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Hussein HAM, Thabet AA, Wardany AA, El-Adly AM, Ali M, Hassan MEA, Abdeldayem MAB, Mohamed ARMA, Sobhy A, El-Mokhtar MA, Afifi MM, Fathy SM, Sultan S. SARS-CoV-2 outbreak: role of viral proteins and genomic diversity in virus infection and COVID-19 progression. Virol J 2024; 21:75. [PMID: 38539202 PMCID: PMC10967059 DOI: 10.1186/s12985-024-02342-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 03/12/2024] [Indexed: 05/15/2024] Open
Abstract
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is the cause of coronavirus disease 2019 (COVID-19); a severe respiratory distress that has emerged from the city of Wuhan, Hubei province, China during December 2019. COVID-19 is currently the major global health problem and the disease has now spread to most countries in the world. COVID-19 has profoundly impacted human health and activities worldwide. Genetic mutation is one of the essential characteristics of viruses. They do so to adapt to their host or to move to another one. Viral genetic mutations have a high potentiality to impact human health as these mutations grant viruses unique unpredicted characteristics. The difficulty in predicting viral genetic mutations is a significant obstacle in the field. Evidence indicates that SARS-CoV-2 has a variety of genetic mutations and genomic diversity with obvious clinical consequences and implications. In this review, we comprehensively summarized and discussed the currently available knowledge regarding SARS-CoV-2 outbreaks with a fundamental focus on the role of the viral proteins and their mutations in viral infection and COVID-19 progression. We also summarized the clinical implications of SARS-CoV-2 variants and how they affect the disease severity and hinder vaccine development. Finally, we provided a massive phylogenetic analysis of the spike gene of 214 SARS-CoV-2 isolates from different geographical regions all over the world and their associated clinical implications.
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Affiliation(s)
- Hosni A M Hussein
- Department of Microbiology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt.
| | - Ali A Thabet
- Department of Zoology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt
| | - Ahmed A Wardany
- Department of Microbiology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt
| | - Ahmed M El-Adly
- Department of Microbiology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt
| | - Mohamed Ali
- Department of Microbiology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt
| | - Mohamed E A Hassan
- Department of Microbiology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt
| | - Mohamed A B Abdeldayem
- Department of Microbiology, Faculty of Science, Al-Azhar University, 71524, Assiut, Egypt
| | | | - Ali Sobhy
- Department of Clinical Pathology, Faculty of Medicine, Al-Azhar University, 71524, Assiut, Egypt
| | - Mohamed A El-Mokhtar
- Department of Medical Microbiology and Immunology, Faculty of Medicine, Assiut University, Assiut, Egypt
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos Campus, Lebanon
| | - Magdy M Afifi
- Department of Botany and Microbiology, Faculty of Science, Al-Azhar University, Nasr City 11884, Cairo, Egypt
| | - Samah M Fathy
- Department of Zoology, Faculty of Science, Fayoum University, Fayoum, Egypt.
| | - Serageldeen Sultan
- Department of Microbiology, Virology Division, Faculty of Veterinary medicine, South Valley University, 83523, Qena, Egypt.
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2
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Wu T, Yu JC, Suresh A, Gale-Day ZJ, Alteen MG, Woo AS, Millbern Z, Johnson OT, Carroll EC, Partch CL, Fourches D, Vinueza NR, Vocadlo DJ, Gestwicki JE. Conformationally responsive dyes enable protein-adaptive differential scanning fluorimetry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.23.525251. [PMID: 36747624 PMCID: PMC9900766 DOI: 10.1101/2023.01.23.525251] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Flexible in vitro methods alter the course of biological discoveries. Differential Scanning Fluorimetry (DSF) is a particularly versatile technique which reports protein thermal unfolding via fluorogenic dye. However, applications of DSF are limited by widespread protein incompatibilities with the available DSF dyes. Here, we enable DSF applications for 66 of 70 tested proteins (94%) including 10 from the SARS-CoV2 virus using a chemically diverse dye library, Aurora, to identify compatible dye-protein pairs in high throughput. We find that this protein-adaptive DSF platform (paDSF) not only triples the previous protein compatibility, but also fundamentally extends the processes observable by DSF, including interdomain allostery in O-GlcNAc Transferase (OGT). paDSF enables routine measurement of protein stability, dynamics, and ligand binding.
