Screening shows potential drugs to fight COVID-19

New Virtual Screening Strategy Identifies Existing Drug that Inhibits COVID-19 Virus

The COVID-19 caused due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has grown into a global pandemic infecting millions of people and tens of thousands of lives lost. As of now, no clinically proven drug or vaccine is available. There is an indispensable need to identify antiviral agents that can inhibit SARS-CoV-2.

The de novo drug development process is time-consuming, unable to meet the urgent need to combat COVID-19. Given current emergencies, repurposing existing approved drugs for COVID-19 may provide a shortcut. Drugs under recent clinical trials such as Remdesivir inhibited the replication of SARS-CoV-2 in vitro. The study illustrates the structural basis of the RNA-dependent RNA polymerase (RdRp) inhibited by Remdesivir.

Some patients have been treated with Remdesivir and shown significant clinical improvements. RdRp is one of the most assuring therapeutic targets as a core component of the RNA synthesis machinery. Molecules that can attach to the catalytic site of RdRp could potentially interfere with the viral RNA synthesis.

A novel computational drug screening strategy coupled with lab experiments imply that Pralatrexate, a chemotherapy medication initially developed to treat lymphoma, could potentially be repurposed to treat Covid-19. Haiping Zhang of the Shenzhen Institutes of Advanced Technology in Shenzhen, China, and co-workers presented these conclusions in the open-access journal PLOS Computational Biology.

With the Covid-19 pandemic causing illness and mortality worldwide, there is an urgent need for better treatments. One shortcut could be to repurpose existing drugs, developed initially to treat other conditions. Computational methods can help identify such medicines by simulating how different drugs would interact with SARS-CoV-2, the virus that causes Covid-19.

Zhang and colleagues consolidated multiple computational techniques that simulate drug-virus interactions from different, complementary perspectives to aid the virtual screening of existing drugs. They utilized this hybrid approach to screen 1,906 existing drugs for their potential ability to inhibit replication of SARS-CoV-2 by targeting a viral protein called RNA-dependent RNA polymerase (RdRP).

The novel screening method identified four promising drugs. The researchers then tested these drugs against SARS-CoV-2 in lab experiments. Two of them – Azithromycin and Pralatrexate, successfully inhibited replication of the virus. Further lab experiments showed that Pralatrexate more strongly inhibited viral replication than Remdesivir, a drug currently used to treat some Covid-19 patients.

According to these findings, potentially repurposing Pralatrexate can help treat Covid-19. However, this chemotherapy drug can prompt significant side effects and is suitable for people with terminal lymphoma, so immediate use for Covid-19 patients is not guaranteed. Still, the findings support using the new screening strategy to identify drugs and repurposing them.

“We have demonstrated the value of our novel hybrid approach that combines deep-learning technologies with more traditional simulations of molecular dynamics,” Zhang says. He and his colleagues are now developing additional computational methods for generating novel molecular structures that could be developed into novel drugs to treat Covid-19.

What is Viral replication?

Virologists use this term to describe biological viruses’ formation in the target host cells during the infection process. Viruses must first enter into the cell before viral replication can happen. From the virus’s perspective, viral replication’s primary purpose is to allow production and survival of its kind. The virus can continue infecting new hosts by generating abundant copies of its genome and packaging them into viruses. Replication between viruses is immensely varied and depends on the type of genes involved.

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