Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches
Having a wide range of pharmacological action antiviral properties of alkaloids, these were focused on this study for computational screening against SARS-CoV-2 proteases. However, 256 alkaloids from PubChem databased, 10 compounds were selected by PASS prediction for primally observation having act...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Sami Publishing Company
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/39218/1/Identification%20of%20SARS-CoV-2%20inhibitors%20from%20alkaloids%20using%20molecular%20modeling%20and%20in%20silico%20approaches.pdf |
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| author | Roni, Md Abul Hasan Mortuza, Md. Golam Rozina, . Shaha, Ripon Kumar Hoque, Sajidul Kumer, Ajoy |
| author_facet | Roni, Md Abul Hasan Mortuza, Md. Golam Rozina, . Shaha, Ripon Kumar Hoque, Sajidul Kumer, Ajoy |
| author_sort | Roni, Md Abul Hasan |
| collection | UMP |
| description | Having a wide range of pharmacological action antiviral properties of alkaloids, these were focused on this study for computational screening against SARS-CoV-2 proteases. However, 256 alkaloids from PubChem databased, 10 compounds were selected by PASS prediction for primally observation having active value against virus with the main protease (Mpro) of acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Besides, the pharmacokinetics and Lipinski's rule of five (RO5) were evaluated for all molecules being drug likeness properties, and then these were selected for molecular docking against the Mpro of corona virus, and L-03, L-07, and L-13 found the best-bonded molecules accounting weak H bonding and hydrophobic bond interactions. In addition, on the binding energies of Mpro, L-3, L-7, L-13, L-18, L-25, L-26, L-34, L-39, L-42, and L-49 were at -8.6, -8.3, 8.2, -8.1, -8.0, -7.9, -7.9, -7.9, and -7.9 kcal/mol. Overall, L-3 is considerable best candidate with Mpro in view of the molecular docking score. In addition, the quantum properties, chemical hardness and softness values were calculated. Finally, from admetSAR online database, absorption, distribution, metabolism, excretion, and toxicity (ADMET) were evaluated. Lastly, L-3, L7, and L-13 were satisfied the toxicity category. In comparison to the World Health Organization (WHO) guidelines, FDA-approved antiviral drugs, favipiravir and remdesivir, which have binding energies of -5.1 and -8.1 kcal/mol of the Mpro, respectively. In this case, our selected L-3, L-7, L-13, and L-18 have binding energies of -8.6, -8.3, -8.2, and -8.2 kcal/mol, respectively. Thus, the L-3, L-7, L-13 and L-18 molecules will have strong activity against the SARS-CoV-2. |
| first_indexed | 2024-03-06T13:10:48Z |
| format | Article |
| id | UMPir39218 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T13:10:48Z |
| publishDate | 2023 |
| publisher | Sami Publishing Company |
| record_format | dspace |
| spelling | UMPir392182023-11-08T03:59:38Z http://umpir.ump.edu.my/id/eprint/39218/ Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches Roni, Md Abul Hasan Mortuza, Md. Golam Rozina, . Shaha, Ripon Kumar Hoque, Sajidul Kumer, Ajoy QD Chemistry TP Chemical technology Having a wide range of pharmacological action antiviral properties of alkaloids, these were focused on this study for computational screening against SARS-CoV-2 proteases. However, 256 alkaloids from PubChem databased, 10 compounds were selected by PASS prediction for primally observation having active value against virus with the main protease (Mpro) of acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Besides, the pharmacokinetics and Lipinski's rule of five (RO5) were evaluated for all molecules being drug likeness properties, and then these were selected for molecular docking against the Mpro of corona virus, and L-03, L-07, and L-13 found the best-bonded molecules accounting weak H bonding and hydrophobic bond interactions. In addition, on the binding energies of Mpro, L-3, L-7, L-13, L-18, L-25, L-26, L-34, L-39, L-42, and L-49 were at -8.6, -8.3, 8.2, -8.1, -8.0, -7.9, -7.9, -7.9, and -7.9 kcal/mol. Overall, L-3 is considerable best candidate with Mpro in view of the molecular docking score. In addition, the quantum properties, chemical hardness and softness values were calculated. Finally, from admetSAR online database, absorption, distribution, metabolism, excretion, and toxicity (ADMET) were evaluated. Lastly, L-3, L7, and L-13 were satisfied the toxicity category. In comparison to the World Health Organization (WHO) guidelines, FDA-approved antiviral drugs, favipiravir and remdesivir, which have binding energies of -5.1 and -8.1 kcal/mol of the Mpro, respectively. In this case, our selected L-3, L-7, L-13, and L-18 have binding energies of -8.6, -8.3, -8.2, and -8.2 kcal/mol, respectively. Thus, the L-3, L-7, L-13 and L-18 molecules will have strong activity against the SARS-CoV-2. Sami Publishing Company 2023 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/39218/1/Identification%20of%20SARS-CoV-2%20inhibitors%20from%20alkaloids%20using%20molecular%20modeling%20and%20in%20silico%20approaches.pdf Roni, Md Abul Hasan and Mortuza, Md. Golam and Rozina, . and Shaha, Ripon Kumar and Hoque, Sajidul and Kumer, Ajoy (2023) Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches. Journal of Medicinal and Nanomaterials Chemistry, 4. 252 -266. ISSN 2981-0825. (In Press / Online First) (In Press / Online First) https://jmnc.samipubco.com/article_182354.html |
| spellingShingle | QD Chemistry TP Chemical technology Roni, Md Abul Hasan Mortuza, Md. Golam Rozina, . Shaha, Ripon Kumar Hoque, Sajidul Kumer, Ajoy Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| title | Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| title_full | Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| title_fullStr | Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| title_full_unstemmed | Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| title_short | Identification of SARS-CoV-2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| title_sort | identification of sars cov 2 inhibitors from alkaloids using molecular modeling and in silico approaches |
| topic | QD Chemistry TP Chemical technology |
| url | http://umpir.ump.edu.my/id/eprint/39218/1/Identification%20of%20SARS-CoV-2%20inhibitors%20from%20alkaloids%20using%20molecular%20modeling%20and%20in%20silico%20approaches.pdf |
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