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In Silico Prediction and Designing of Potential siRNAs to be used as Antivirals Against SARS-CoV-2.
Sohrab, Sayed S; El-Kafrawy, Sherif A; Abbas, Aymn T; Bajrai, Leena H; Azhar, Esam I.
  • Sohrab SS; Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
  • El-Kafrawy SA; Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Abbas AT; Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Bajrai LH; Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Azhar EI; Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
Curr Pharm Des ; 27(32): 3490-3500, 2021.
Article in English | MEDLINE | ID: covidwho-1024456
Semantic information from SemMedBD (by NLM)
1. SARS coronavirus PROCESS_OF Chiroptera
Subject
SARS coronavirus
Predicate
PROCESS_OF
Object
Chiroptera
2. SARS coronavirus PROCESS_OF Chiroptera
Subject
SARS coronavirus
Predicate
PROCESS_OF
Object
Chiroptera
ABSTRACT

BACKGROUND:

The unusual pneumonia outbreak that originated in the city of Wuhan, China in December 2019 was found to be caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19.

METHODS:

In this work, we have performed an in silico design and prediction of potential siRNAs based on genetic diversity and recombination patterns, targeting various genes of SARS-CoV-2 for antiviral therapeutics. We performed extensive sequence analysis to analyze the genetic diversity and phylogenetic relationships, and to identify the possible source of virus reservoirs and recombination patterns, and the evolution of the virus as well as we designed the siRNAs which can be used as antivirals against SARS-CoV-2.

RESULTS:

The sequence analysis and phylogenetic relationships indicated high sequence identity and closed clusters with many types of coronavirus. In our analysis, the full-genome of SARS-CoV-2 showed the highest sequence (nucleotide) identity with SARS-bat-ZC45 (87.7%). The overall sequence identity ranged from 74.3% to 87.7% with selected SARS viruses. The recombination analysis indicated the bat SARS virus is a potential recombinant and serves as a major and minor parent. We have predicted 442 siRNAs and finally selected only 19 functional, and potential siRNAs.

CONCLUSION:

The siRNAs were predicted and selected based on their greater potency and specificity. The predicted siRNAs need to be validated experimentally for their effective binding and antiviral activity.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study / Risk factors Limits: Humans Language: English Journal: Curr Pharm Des Journal subject: Pharmacy Year: 2021 Document Type: Article Affiliation country: 1381612827999210111194101

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study / Risk factors Limits: Humans Language: English Journal: Curr Pharm Des Journal subject: Pharmacy Year: 2021 Document Type: Article Affiliation country: 1381612827999210111194101