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Kumar P, Parveen, Raj N, Kumar M, Fakhri KU, Kumar S, Khan AA, Alanazi AM, Solanki R, Harsha, Manzoor N, Kapur MK. Natural products from Streptomyces spp. as potential inhibitors of the major factors (holoRdRp and nsp13) for SARS-CoV-2 replication: an in silico approach. Arch Microbiol 2024; 206:88. [PMID: 38305873 DOI: 10.1007/s00203-023-03820-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/27/2023] [Accepted: 12/27/2023] [Indexed: 02/03/2024]
Abstract
The COVID-19 pandemic caused unprecedented damage to humanity, and while vaccines have been developed, they are not fully effective against the SARS-CoV-2 virus. Limited targeted drugs, such as Remdesivir and Paxlovid, are available against the virus. Hence, there is an urgent need to explore and develop new drugs to combat COVID-19. This study focuses on exploring microbial natural products from soil-isolated bacteria Streptomyces sp. strain 196 and RI.24 as a potential source of new targeted drugs against SARS-CoV-2. Molecular docking studies were performed on holoRdRp and nsp13, two key factors responsible for virus replication factor. Our in silico studies, K-252-C aglycone indolocarbazole alkaloid (K252C) and daunorubicin were found to have better binding affinities than the respective control drugs, with K252C exhibiting binding energy of - 9.1 kcal/mol with holoRdRp and - 9.2 kcal/mol with nsp13, and daunorubicin showing binding energy at - 8.1 kcal/mol with holoRdRp and - 9.3 kcal/mol with nsp13. ADMET analysis, MD simulation, and MM/GBSA studies indicated that K252C and daunorubicin have the potential to be developed as targeted drugs against SARS-CoV-2. The study concludes that K252C and daunorubicin are potential lead compounds that might suppress the inhibition of SARS-CoV-2 replication among the tested microbial compounds and could be developed as targeted drugs against COVID-19. In the future, further in vitro studies are required to validate these findings.
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Affiliation(s)
- Prateek Kumar
- Department of Zoology, University of Allahabad, Uttar Pradesh, Prayagraj, 211 002, India.
| | - Parveen
- Medical Mycology Laboratory, Department of Biosciences, Jamia Millia Islamia, New Delhi, 110025, India
| | - Nafis Raj
- Medical Mycology Laboratory, Department of Biosciences, Jamia Millia Islamia, New Delhi, 110025, India
| | - Munendra Kumar
- Department of Zoology, Rajiv Gandhi University, Doimukh, 791112, Arunachal Pradesh, India
| | - Khalid Umar Fakhri
- Department of Biosciences, Jamia Millia Islamia, New Delhi, 110025, India
| | - Sugandh Kumar
- School of Medicine, University of San Francisco California (UCSF), San Francisco, CA, 95115, USA
| | - Azmat Ali Khan
- Pharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, 11451, Riyadh, Saudi Arabia
| | - Amer M Alanazi
- Pharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, 11451, Riyadh, Saudi Arabia
| | - Renu Solanki
- Deen Dayal Upadhyaya College, University of Delhi, New Delhi, 110 078, India
| | - Harsha
- Microbial Technology Lab, Acharya Narendra Dev College, University of Delhi, New Delhi, 110 019, India
| | - Nikhat Manzoor
- Medical Mycology Laboratory, Department of Biosciences, Jamia Millia Islamia, New Delhi, 110025, India
| | - Monisha Khanna Kapur
- Microbial Technology Lab, Acharya Narendra Dev College, University of Delhi, New Delhi, 110 019, India.
