A Preliminary Investigation in the Molecular Basis of Host Shutoff Mechanism in SARS-CoV

by   Niharika Pandala, et al.

Recent events leading to the worldwide pandemic of COVID-19 have demonstrated the effective use of genomic sequencing technologies to establish the genetic sequence of this virus. In contrast, the COVID-19 pandemic has demonstrated the absence of computational approaches to understand the molecular basis of this infection rapidly. Here we present an integrated approach to the study of the nsp1 protein in SARS-CoV-1, which plays an essential role in maintaining the expression of viral proteins and further disabling the host protein expression, also known as the host shutoff mechanism. We present three independent methods of evaluating two potential binding sites speculated to participate in host shutoff by nsp1. We have combined results from computed models of nsp1, with deep mining of all existing protein structures (using PDBMine), and binding site recognition (using msTALI) to examine the two sites consisting of residues 55-59 and 73-80. Based on our preliminary results, we conclude that the residues 73-80 appear as the regions that facilitate the critical initial steps in the function of nsp1. Given the 90 SARS-CoV-1 and SARS-CoV-2, we conjecture the same critical initiation step in the function of COVID-19 nsp1.


Analyzing Host-Viral Interactome of SARS-CoV-2 for Identifying Vulnerable Host Proteins during COVID-19 Pathogenesis

The development of therapeutic targets for COVID-19 treatment is based o...

Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs

Coronavirus Disease 2019 (COVID-19) has been creating a worldwide pandem...

Identification and validation of Triamcinolone and Gallopamil as treatments for early COVID-19 via an in silico repurposing pipeline

SARS-CoV-2, the causative virus of COVID-19 continues to cause an ongoin...

Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19

The COVID-19 pandemic demands the rapid identification of drug-repurpusi...

Algorithmic Bio-surveillance For Precise Spatio-temporal Prediction of Zoonotic Emergence

Viral zoonoses have emerged as the key drivers of recent pandemics. Huma...

Training large margin host-pathogen protein-protein interaction predictors

Detection of protein-protein interactions (PPIs) plays a vital role in m...

MC-NN: An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types

Influenza poses a significant threat to public health, particularly amon...

Please sign up or login with your details

Forgot password? Click here to reset