In response to COVID-19

At Prescience In silico we have a technology prototype to zero down to a particular set of molecules (NCE) that could be active against SARS-COV2. So, even we were busy with the development and automation of the platform, we decided to use our technology for finding NCEs and drugs for repurposing for COVID-19.

The current state for designing and developing a new drug candidate is alarming. The time required for a molecule to reach bed side is still more than 10 years. Additionally the expenses are very high, that limits the small pharmaceutical companies to start a program for NCE development. Therefore, in India, even we are having large number of pharmaceutical companies, all the innovations are targeted towards development of generic molecules and new formulations.

Because of this, the development of new molecules are not at par towards the demand and we started realising this more after we got hit my COVID-19. There is a large need of new molecules, even to address orphan diseases, cancer, tuberculosis etc.

Our technology which is a combination of high throughput computational screening, artificial intelligence and large scale computer simulations with enhanced sampling is capable of reducing the time of the drug development and so reduce the expenses. We also get mechanistic understanding of the ligand-target binding and selectivity towards a particular protein target in the pathway (role of other proteins in the similar pathways) along with binding free energies, effect of solvent (we take solvent as well in our calculations), effect of entropy and effect of ions/pH. Our method is best suited for NCEs and drug repurposing.

We are using this revolutionary technology powered by large scale computer simulations and AI to identify the top candidate drugs that are highly likely to be effective in treating COVID-19.

Within last 20 days, we have obtained data from 1.5 million molecules, from which we have selected 30 molecules and subjected to our technology platform. We have identified 3 best molecules (NCE) which show high binding to the target protein. We have compared the data with a molecule which is currently in clinical trail for repurposing and found that our NCEs are much better i.e., potentially efficacious.

We are also working on drug repurposing for COVID-19. Our method is based on finding the targets that are in the pathways for virus and human cell interactions. So, we have taken a holistic approach to find a target and zoom in the space of available FDA approved molecules. Finally, we are using our technology platform for spotting the right combination i.e., molecules with high specificity towards the target in a particular pathway..

Recent publications by our team


submitted on 07.05.2020, 12:05 and posted on 08.05.2020, 03:11 by Sadanandam Namsani Debabrata Pramanik Mohd Aamir Khan Sudip Roy Jayant Singh

Here we report new chemical entities that are highly specific in binding towards the 3-chymotrypsin- like cysteine protease (3CLpro) protein present in the novel SARS-CoV2 virus. The viral 3CLpro

protein controls coronavirus replication. Therefore, 3CLpro is identified as a target for drug molecules. We have implemented an enhanced sampling method in combination with molecular dynamics and docking to bring down the computational screening search space to four molecules that could be synthesised and tested against COVID-19. Our computational method is much more robust than any other method available for drug screening e.g., docking, because of sampling of the free energy surface of the binding site of the protein (including the ligand) and use of explicit solvent. We have considered all possible interactions between all the atoms present in the protein, ligands, and water. Using high performance computing with graphical processing units we are able to perform large number of simulations within a month's time and converge to 4 most strongly bound ligands (by free energy and other scores) from a set of 17 ligands with lower docking scores. Based on our results and analysis, we claim with high confidence, that we have identified four potential ligands. Out of those, one particular ligand is the most promising candidate, based on free energy data, for further synthesis and testing against SARS-CoV-2 and might be effective for the cure of COVID-19.

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