1
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Wee J, Chen J, Wei GW. Preventing future zoonosis: SARS-CoV-2 mutations enhance human-animal cross-transmission. Comput Biol Med 2024; 182:109101. [PMID: 39243518 DOI: 10.1016/j.compbiomed.2024.109101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/13/2024] [Accepted: 08/31/2024] [Indexed: 09/09/2024]
Abstract
The COVID-19 pandemic has driven substantial evolution of the SARS-CoV-2 virus, yielding subvariants that exhibit enhanced infectiousness in humans. However, this adaptive advantage may not universally extend to zoonotic transmission. In this work, we hypothesize that viral adaptations favoring animal hosts do not necessarily correlate with increased human infectivity. In addition, we consider the potential for gain-of-function mutations that could facilitate the virus's rapid evolution in humans following adaptation in animal hosts. Specifically, we identify the SARS-CoV-2 receptor-binding domain (RBD) mutations that enhance human-animal cross-transmission. To this end, we construct a multitask deep learning model, MT-TopLap trained on multiple deep mutational scanning datasets, to accurately predict the binding free energy changes upon mutation for the RBD to ACE2 of various species, including humans, cats, bats, deer, and hamsters. By analyzing these changes, we identified key RBD mutations such as Q498H in SARS-CoV-2 and R493K in the BA.2 variant that are likely to increase the potential for human-animal cross-transmission.
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Affiliation(s)
- JunJie Wee
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Jiahui Chen
- Department of Mathematical Sciences, University of Arkansas, Fayetteville, AR 72701, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA.
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2
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Halder S, Thakur A, Keshry SS, Jana P, Karothia D, Das Jana I, Acevedo O, Swain RK, Mondal A, Chattopadhyay S, Jayaprakash V, Dev A. SELEX based aptamers with diagnostic and entry inhibitor therapeutic potential for SARS-CoV-2. Sci Rep 2023; 13:14560. [PMID: 37666993 PMCID: PMC10477244 DOI: 10.1038/s41598-023-41885-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 09/01/2023] [Indexed: 09/06/2023] Open
Abstract
Frequent mutation and variable immunological protection against vaccination is a common feature for COVID-19 pandemic. Early detection and confinement remain key to controlling further spread of infection. In response, we have developed an aptamer-based system that possesses both diagnostic and therapeutic potential towards the virus. A random aptamer library (~ 1017 molecules) was screened using systematic evolution of ligands by exponential enrichment (SELEX) and aptamer R was identified as a potent binder for the SARS-CoV-2 spike receptor binding domain (RBD) using in vitro binding assay. Using a pseudotyped viral entry assay we have shown that aptamer R specifically inhibited the entry of a SARS-CoV-2 pseudotyped virus in HEK293T-ACE2 cells but did not inhibit the entry of a Vesicular Stomatitis Virus (VSV) glycoprotein (G) pseudotyped virus, hence establishing its specificity towards SARS-CoV-2 spike protein. The antiviral potential of aptamers R and J (same central sequence as R but lacking flanked primer regions) was tested and showed 95.4% and 82.5% inhibition, respectively, against the SARS-CoV-2 virus. Finally, intermolecular interactions between the aptamers and the RBD domain were analyzed using in silico docking and molecular dynamics simulations that provided additional insight into the binding and inhibitory action of aptamers R and J.
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Affiliation(s)
- Sayanti Halder
- Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India
| | - Abhishek Thakur
- Department of Chemistry, University of Miami, Coral Gables, FL, 33146, USA
| | - Supriya Suman Keshry
- Institute of Life Sciences, Bhubaneswar, Odisha, 751023, India
- School of Biotechnology, Kalinga Institute of Industrial Technology (KIIT) University, Bhubaneswar, Odisha, India
| | - Pradip Jana
- Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India
| | | | - Indrani Das Jana
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India
| | - Orlando Acevedo
- Department of Chemistry, University of Miami, Coral Gables, FL, 33146, USA
| | - Rajeeb K Swain
- Institute of Life Sciences, Bhubaneswar, Odisha, 751023, India
| | - Arindam Mondal
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India
| | | | - Venkatesan Jayaprakash
- Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India
| | - Abhimanyu Dev
- Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.
