De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

19 March 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral
polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-
CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study,
we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated
small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have
identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2.

Keywords

COVID-19
Artificial intelligence
Deep Learning
Drug design
Protease Inhibitor

Supplementary materials

Title
Description
Actions
Title
TCS RnI COVID-19 Supplementary Material
Description
Actions

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.