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Affiliation(s)
- Taiasean Wu
- Department of Pharmaceutical Chemistry, University of California San Francisco; San Francisco, CA, 94038, USA
- Institute for Neurodegenerative Diseases, University of California, San Francisco; San Francisco, CA, 94038, USA
| | - Joshua C. Yu
- Department of Pharmaceutical Chemistry, University of California San Francisco; San Francisco, CA, 94038, USA
| | - Arundhati Suresh
- Department of Pharmaceutical Chemistry, University of California San Francisco; San Francisco, CA, 94038, USA
| | - Zachary J. Gale-Day
- Department of Pharmaceutical Chemistry, University of California San Francisco; San Francisco, CA, 94038, USA
| | - Matthew G. Alteen
- Department of Chemistry, Simon Fraser University; Burnaby, BC V5A 1S6, Canada
| | - Amanda S. Woo
- Department of Pharmaceutical Chemistry, University of California San Francisco; San Francisco, CA, 94038, USA
| | - Zoe Millbern
- Department of Textile Engineering, North Carolina State University; Raleigh, NC 27695, USA
| | - Oleta T. Johnson
- Institute for Neurodegenerative Diseases, University of California, San Francisco; San Francisco, CA, 94038, USA
| | - Emma C. Carroll
- Institute for Neurodegenerative Diseases, University of California, San Francisco; San Francisco, CA, 94038, USA
| | - Carrie L. Partch
- Department of Chemistry, University of California, Santa Cruz; Santa Cruz, CA, 95064, USA
| | - Denis Fourches
- Department of Textile Engineering, North Carolina State University; Raleigh, NC 27695, USA
| | - Nelson R. Vinueza
- Department of Textile Engineering, North Carolina State University; Raleigh, NC 27695, USA
| | - David J. Vocadlo
- Department of Chemistry, Simon Fraser University; Burnaby, BC V5A 1S6, Canada
- Department of Molecular Biology and Biochemistry, Simon Fraser University; Burnaby, BC V5A 1S6, Canada
| | - Jason E. Gestwicki
- Department of Pharmaceutical Chemistry, University of California San Francisco; San Francisco, CA, 94038, USA
- Institute for Neurodegenerative Diseases, University of California, San Francisco; San Francisco, CA, 94038, USA
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3
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Mok PL, Koh AEH, Farhana A, Alsrhani A, Alam MK, Suresh Kumar S. Computational drug screening against the SARS-CoV-2 Saudi Arabia isolates through a multiple-sequence alignment approach. Saudi J Biol Sci 2021; 28:2502-2509. [PMID: 33551661 PMCID: PMC7845492 DOI: 10.1016/j.sjbs.2021.01.051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/19/2021] [Accepted: 01/21/2021] [Indexed: 11/18/2022] Open
Abstract
COVID-19 is a rapidly emerging infectious disease caused by the SARS-CoV-2 virus currently spreading throughout the world. To date, there are no specific drugs formulated for it, and researchers around the globe are racing against the clock to investigate potential drug candidates. The repurposing of existing drugs in the market represents an effective and economical strategy commonly utilized in such investigations. In this study, we used a multiple-sequence alignment approach for preliminary screening of commercially-available drugs on SARS-CoV sequences from the Kingdom of Saudi Arabia (KSA) isolates. The viral genomic sequences from KSA isolates were obtained from GISAID, an open access repository housing a wide variety of epidemic and pandemic virus data. A phylogenetic analysis of the present 164 sequences from the KSA provinces was carried out using the MEGA X software, which displayed high similarity (around 98%). The sequence was then analyzed using the VIGOR4 genome annotator to construct its genomic structure. Screening of existing drugs was carried out by mining data based on viral gene expressions from the ZINC database. A total of 73 hits were generated. The viral target orthologs were mapped to the SARS-CoV-2 KSA isolate sequence by multiple sequence alignment using CLUSTAL OMEGA, and a list of 29 orthologs with purchasable drug information was generated. The results showed that the SARS CoV replicase polyprotein 1a had the highest sequence similarity at 79.91%. Through ZINC data mining, tanshinones were found to have high binding affinities to this target. These compounds could be ideal candidates for SARS-CoV-2. Other matches ranged between 27 and 52%. The results of this study would serve as a significant endeavor towards drug discovery that would increase our chances of finding an effective treatment or prevention against COVID19.
