Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells
Dengue virus (DV) infection is one of the main public health concerns, affecting approximately 390 million people worldwide, as reported by the World Health Organization. Yet, there is no antiviral treatment for DV infection. Therefore, the development of potent and nontoxic anti-DV, as a complement...
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my.um.eprints.418362023-10-20T04:22:13Z http://eprints.um.edu.my/41836/ Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells Arumugam, Aathe Cangaree Agharbaoui, Fatima Ezzahra Khazali, Ahmad Suhail Yusof, Rohana Abd Rahman, Noorsaadah Ahmad Fuaad, Abdullah Al Hadi QA75 Electronic computers. Computer science QH301 Biology Dengue virus (DV) infection is one of the main public health concerns, affecting approximately 390 million people worldwide, as reported by the World Health Organization. Yet, there is no antiviral treatment for DV infection. Therefore, the development of potent and nontoxic anti-DV, as a complement for the existing treatment strategies, is urgently needed. Herein, we investigate a series of small peptides inhibitors of DV antiviral activity targeting the entry process as the promising strategy to block DV infection. The peptides were designed based on our previously reported peptide sequence, DN58opt (TWWCFYFCRRHHPFWFFYRHN), to identify minimal effective inhibitory sequence through molecular docking and dynamics studies. The in silico designed peptides were synthesized using conventional Fmoc solid-phase peptide synthesis chemistry, purified by RP-HPLC and characterized using LCMS. Later, they were screened for their antiviral activity. One of the peptides, AC 001, was able to reduce about 40% of DV plaque formation. This observation correlates well with the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) analysis - AC 001 showed the most favorable binding affinity through 60 ns simulations. Pairwise residue decomposition analysis has revealed four key residues that contributed to the binding of these peptides into the DV2 E protein pocket. This work identifies the minimal peptide sequence required to inhibit DV replication and explains the behavior observed on an atomic level using computational study. Communicated by Ramaswamy H. Sarma Taylor & Francis 2022-06-28 Article PeerReviewed Arumugam, Aathe Cangaree and Agharbaoui, Fatima Ezzahra and Khazali, Ahmad Suhail and Yusof, Rohana and Abd Rahman, Noorsaadah and Ahmad Fuaad, Abdullah Al Hadi (2022) Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells. Journal of Biomolecular Structure and Dynamics, 40 (11). pp. 5026-5035. ISSN 0739-1102, DOI https://doi.org/10.1080/07391102.2020.1866074 <https://doi.org/10.1080/07391102.2020.1866074>. 10.1080/07391102.2020.1866074 |
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QA75 Electronic computers. Computer science QH301 Biology Arumugam, Aathe Cangaree Agharbaoui, Fatima Ezzahra Khazali, Ahmad Suhail Yusof, Rohana Abd Rahman, Noorsaadah Ahmad Fuaad, Abdullah Al Hadi Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells |
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Dengue virus (DV) infection is one of the main public health concerns, affecting approximately 390 million people worldwide, as reported by the World Health Organization. Yet, there is no antiviral treatment for DV infection. Therefore, the development of potent and nontoxic anti-DV, as a complement for the existing treatment strategies, is urgently needed. Herein, we investigate a series of small peptides inhibitors of DV antiviral activity targeting the entry process as the promising strategy to block DV infection. The peptides were designed based on our previously reported peptide sequence, DN58opt (TWWCFYFCRRHHPFWFFYRHN), to identify minimal effective inhibitory sequence through molecular docking and dynamics studies. The in silico designed peptides were synthesized using conventional Fmoc solid-phase peptide synthesis chemistry, purified by RP-HPLC and characterized using LCMS. Later, they were screened for their antiviral activity. One of the peptides, AC 001, was able to reduce about 40% of DV plaque formation. This observation correlates well with the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) analysis - AC 001 showed the most favorable binding affinity through 60 ns simulations. Pairwise residue decomposition analysis has revealed four key residues that contributed to the binding of these peptides into the DV2 E protein pocket. This work identifies the minimal peptide sequence required to inhibit DV replication and explains the behavior observed on an atomic level using computational study. Communicated by Ramaswamy H. Sarma |
format |
Article |
author |
Arumugam, Aathe Cangaree Agharbaoui, Fatima Ezzahra Khazali, Ahmad Suhail Yusof, Rohana Abd Rahman, Noorsaadah Ahmad Fuaad, Abdullah Al Hadi |
author_facet |
Arumugam, Aathe Cangaree Agharbaoui, Fatima Ezzahra Khazali, Ahmad Suhail Yusof, Rohana Abd Rahman, Noorsaadah Ahmad Fuaad, Abdullah Al Hadi |
author_sort |
Arumugam, Aathe Cangaree |
title |
Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells |
title_short |
Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells |
title_full |
Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells |
title_fullStr |
Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells |
title_full_unstemmed |
Computational-aided design: Minimal peptide sequence to block dengue virus transmission into cells |
title_sort |
computational-aided design: minimal peptide sequence to block dengue virus transmission into cells |
publisher |
Taylor & Francis |
publishDate |
2022 |
url |
http://eprints.um.edu.my/41836/ |
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1781704562468454400 |