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Large scale peptide screening against main protease of SARS CoV-2.
Uddin, Md Jaish; Akhter, Hasina; Chowdhury, Urmi; Mawah, Jannatul; Karim, Sanzida Tul; Jomel, Mohammad; Islam, Md Sirajul; Islam, Mohammad Raqibul; Onin, Latifa Afrin Bhuiyan; Ali, Md Ackas; Efaz, Faiyaz Md; Halim, Mohammad A.
  • Uddin MJ; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Akhter H; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Chowdhury U; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Mawah J; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Karim ST; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Jomel M; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Islam MS; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Islam MR; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Onin LAB; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Ali MA; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
  • Efaz FM; Department of Chemistry and Biochemistry, Kennesaw State University, Kennesaw, Georgia, USA.
  • Halim MA; Division of Infectious Disease and Division of Computer-Aided Drug Design, The Red-Green Research Centre, Dhaka, Bangladesh.
J Comput Chem ; 44(8): 887-901, 2023 03 30.
Article in English | MEDLINE | ID: covidwho-2284793
ABSTRACT
The COVID-19 pandemic has been a public health emergency, with deadly forms constantly emerging around the world, highlighting the dire need for highly effective antiviral therapeutics. Peptide therapeutics show significant potential for this viral disease due to their efficiency, safety, and specificity. Here, two thousand seven hundred eight antibacterial peptides were screened computationally targeting the Main protease (Mpro) of SARS CoV-2. Six top-ranked peptides according to their binding scores, binding pose were investigated by molecular dynamics to explore the interaction and binding behavior of peptide-Mpro complexes. The structural and energetic characteristics of Mpro-DRAMP01760 and Mpro-DRAMP01808 complexes fluctuated less during a 250 ns MD simulation. In addition, three peptides (DRAMP01760, DRAMP01808, and DRAMP01342) bind strongly to Mpro protein, according to the free energy landscape and principal component analysis. Peptide helicity and secondary structure analysis are in agreement with our findings. Interaction analysis of protein-peptide complexes demonstrated that Mpro's residue CYS145, HIS41, PRO168, GLU166, GLN189, ASN142, MET49, and THR26 play significant contributions in peptide-protein attachment. Binding free energy analysis (MM-PBSA) demonstrated the energy profile of interacting residues of Mpro in peptide-Mpro complexes. To summarize, the peptides DRAMP01808 and DRAMP01760 may be highly Mpro specific, resulting disruption in a viral replication and transcription. The results of this research are expected to assist future research toward the development of antiviral peptide-based therapeutics for Covid-19 treatment.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: J Comput Chem Journal subject: Chemistry Year: 2023 Document Type: Article Affiliation country: Jcc.27050

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: J Comput Chem Journal subject: Chemistry Year: 2023 Document Type: Article Affiliation country: Jcc.27050