Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19
Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro<i>,</i> and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Antibiotics |
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| Online Access: | https://www.mdpi.com/2079-6382/10/7/856 |
| _version_ | 1797527751866974208 |
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| author | Faizul Azam |
| author_facet | Faizul Azam |
| author_sort | Faizul Azam |
| collection | DOAJ |
| description | Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro<i>,</i> and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were employed to decrypt the mechanistic insight of teicoplanin interaction with several COVID-19 drug targets. Initially, molecular docking was employed to study the teicoplanin interaction with twenty-five SARS-CoV-2 structural and non-structural proteins which was followed by molecular mechanics/generalized Born surface area (MM/GBSA) computation for binding energy predictions of top ten models from each target. Amongst all macromolecular targets, the N-terminal domain of the nucleocapsid protein displayed the strongest affinity with teicoplanin showing binding energies of −7.4 and −102.13 kcal/mol, in docking and Prime MM/GBSA, respectively. Thermodynamic stability of the teicoplanin-nucleocapsid protein was further probed by molecular dynamics simulations of protein–ligand complex as well as unbounded protein in 100 ns trajectories. Post-simulation MM-GBSA computation of 50 frames extracted from simulated trajectories estimated an average binding energy of −62.52 ± 12.22 kcal/mol. In addition, conformational state of protein in complex with docked teicoplanin displayed stable root-mean-square deviation/fluctuation. In conclusion, computational investigation of the potential targets of COVID-19 and their interaction mechanism with teicoplanin can guide the design of novel therapeutic armamentarium for the treatment of SARS-CoV-2 infection. However, additional studies are warranted to establish the clinical use or relapses, if any, of teicoplanin in the therapeutic management of COVID-19 patients. |
| first_indexed | 2024-03-10T09:48:16Z |
| format | Article |
| id | doaj.art-b8292e94846c4938b24e2441b4d494d9 |
| institution | Directory Open Access Journal |
| issn | 2079-6382 |
| language | English |
| last_indexed | 2024-03-10T09:48:16Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Antibiotics |
| spelling | doaj.art-b8292e94846c4938b24e2441b4d494d92023-11-22T03:04:19ZengMDPI AGAntibiotics2079-63822021-07-0110785610.3390/antibiotics10070856Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19Faizul Azam0Department of Pharmaceutical Chemistry & Pharmacognosy, Unaizah College of Pharmacy, Qassim University, Unaizah 51911, Saudi ArabiaTeicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro<i>,</i> and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were employed to decrypt the mechanistic insight of teicoplanin interaction with several COVID-19 drug targets. Initially, molecular docking was employed to study the teicoplanin interaction with twenty-five SARS-CoV-2 structural and non-structural proteins which was followed by molecular mechanics/generalized Born surface area (MM/GBSA) computation for binding energy predictions of top ten models from each target. Amongst all macromolecular targets, the N-terminal domain of the nucleocapsid protein displayed the strongest affinity with teicoplanin showing binding energies of −7.4 and −102.13 kcal/mol, in docking and Prime MM/GBSA, respectively. Thermodynamic stability of the teicoplanin-nucleocapsid protein was further probed by molecular dynamics simulations of protein–ligand complex as well as unbounded protein in 100 ns trajectories. Post-simulation MM-GBSA computation of 50 frames extracted from simulated trajectories estimated an average binding energy of −62.52 ± 12.22 kcal/mol. In addition, conformational state of protein in complex with docked teicoplanin displayed stable root-mean-square deviation/fluctuation. In conclusion, computational investigation of the potential targets of COVID-19 and their interaction mechanism with teicoplanin can guide the design of novel therapeutic armamentarium for the treatment of SARS-CoV-2 infection. However, additional studies are warranted to establish the clinical use or relapses, if any, of teicoplanin in the therapeutic management of COVID-19 patients.https://www.mdpi.com/2079-6382/10/7/856SARS-CoV-2teicoplanindockingmolecular dynamicsMM/GBSA |
| spellingShingle | Faizul Azam Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 Antibiotics SARS-CoV-2 teicoplanin docking molecular dynamics MM/GBSA |
| title | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
| title_full | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
| title_fullStr | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
| title_full_unstemmed | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
| title_short | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
| title_sort | elucidation of teicoplanin interactions with drug targets related to covid 19 |
| topic | SARS-CoV-2 teicoplanin docking molecular dynamics MM/GBSA |
| url | https://www.mdpi.com/2079-6382/10/7/856 |
| work_keys_str_mv | AT faizulazam elucidationofteicoplanininteractionswithdrugtargetsrelatedtocovid19 |