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Liang JJ, Pitsillou E, Hung A, Karagiannis TC. A repository of COVID-19 related molecular dynamics simulations and utilisation in the context of nsp10-nsp16 antivirals. J Mol Graph Model 2024; 126:108666. [PMID: 37976980 DOI: 10.1016/j.jmgm.2023.108666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/31/2023] [Accepted: 11/01/2023] [Indexed: 11/19/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of establishing systems and infrastructure to develop vaccines, antiviral drugs, and therapeutic antibodies against emerging pathogens. Typical drug discovery processes involve targeting suitable proteins to effect pathogen replication or to attenuate host responses, by examining either large chemical databases or protein-protein interactions. Following initial screens, molecular dynamics (MD) simulations are critical for gaining further insight into molecular interactions. During the COVID-19 pandemic, many research groups made their simulations widely available, as highlighted by the comprehensive D.E. Shaw Research trajectory database. To investigate protein target sites and evaluate potential lead compounds, we performed over 300 MD simulations relating to COVID-19. We organised our simulations into a repository, which is publicly available at https://epimedlab.org/trajectories/. The trajectories cover a large part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome, and the majority of our MD simulations focused on the identification of potential antivirals. For example, we focused on the S-adenosyl-l-methionine binding site of the nsp10-nsp16 complex, a critical component of viral replication, revealing verbascoside as a potential lead. Moreover, we utilised MD trajectories to explore the interface between the spike protein receptor binding domain and human angiotensin-converting enzyme 2 receptor, with the ultimate aim being investigation of new variants in real-time. Overall, MD simulations are a critical component of the in silico drug discovery process and as highlighted throughout the pandemic, data sharing enables accelerated progress. We have organised our extensive collection of COVID-19 related MD trajectories into an easily accessible repository.
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Affiliation(s)
- Julia J Liang
- Epigenetics in Human Health and Disease Program, Baker Heart and Diabetes Institute, 75 Commercial Road, Prahran, VIC, 3004, Australia; Epigenomic Medicine Laboratory at prospED Training, Carlton, VIC, 3053, Australia; School of Science, STEM College, RMIT University, VIC, 3001, Australia
| | - Eleni Pitsillou
- Epigenomic Medicine Laboratory at prospED Training, Carlton, VIC, 3053, Australia; School of Science, STEM College, RMIT University, VIC, 3001, Australia
| | - Andrew Hung
- School of Science, STEM College, RMIT University, VIC, 3001, Australia
| | - Tom C Karagiannis
- Epigenetics in Human Health and Disease Program, Baker Heart and Diabetes Institute, 75 Commercial Road, Prahran, VIC, 3004, Australia; Epigenomic Medicine Laboratory at prospED Training, Carlton, VIC, 3053, Australia; Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, 3010, Australia; Department of Microbiology and Immunology, The University of Melbourne, Parkville, VIC, 3010, Australia.
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Yang CR, Chang SY, Gong YN, Huang CG, Tung TH, Liu W, Chan TC, Hung KS, Shang HS, Tsai JJ, Kao CL, Wu HL, Daisy Liu LY, Lin WY, Fan YC, King CC, Ku CC. The emergence and successful elimination of SARS-CoV-2 dominant strains with increasing epidemic potential in Taiwan's 2021 outbreak. Heliyon 2023; 9:e22436. [PMID: 38107297 PMCID: PMC10724543 DOI: 10.1016/j.heliyon.2023.e22436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 11/10/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023] Open
Abstract
Taiwan's experience with severe acute respiratory syndrome coronavirus (SARS-CoV) in 2003 guided its development of strategies to defend against SARS-CoV-2 in 2020, which enabled the successful control of Coronavirus disease 2019 (COVID-19) cases from 2020 through March 2021. However, in late-April 2021, the imported Alpha variant began to cause COVID-19 outbreaks at an exceptional rate in Taiwan. In this study, we aimed to determine what epidemiological conditions enabled the SARS-CoV-2 Alpha variant strains to become dominant and decline later during a surge in the outbreak. In conjunction with contact-tracing investigations, we used our bioinformatics software, CoVConvert and IniCoV, to analyze whole-genome sequences of 101 Taiwan Alpha strains. Univariate and multivariable regression analyses revealed the epidemiological factors associated with viral dominance. Univariate analysis showed the dominant Alpha strains were preferentially selected in the surge's epicenter (p = 0.0024) through intensive human-to-human contact and maintained their dominance for 1.5 months until the Zero-COVID Policy was implemented. Multivariable regression found that the epidemic periods (p = 0.007) and epicenter (p = 0.001) were two significant factors associated with the dominant virus strains spread in the community. These dominant virus strains emerged at the outbreak's epicenter with frequent human-to-human contact and low vaccination coverage. The Level 3 Restrictions and Zero-COVID policy successfully controlled the outbreak in the community without city lockdowns. Our integrated method can identify the epidemiological conditions for emerging dominant virus with increasing epidemiological potential and support decision makers in rapidly containing outbreaks using public health measures that target fast-spreading virus strains.