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Affiliation(s)
- Pooi Ling Mok
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
- Genetics and Regenerative Medicine Research Centre, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
| | - Avin Ee-Hwan Koh
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
| | - Aisha Farhana
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia
| | - Abdullah Alsrhani
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia
| | - Mohammad Khursheed Alam
- Department of Orthodontics, College of Dentistry, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia
| | - Subbiah Suresh Kumar
- Genetics and Regenerative Medicine Research Centre, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
- Department of Medical Microbiology and Parasitology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
- UPM-MAKNA Cancer Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang 43400 UPM, Selangor, Malaysia
- Department of Biotechnology, Bharath Institute of Higher Education and Research, Bharath University, Selaiyur, Chennai 600073, Tamil Nadu, India
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Schuller M, Correy GJ, Gahbauer S, Fearon D, Wu T, Díaz RE, Young ID, Martins LC, Smith DH, Schulze-Gahmen U, Owens TW, Deshpande I, Merz GE, Thwin AC, Biel JT, Peters JK, Moritz M, Herrera N, Kratochvil HT, Aimon A, Bennett JM, Neto JB, Cohen AE, Dias A, Douangamath A, Dunnett L, Fedorov O, Ferla MP, Fuchs M, Gorrie-Stone TJ, Holton JM, Johnson MG, Krojer T, Meigs G, Powell AJ, Rangel VL, Russi S, Skyner RE, Smith CA, Soares AS, Wierman JL, Zhu K, Jura N, Ashworth A, Irwin J, Thompson MC, Gestwicki JE, von Delft F, Shoichet BK, Fraser JS, Ahel I. Fragment Binding to the Nsp3 Macrodomain of SARS-CoV-2 Identified Through Crystallographic Screening and Computational Docking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.11.24.393405. [PMID: 33269349 PMCID: PMC7709169 DOI: 10.1101/2020.11.24.393405] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The SARS-CoV-2 macrodomain (Mac1) within the non-structural protein 3 (Nsp3) counteracts host-mediated antiviral ADP-ribosylation signalling. This enzyme is a promising antiviral target because catalytic mutations render viruses non-pathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of diverse fragment libraries resulted in 214 unique macrodomain-binding fragments, out of 2,683 screened. An additional 60 molecules were selected from docking over 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several crystallographic and docking fragment hits were validated for solution binding using three biophysical techniques (DSF, HTRF, ITC). Overall, the 234 fragment structures presented explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.
