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In silico evaluation of the inhibitory potential of nucleocapsid inhibitors of SARS-CoV-2: a binding and energetic perspective.
Haque, Shafiul; Kumar, Pawan; Mathkor, Darin Mansor; Bantun, Farkad; Jalal, Naif A; Mufti, Ahmad Hasan; Prakash, Amresh; Kumar, Vijay.
  • Haque S; Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia.
  • Kumar P; School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
  • Mathkor DM; Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia.
  • Bantun F; Department of Microbiology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Jalal NA; Department of Microbiology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Mufti AH; Medical Genetics Department, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Prakash A; Amity Institute of Integrative Sciences and Health, Amity University Haryana, Gurgaon, India.
  • Kumar V; Amity Institute of Neuropsychology & Neurosciences, Amity University, Noida, Uttar Pradesh, India.
J Biomol Struct Dyn ; : 1-11, 2022 Nov 15.
Article in English | MEDLINE | ID: covidwho-2120918
ABSTRACT
The COVID-19 outbreak brought on by the SARS-CoV-2 virus continued to infect a sizable population worldwide. The SARS-CoV-2 nucleocapsid (N) protein is the most conserved RNA-binding structural protein and is a desirable target because of its involvement in viral transcription and replication. Based on this aspect, this study focused to repurpose antiviral compounds approved or in development for treating COVID-19. The inhibitors chosen are either FDA-approved or are currently being studied in clinical trials against COVID-19. Initially, they were designed to target stress granules and other RNA biology. We have utilized structure-based molecular docking and all-atom molecular dynamics (MD) simulation approach to investigate in detail the binding energy and binding modes of the different anti-N inhibitors to N protein. The result showed that five drugs including Silmitasterib, Ninetanidinb, Ternatin, Luteolin, Fedratinib, PJ34, and Zotatafin were found interacting with RNA binding sites as well as to predicted protein interface with higher binding energy. Overall, drug binding increases the stability of the complex with maximum stability found in the order, Silmitasertib > PJ34 > Zotatatafin. In addition, the frustration changes due to drug binding brings a decrease in local frustration and this decrease is mainly observed in α-helix, ß3, ß5, and ß6 strands and are important for drug binding. Our in-silico data suggest that an effective interaction occurs for some of the tested drugs and prompt their further validation to reduce the rapid outspreading of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: J Biomol Struct Dyn Year: 2022 Document Type: Article Affiliation country: 07391102.2022.2146752

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: J Biomol Struct Dyn Year: 2022 Document Type: Article Affiliation country: 07391102.2022.2146752