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Affiliation(s)
- Chin-Rur Yang
- Graduate Institute of Immunology, College of Medicine, National Taiwan University, 1 Jen-Ai Road Section 1, Taipei, 10051, Taiwan, ROC
| | - Sui-Yuan Chang
- Department (Dept.) of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, 10051, Taiwan, ROC
- Dept. of Laboratory Medicine, National Taiwan University Hospital, Taipei, 10051, Taiwan, ROC
| | - Yu-Nong Gong
- Research Center for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan, 33302, Taiwan, ROC
- Dept. of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, 33302, Taiwan, ROC
| | - Chung-Guei Huang
- Dept. of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, 33302, Taiwan, ROC
- Dept. of Medical Biotechnology and Laboratory Science, College of Medicine, Chang Gung University, Taoyuan, 33302, Taiwan, ROC
| | - Tsung-Hua Tung
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, NTU 17 Xu-Zhou Road, Taipei, 10055, Taiwan, ROC
- Dept. of Health, Taipei City Government, Taipei, Taiwan, ROC
| | - Wei Liu
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, NTU 17 Xu-Zhou Road, Taipei, 10055, Taiwan, ROC
| | - Ta-Chien Chan
- Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, 11529, Taiwan, ROC
| | - Kuo-Sheng Hung
- Center for Precision Medicine and Genomics, Tri-Service General Hospital, National Defense Medical Center, Taipei, 11490, Taiwan, ROC
| | - Hung-Sheng Shang
- Division of Clinical Pathology, Dept. of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 11490, Taiwan, ROC
| | - Jih-Jin Tsai
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan, ROC
- Tropical Medicine Center, Kaohsiung Medical University Hospital, Kaohsiung, 80756, Taiwan, ROC
- Division of Infectious Diseases, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, 80756, Taiwan, ROC
| | - Chuan-Liang Kao
- Department (Dept.) of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, 10051, Taiwan, ROC
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, NTU 17 Xu-Zhou Road, Taipei, 10055, Taiwan, ROC
| | - Hui-Lin Wu
- Hepatitis Research Center, National Taiwan University Hospital, Taipei, 10051, Taiwan, ROC
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, 10051, Taiwan, ROC
| | - Li-Yu Daisy Liu
- Division of Biometry, Department of Agronomy, National Taiwan University, Taipei, 10617, Taiwan, ROC
| | - Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, NTU 17 Xu-Zhou Road, Taipei, 10055, Taiwan, ROC
| | - Yi-Chin Fan
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, NTU 17 Xu-Zhou Road, Taipei, 10055, Taiwan, ROC
| | - Chwan-Chuen King
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, NTU 17 Xu-Zhou Road, Taipei, 10055, Taiwan, ROC
| | - Chia-Chi Ku
- Graduate Institute of Immunology, College of Medicine, National Taiwan University, 1 Jen-Ai Road Section 1, Taipei, 10051, Taiwan, ROC
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Kartchner D, McCoy K, Dubey J, Zhang D, Zheng K, Umrani R, Kim JJ, Mitchell CS. Literature-Based Discovery to Elucidate the Biological Links between Resistant Hypertension and COVID-19. BIOLOGY 2023; 12:1269. [PMID: 37759668 PMCID: PMC10526006 DOI: 10.3390/biology12091269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/11/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023]
Abstract
Multiple studies have reported new or exacerbated persistent or resistant hypertension in patients previously infected with COVID-19. We used literature-based discovery to identify and prioritize multi-scalar explanatory biology that relates resistant hypertension to COVID-19. Cross-domain text mining of 33+ million PubMed articles within a comprehensive knowledge graph was performed using SemNet 2.0. Unsupervised rank aggregation determined which concepts were most relevant utilizing the normalized HeteSim score. A series of simulations identified concepts directly related to COVID-19 and resistant hypertension or connected via one of three renin-angiotensin-aldosterone system hub nodes (mineralocorticoid receptor, epithelial sodium channel, angiotensin