Inspiration

A rapid rational drug repurposing approach to stop COVID-19 virus entry into human cells as therapy using data science techniques SARS-CoV-2 (COVID-19) emerged in late 2019, spread rapidly across the globe as pandemic claiming lives at unprecedented rate. Scientists are endeavouring to find various approaches to contain the spread of COVID-19 such as finding new drugs, drug repurposing of older drugs approved for other diseases, vaccines and use of antibodies. Our approach is to compare virus proteins and also get to finding the best ligand protein match for nullifying the virus effect UNIQUENESS The uniqueness of our work stems from identifying a peptide sequence specific to COVID-19 spike protein which is used for virus entry using data science techniques. This peptide sequence was identified through bioinformatics tool approaches. The classical new drug discovery route for antagonizing the activity against SARS-CoV-2 is long and high risk. Therefore, rational computational and rapid approaches for drug-repurposing such as ours are needed. The present work from our team will elucidate the repurposing of FDA approved anti-viral drugs, drugs approved for various diseases, and even some of the natural products/GRAS compounds approved by FDA. Our peptide sequence will be used as the guiding principle to find only those drugs that are selective for COVID-19. The repurposed drugs will be computationally screened, prioritized, and rank-ordered - followed by in vitro evaluation of the short-listed drugs. Our structure-based approaches will use molecular docking and will not only give a greater visual understanding of a protein/peptide interacting with a small molecule ligand/drugs but also provide rank-ordering of the FDA approved drugs.

How I built it

• PRE-STUDY: We are computational scientists with little or no knowledge of Biology or the functioning of the body, leave alone the world of viruses and bacteria, so we had to resort to classes online to understand the virus, its structure and also how it functions. We studied for 48 hours straight , and some of the classes I found brilliant which gave me understanding were classes on Virology (Virology Lectures by Vincent Racaniello) • EXPERIMENTAL RESEARCH Making an Atomic Cloud : : Armed with this knowledge, and backed by the fact that protein membrane of the virus plays a major part in attacking a host cell within the human body and then replicates, we wanted to do the following studies, more like questions that we wanted an answer about o Can we get the viral protein structure and can we make a 3d model of atoms by placement? o Can we compare the protein amino acid chains of two or more viruses? • Extending comparison to amino acids : The program now compares the protein atomic sequences and matches them. Given below is also a structure match of Corona virus with Polio

Challenges I ran into

Understanding the bio chemistry facet and understanding the forces that play between atoms like bond lengths, dihedral angles etc was a major challenge

Accomplishments that I'm proud of

Proud of the fact that the results match , with things talked about like hydroy choloquine also our deeper study indicates how amino acids of polio match those of corona virus and a very prominent scientist, Dr. Robert Barlow is on records in PBS indicating how OPV could give immunity for covid patients. So far, our results match elements being spoken about

What's next for COVID-19 In Quest of a Therapeutic Drug

We plan to extend this work by using convolutional 3d networks to see protein ligand interaction with active sites as an attack plan.

In this, we will be using the Repurposed DOVE model, which is a protein docking model evaluation method which distinguishes good quality from incorrect models, and is fairly accurate as it has been trained on 2 MN examples.

We also have a provisional patent approved for Rapid Rational Identification of Repurposed FDA Approved Drugs AND NCE’S as therapeutics for COVID-19 using a specific amino acid sequence of VIRUS surface spike protein (No. TEMP/E1/18551/2020CH)

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