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Haghir Ebrahim Abadi MH, Ghasemlou A, Bayani F, Sefidbakht Y, Vosough M, Mozaffari-Jovin S, Uversky VN. AI-driven covalent drug design strategies targeting main protease (m pro) against SARS-CoV-2: structural insights and molecular mechanisms. J Biomol Struct Dyn 2024:1-29. [PMID: 38287509 DOI: 10.1080/07391102.2024.2308769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/17/2024] [Indexed: 01/31/2024]
Abstract
The emergence of new SARS-CoV-2 variants has raised concerns about the effectiveness of COVID-19 vaccines. To address this challenge, small-molecule antivirals have been proposed as a crucial therapeutic option. Among potential targets for anti-COVID-19 therapy, the main protease (Mpro) of SARS-CoV-2 is important due to its essential role in the virus's life cycle and high conservation. The substrate-binding region of the core proteases of various coronaviruses, including SARS-CoV-2, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV), could be used for the generation of new protease inhibitors. Various drug discovery methods have employed a diverse range of strategies, targeting both monomeric and dimeric forms, including drug repurposing, integrating virtual screening with high-throughput screening (HTS), and structure-based drug design, each demonstrating varying levels of efficiency. Covalent inhibitors, such as Nirmatrelvir and MG-101, showcase robust and high-affinity binding to Mpro, exhibiting stable interactions confirmed by molecular docking studies. Development of effective antiviral drugs is imperative to address potential pandemic situations. This review explores recent advances in the search for Mpro inhibitors and the application of artificial intelligence (AI) in drug design. AI leverages vast datasets and advanced algorithms to streamline the design and identification of promising Mpro inhibitors. AI-driven drug discovery methods, including molecular docking, predictive modeling, and structure-based drug repurposing, are at the forefront of identifying potential candidates for effective antiviral therapy. In a time when COVID-19 potentially threat global health, the quest for potent antiviral solutions targeting Mpro could be critical for inhibiting the virus.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
| | | | - Fatemeh Bayani
- Protein Research Center, Shahid Beheshti University, Tehran, Iran
| | - Yahya Sefidbakht
- Protein Research Center, Shahid Beheshti University, Tehran, Iran
| | - Massoud Vosough
- Department of Regenerative Medicine, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
| | - Sina Mozaffari-Jovin
- Department of Medical Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Vladimir N Uversky
- Department of Molecular Medicine, University of South Florida, Tampa, FL, USA
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Khan N, Rehman B, Almanaa TN, Aljahdali SM, Waheed Y, Ullah A, Asfandayar M, Al-Harbi AI, Naz T, Arshad M, Sanami S, Ahmad S. A novel therapeutic approach to prevent Helicobacter pylori induced gastric cancer using networking biology, molecular docking, and simulation approaches. J Biomol Struct Dyn 2023:1-14. [PMID: 37962871 DOI: 10.1080/07391102.2023.2279276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 10/27/2023] [Indexed: 11/15/2023]
Abstract
Helicobacter pylori infects 50% of the world population and in 80% of cases, the infection progresses to the point where an ulcer develops leading to gastric cancer (GC). This study aimed to prevent GC by predicting Hub genes that are inducing GC. Furthermore, the study objective was to screen inhibitory molecules that block the function of predicted genes through several biophysical approaches. These proteins, such as Mucin 4 (MUC4) and Baculoviral IAP repeat containing 3 (BIRC3), had LogFC values of 2.28 and 3.39, respectively, and were found to be substantially expressed in those who had H. pylori infection. The MUC4 and BIRC3 inhibit apoptosis of infected cells and promote cancerous cell survival. The proteins were examined for their Physico-chemical characteristics, 3D structure and secondary structure analysis, solvent assessable surface area (SASA), active site identification, and network analysis. The MUC4 and BIRC3 expression was inhibited by docking eighty different compounds collected from the ZINC database. Fifty-seven compounds were successfully docked into the active site resulting in the lowest binding energy scores. The ZINC585267910 and ZINC585268691 compounds showed the lowest binding energy of -8.5 kcal/mol for MUC4 and -7.1 kcal/mol for BIRC3, respectively, and were considered best-docked solutions for molecular dynamics simulations. The mean root mean square deviation (RMSD) value for the ZINC585267910-MUC4 complex was 0.86 Å and the ZINC585268691-BIRC3 complex was 1.01 Å. The net MM/GBSA energy value of the ZINC585267910-MUC4 complex estimated was -46.84 kcal/mol and that of the ZINC585268691-BIRC3 complex was -44.84 kcal/mol. In a nutshell, the compounds might be investigated further as an inhibitor of the said proteins to stop the progress of GC induced by H. pylori.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Nadeem Khan
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan
| | - Bushra Rehman
- Institute of Biotechnology and Microbiology, Bacha Khan University, Charsadaa, Pakistan
| | - Taghreed N Almanaa
- Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | | | - Yasir Waheed
- Office of Research, Innovation and Commercialization, Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad, Pakistan
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
| | - Asad Ullah
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan
| | - Muhammad Asfandayar
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan
| | - Alhanouf I Al-Harbi
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, Saudi Arabia
| | - Tahira Naz
- Department of Chemical and Life Sciences, Qurtuba University of Science and Technology, Peshawar, Pakistan
| | - Muhammad Arshad
- Center of Biotechnology and Microbiology, University of Peshawar, Peshawar, Pakistan
| | - Samira Sanami
- Nervous System Stem Cells Research Center, Semnan University of Medical Sciences, Semnan, Iran
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan
- Department of Computer Science, Virginia Tech, Blacksburg, VA, USA
- Department of Natural Sciences, Lebanese American University, Beirut, Lebanon
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