I receptor). The top-ranking concepts relating COVID-19 to resistant hypertension included: cGMP-dependent protein kinase II, MAP3K1, haspin, ral guanine nucleotide exchange factor, N-(3-Oxododecanoyl)-L-homoserine lactone, aspartic endopeptidases, metabotropic glutamate receptors, choline-phosphate cytidylyltransferase, protein tyrosine phosphatase, tat genes, MAP3K10, uridine kinase, dicer enzyme, CMD1B, USP17L2, FLNA, exportin 5, somatotropin releasing hormone, beta-melanocyte stimulating hormone, pegylated leptin, beta-lipoprotein, corticotropin, growth hormone-releasing peptide 2, pro-opiomelanocortin, alpha-melanocyte stimulating hormone, prolactin, thyroid hormone, poly-beta-hydroxybutyrate depolymerase, CR 1392, BCR-ABL fusion gene, high density lipoprotein sphingomyelin, pregnancy-associated murine protein 1, recQ4 helicase, immunoglobulin heavy chain variable domain, aglycotransferrin, host cell factor C1, ATP6V0D1, imipramine demethylase, TRIM40, H3C2 gene, COL1A1+COL1A2 gene, QARS gene, VPS54, TPM2, MPST, EXOSC2, ribosomal protein S10, TAP-144, gonadotropins, human gonadotropin releasing hormone 1, beta-lipotropin, octreotide, salmon calcitonin, des-n-octanoyl ghrelin, liraglutide, gastrins. Concepts were mapped to six physiological themes: altered endocrine function, 23.1%; inflammation or cytokine storm, 21.3%; lipid metabolism and atherosclerosis, 17.6%; sympathetic input to blood pressure regulation, 16.7%; altered entry of COVID-19 virus, 14.8%; and unknown, 6.5%.
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Affiliation(s)
- David Kartchner
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Kevin McCoy
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Janhvi Dubey
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Dongyu Zhang
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Kevin Zheng
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Rushda Umrani
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - James J. Kim
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Cassie S. Mitchell
- Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Center for Machine Learning at Georgia Tech, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding. Sci Rep 2023; 13:3643. [PMID: 36871056 PMCID: PMC9985643 DOI: 10.1038/s41598-023-30095-z] [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: 09/26/2022] [Accepted: 02/15/2023] [Indexed: 03/06/2023] Open
Abstract
The search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns "ensemble embeddings" of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.
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Halma MTJ, Wever MJA, Abeln S, Roche D, Wuite GJL. Therapeutic potential of compounds targeting SARS-CoV-2 helicase. Front Chem 2022; 10:1062352. [PMID: 36561139 PMCID: PMC9763700 DOI: 10.3389/fchem.2022.1062352] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022] Open
Abstract
The economical and societal impact of COVID-19 has made the development of vaccines and drugs to combat SARS-CoV-2 infection a priority. While the SARS-CoV-2 spike protein has been widely explored as a drug target, the SARS-CoV-2 helicase (nsp13) does not have any approved medication. The helicase shares 99.8% similarity with its SARS-CoV-1 homolog and was shown to be essential for viral replication. This review summarizes and builds on existing research on inhibitors of SARS-CoV-1 and SARS-CoV-2 helicases. Our analysis on the toxicity and specificity of these compounds, set the road going forward for the repurposing of existing drugs and the development of new SARS-CoV-2 helicase inhibitors.
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Affiliation(s)
- Matthew T. J. Halma
- Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- LUMICKS B. V., Amsterdam, Netherlands
| | - Mark J. A. Wever
- DCM, University of Grenoble Alpes, Grenoble, France
- Edelris, Lyon, France
| | - Sanne Abeln
- Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Gijs J. L. Wuite
- Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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