Drug repurposing against SARS-CoV-2 using computational approaches.

Area of Science:

• Virology
• Drug Discovery
• Computational Chemistry

Background:

• The COVID-19 pandemic necessitates rapid development of effective treatments.
• Traditional drug development timelines are insufficient for urgent global health crises.
• Repurposing existing drugs presents a viable strategy to accelerate therapeutic interventions.

Purpose of the Study:

• To review essential SARS-CoV-2 protein targets and their potential inhibitors identified through computational approaches.
• To highlight drugs that have progressed to clinical trials for COVID-19 treatment.

Main Methods:

• Analysis of structural data for key SARS-CoV-2 proteins.
• Application of computational methods to predict potential drug inhibitors.
• Review of identified candidates progressing through clinical trials.

Main Results:

• Structural data for critical viral proteins were rapidly obtained.
• Computational approaches identified numerous potential inhibitors for SARS-CoV-2 targets.
• Thirty-five drug candidates were proposed for further evaluation.
• Ten of these candidates are currently in Phase III and IV clinical trials for COVID-19.

Conclusions:

• Computational drug repurposing is an effective strategy for accelerating COVID-19 treatment development.
• Several promising drug candidates have emerged from computational screening and advanced to clinical testing.
• This approach significantly shortens the timeline for identifying potential therapies against emerging infectious diseases.