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Affiliation(s)
- Marion Schuller
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
| | - Galen J. Correy
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
| | - Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
| | - Daren Fearon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Taiasean Wu
- Institute for Neurodegenerative Disease, University of California San Francisco, CA, USA
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, CA, USA
| | - Roberto Efraín Díaz
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
- Tetrad Graduate Program, University of California San Francisco, CA, USA
| | - Iris D. Young
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Luan Carvalho Martins
- Biochemistry Department, Institute for Biological Sciences, Federal University of Minas Gerais. Belo Horizonte, Brazil
| | - Dominique H. Smith
- Helen Diller Family Comprehensive Cancer, University of California San Francisco, CA, USA
| | - Ursula Schulze-Gahmen
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Tristan W. Owens
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Ishan Deshpande
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Gregory E. Merz
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Aye C. Thwin
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Justin T. Biel
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Jessica K. Peters
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Michelle Moritz
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Nadia Herrera
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Huong T. Kratochvil
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - QCRG Structural Biology Consortium
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Anthony Aimon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - James M. Bennett
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
| | - Jose Brandao Neto
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Aina E. Cohen
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Alexandre Dias
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Alice Douangamath
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Louise Dunnett
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Oleg Fedorov
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
| | - Matteo P. Ferla
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Martin Fuchs
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, USA
| | - Tyler J. Gorrie-Stone
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - James M. Holton
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, CA, USA
- Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | - Tobias Krojer
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
| | - George Meigs
- Department of Biochemistry and Biophysics, University of California San Francisco, CA, USA
- Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ailsa J. Powell
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | | | - Victor L Rangel
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- School of Pharmaceutical Sciences of Ribeirao Preto, University of Sao Paulo, São Paulo, Brazil
| | - Silvia Russi
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Rachael E. Skyner
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Clyde A. Smith
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | | | - Jennifer L. Wierman
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Kang Zhu
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
| | - Natalia Jura
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA, USA
| | - Alan Ashworth
- Helen Diller Family Comprehensive Cancer, University of California San Francisco, CA, USA
| | - John Irwin
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
| | - Michael C. Thompson
- Department of Chemistry and Chemical Biology, University of California Merced, CA, USA
| | - Jason E. Gestwicki
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
- Institute for Neurodegenerative Disease, University of California San Francisco, CA, USA
| | - Frank von Delft
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- Department of Biochemistry, University of Johannesburg, Auckland Park, 2006, South Africa
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
| | - James S. Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
| | - Ivan Ahel
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
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5
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Morselli Gysi D, Do Valle Í, Zitnik M, Ameli A, Gan X, Varol O, Ghiassian SD, Patten JJ, Davey R, Loscalzo J, Barabási AL. Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19. ARXIV 2020:arXiv:2004.07229v2. [PMID: 32550253 PMCID: PMC7280907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 08/09/2020] [Indexed: 06/11/2023]
Abstract
The current pandemic has highlighted the need for methodologies that can quickly and reliably prioritize clinically approved compounds for their potential effectiveness for SARS-CoV-2 infections. In the past decade, network medicine has developed and validated multiple predictive algorithms for drug repurposing, exploiting the sub-cellular network-based relationship between a drug's targets and disease genes. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity, tasking each of them to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. To test the predictions, we used as ground truth 918 drugs that had been experimentally screened in VeroE6 cells, and the list of drugs under clinical trial, that capture the medical community's assessment of drugs with potential COVID-19 efficacy. We find that while most algorithms offer predictive power for these ground truth data, no single method offers consistently reliable outcomes across all datasets and metrics. This prompted us to develop a multimodal approach that fuses the predictions of all algorithms, showing that a consensus among the different predictive methods consistently exceeds the performance of the best individual pipelines. We find that 76 of the 77 drugs that successfully reduced viral infection do not bind the proteins targeted by SARS-CoV-2, indicating that these drugs rely on network-based actions that cannot be identified using docking-based strategies. These advances offer a methodological pathway to identify repurposable drugs for future pathogens and neglected diseases underserved by the costs and extended timeline of de novo drug development.
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Affiliation(s)
- Deisy Morselli Gysi
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Ítalo Do Valle
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA
| | - Marinka Zitnik
- Department of Biomedical Informatics, Harvard University, Boston, MA 02115, USA
- Harvard Data Science Initiative, Harvard University, Cambridge, MA 02138, USA
| | - Asher Ameli
- Scipher Medicine, 221 Crescent St, Suite 103A, Waltham, MA 02453
- Department of Physics, Northeastern University, Boston, MA 02115, USA
| | - Xiao Gan
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Onur Varol
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
| | | | - J J Patten
- Department of microbiology, NEIDL, Boston University, Boston, MA, USA
| | - Robert Davey
- Department of microbiology, NEIDL, Boston University, Boston, MA, USA
| | - Joseph Loscalzo
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Albert-László Barabási
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA
- Department of Network and Data Science, Central European University, Budapest 1051, Hungary
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