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3
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Chen J, Woldring DR, Huang F, Huang X, Wei GW. Topological deep learning based deep mutational scanning. Comput Biol Med 2023; 164:107258. [PMID: 37506452 PMCID: PMC10528359 DOI: 10.1016/j.compbiomed.2023.107258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/28/2023] [Accepted: 07/08/2023] [Indexed: 07/30/2023]
Abstract
High-throughput deep mutational scanning (DMS) experiments have significantly impacted protein engineering, drug discovery, immunology, cancer biology, and evolutionary biology by enabling the systematic understanding of protein functions. However, the mutational space associated with proteins is astronomically large, making it overwhelming for current experimental capabilities. Therefore, alternative methods for DMS are imperative. We propose a topological deep learning (TDL) paradigm to facilitate in silico DMS. We utilize a new topological data analysis (TDA) technique based on the persistent spectral theory, also known as persistent Laplacian, to capture both topological invariants and the homotopic shape evolution of data. To validate our TDL-DMS model, we use SARS-CoV-2 datasets and show excellent accuracy and reliability for binding interface mutations. This finding is significant for SARS-CoV-2 variant forecasting and designing effective antibodies and vaccines. Our proposed model is expected to have a significant impact on drug discovery, vaccine design, precision medicine, and protein engineering.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematical Sciences, University of Arkansas, Fayetteville, AR 72701, USA
| | - Daniel R Woldring
- Department of Chemical Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Faqing Huang
- Department of Chemistry and Biochemistry, University of Southern Mississippi, Hattiesburg, MS 39406, USA
| | - Xuefei Huang
- Department of Chemistry, Michigan State University, MI 48824, USA; Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA; The Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
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4
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Rahman A, Roy KJ, Deb GK, Ha T, Rahman S, Aktar MK, Ali MI, Kafi MA, Choi JW. Nano-Enabled Antivirals for Overcoming Antibody Escaped Mutations Based SARS-CoV-2 Waves. Int J Mol Sci 2023; 24:13130. [PMID: 37685938 PMCID: PMC10488153 DOI: 10.3390/ijms241713130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/11/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023] Open
Abstract
This review discusses receptor-binding domain (RBD) mutations related to the emergence of various SARS-CoV-2 variants, which have been highlighted as a major cause of repetitive clinical waves of COVID-19. Our perusal of the literature reveals that most variants were able to escape neutralizing antibodies developed after immunization or natural exposure, pointing to the need for a sustainable technological solution to overcome this crisis. This review, therefore, focuses on nanotechnology and the development of antiviral nanomaterials with physical antagonistic features of viral replication checkpoints as such a solution. Our detailed discussion of SARS-CoV-2 replication and pathogenesis highlights four distinct checkpoints, the S protein (ACE2 receptor coupling), the RBD motif (ACE2 receptor coupling), ACE2 coupling, and the S protein cleavage site, as targets for the development of nano-enabled solutions that, for example, prevent viral attachment and fusion with the host cell by either blocking viral RBD/spike proteins or cellular ACE2 receptors. As proof of this concept, we highlight applications of several nanomaterials, such as metal and metal oxide nanoparticles, carbon-based nanoparticles, carbon nanotubes, fullerene, carbon dots, quantum dots, polymeric nanoparticles, lipid-based, polymer-based, lipid-polymer hybrid-based, surface-modified nanoparticles that have already been employed to control viral infections. These nanoparticles were developed to inhibit receptor-mediated host-virus attachments and cell fusion, the uncoating of the virus, viral gene expression, protein synthesis, the assembly of progeny viral particles, and the release of the virion. Moreover, nanomaterials have been used as antiviral drug carriers and vaccines, and nano-enabled sensors have already been shown to enable fast, sensitive, and label-free real-time diagnosis of viral infections. Nano-biosensors could, therefore, also be useful in the remote testing and tracking of patients, while nanocarriers probed with target tissue could facilitate the targeted delivery of antiviral drugs to infected cells, tissues, organs, or systems while avoiding unwanted exposure of non-target tissues. Antiviral nanoparticles can also be applied to sanitizers, clothing, facemasks, and other personal protective equipment to minimize horizontal spread. We believe that the nanotechnology-enabled solutions described in this review will enable us to control repeated SAR-CoV-2 waves caused by antibody escape mutations.
