MUTATIONAL ANALYSIS OF SARS-COV-2 ORF6 AND ITS EFFECT ON EVASION OF HUMAN IMMUNE SYSTEM: A MOLECULAR DOCKING AND SIMMULATION APPROACHES

SARS CoV-2 (Severe acute respiratory syndrome coronavirus 2), is a virus responsible for causing a global pandemic of COVID-19 respiratory disease, first broke out in Wuhan, China, on the 31st of December 2019. As of 4th  July 2020, there have been over  11 million infected persons around

Project Title

MUTATIONAL ANALYSIS OF SARS-COV-2 ORF6 AND ITS EFFECT ON EVASION OF HUMAN IMMUNE SYSTEM: A MOLECULAR DOCKING AND SIMMULATION APPROACHES

Project Area of Specialization

Artificial Intelligence

Project Summary

SARS CoV-2 (Severe acute respiratory syndrome coronavirus 2), is a virus responsible for causing a global pandemic of COVID-19 respiratory disease, first broke out in Wuhan, China, on the 31st of December 2019. As of 4th  July 2020, there have been over  11 million infected persons around the world and 525,000 deaths (https://coronavirus.jhu.edu/), until 12th April 2021 the confirmed cases exceed 136 million, and more than 2,930,000 deaths. According to the latest updates, as of 15 April 2022, the global confirmed cases are about 504 million and 6,197,159 deaths (https://coronavirus.jhu.edu/). The symptoms of the disease range from mild to acute even though, cases with no symptoms have also been documented.  Coronaviruses are dangerous pathogens for both humans and animals, they are transmitted from animals to humans and also from person to person. SARS CoV-2 belongs to Riboviria kingdom, Nidovirales order, coronaviridae family, ?-coronavirus Genes and SARS CoV species.

ORF6 protien of SARS CoV-2 counteracts interferon signaling by preventing the STAT1 nuclear translocation. Through two different tactics and strategies, ORF6 work as a virulence factor. First, ORF6 shows direct interaction with STAT1 leads to suppression of nuclear translocation. Second, ORF6 shows direct interaction with importin alpha 1. ORF6 binding to importin alpha 1 leads to suppression of nuclear translocation. Importin alpha 1, is a nuclear transport factor encoded by KPNA2, that represses viral replication and propagation thus knocking out KPNA2 intensify viral propagation. Furthermore, gene expression analysis exhibit that in an older person’s lungs importin alpha 1 level is lowered. Thus SARS CoV-2 ORF6 enhances replication of the virus by disturbing nuclear translocation, helps in disease progression, particularly in older persons.

Keeping in view the importance of ORF6 in human immune evasion we designed this study to first identify the emerging mutations in the ORF6 protein by using the different artificial intelligence algorithms. Then the high deleterious mutation will be identified by using different online servers. Then we will check the effect of the identified mutations on the structural stability of the ORF6 protein. As the ORF6 protein is involved in the human immune evasion by using the STAT1 and STAT2 proteins, therefore, we will check the effect of these mutations on the binding ability of ORF6 with the aforementioned proteins by using the molecular docking approaches. Finally, the molecular dynamics simulation approach will be used to check the binding network of ORF6-STAT1 and ORF6-STAT2 complexes. Afterward, the binding interfaces of the above-mentioned complexes will be targeted by drugs using the drug screening approaches.

Project Objectives

1. To detect newly emerged mutations in ORF6 protein by using different computational algorithms
2. To predict the high deleterious mutations by using different online servers.
3. To check the effect of identified mutations on the structural stability of the ORF6 protein
4. To check the effect of mutations on the binding affinity of ORF6 with STAT1 and STAT2 by using the molecular docking approach.
5. Molecular dynamic simulation of the ORF6-STAT1 and ORF6-STAT2 complexes.
6. Drug screening against the identified binding interfaces between ORF6 and STAT proteins.

Project Implementation Method

The project will be executed by using the AI and bioinformatics tools to identify the drugable targets for the prevention of coronavirus pathogenesis 

Benefits of the Project

The ultimate goal is therefore to computationally investigate the novel biomarkers in the development of COVID-19 infection and drug resistance. Otherwise, novel drug targets (biomarkers) may help to overcome the problem of drug resistance in Pathogenesis. The most advanced  In-silico techniques. particularly using artificial intelligence and machine learning methods, can be implemented to predict the structural implications of mutations. This will be beneficial in understanding the mechanisms of drug resistance and the discovery of novel biomarkers and drugs.

Technical Details of Final Deliverable

For the successful completion of this project, we need a high-performance computer recources and cost of MD simulations 

Final Deliverable of the Project

Hardware System

Core Industry

Medical

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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