and scopolamine, were also identified.
• These compounds demonstrated potential for treating COVID-19 disease.

Conclusions:

• The identified molecules show potential as effective inhibitors against COVID-19.
• This study provides a basis for further investigation into novel therapeutics for coronavirus disease 2019.
• Bioinformatics screening is a valuable tool for accelerating drug discovery for emerging infectious diseases.