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Affiliation(s)
- Aminur Rahman
- Department of Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh; (A.R.); (K.J.R.); (S.R.); (M.K.A.); (M.I.A.)
| | - Kumar Jyotirmoy Roy
- Department of Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh; (A.R.); (K.J.R.); (S.R.); (M.K.A.); (M.I.A.)
| | - Gautam Kumar Deb
- Department of Biotechnology, Bangladesh Livestock Research Institute, Dhaka 1341, Bangladesh;
| | - Taehyeong Ha
- Department of Chemical and Biomolecular Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Republic of Korea;
| | - Saifur Rahman
- Department of Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh; (A.R.); (K.J.R.); (S.R.); (M.K.A.); (M.I.A.)
| | - Mst. Khudishta Aktar
- Department of Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh; (A.R.); (K.J.R.); (S.R.); (M.K.A.); (M.I.A.)
| | - Md. Isahak Ali
- Department of Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh; (A.R.); (K.J.R.); (S.R.); (M.K.A.); (M.I.A.)
| | - Md. Abdul Kafi
- Department of Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh; (A.R.); (K.J.R.); (S.R.); (M.K.A.); (M.I.A.)
| | - Jeong-Woo Choi
- Department of Chemical and Biomolecular Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Republic of Korea;
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5
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Zeng L, Lu Y, Yan W, Yang Y. A Protein Co-Conservation Network Model Characterizes Mutation Effects on SARS-CoV-2 Spike Protein. Int J Mol Sci 2023; 24:ijms24043255. [PMID: 36834664 PMCID: PMC9960056 DOI: 10.3390/ijms24043255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/03/2023] [Accepted: 02/04/2023] [Indexed: 02/10/2023] Open
Abstract
The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main target for host antibodies. It is critically important to study the biological effects of the mutations to understand the mechanisms of how mutations alter viral functions. Here, we propose a protein co-conservation weighted network (PCCN) model only based on the protein sequence to characterize the mutation sites by topological features and to investigate the mutation effects on the spike protein from a network view. Frist, we found that the mutation sites on the spike protein had significantly larger centrality than the non-mutation sites. Second, the stability changes and binding free energy changes in the mutation sites were positively significantly correlated with their neighbors' degree and the shortest path length separately. The results indicate that our PCCN model provides new insights into mutations on spike proteins and reflects the mutation effects on protein function alternations.
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Affiliation(s)
- Lianjie Zeng
- School of Computer Science & Technology, Soochow University, Suzhou 215000, China
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210000, China
| | - Yitan Lu
- Department of Bioinformatics, School of Biology and Basic Medical Sciences, Medical College of Soochow University, Suzhou 215123, China
| | - Wenying Yan
- Department of Bioinformatics, School of Biology and Basic Medical Sciences, Medical College of Soochow University, Suzhou 215123, China
- Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Suzhou 215123, China
- Correspondence: (W.Y.); (Y.Y.)
| | - Yang Yang
- School of Computer Science & Technology, Soochow University, Suzhou 215000, China
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210000, China
- Correspondence: (W.Y.); (Y.Y.)
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6
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Liu X, Jiang L, Li L, Lu F, Liu F. Bionics design of affinity peptide inhibitors for SARS-CoV-2 RBD to block SARS-CoV-2 RBD-ACE2 interactions. Heliyon 2023; 9:e12890. [PMID: 36686609 PMCID: PMC9836997 DOI: 10.1016/j.heliyon.2023.e12890] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 12/30/2022] [Accepted: 01/06/2023] [Indexed: 01/14/2023] Open
Abstract
Coronavirus Disease 2019 (COVID-19), has already posed serious threats and impacts on the health of the population and the country's economy. Therefore, it is of great theoretical significance and practical application value to better understand the process of COVID-19 infection and develop effective therapeutic drugs. It is known that the receptor-binding structural domain (SARS-CoV-2 RBD) on the spike protein of the novel coronavirus directly mediates its interaction with the host receptor angiotensin-converting enzyme 2 (ACE2), and thus blocking SARS-CoV-2 RBD-ACE2 interaction is capable of inhibiting SARS-CoV-2 infection. Firstly, the interaction mechanism between SARS-CoV-2RBD-ACE2 was explored using molecular dynamics simulation (MD) coupled with molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculation method. The results of energy analysis showed that the key residues R403, R408, K417, and Y505 of SARS-CoV-2 RBD and the key residues D30, E37, D38, and Y41 of ACE2 were identified. Therefore, according to the hotspot residues of ACE2 and their distribution, a short peptide library of high-affinity SARS-CoV-2 RBD was constructed. And by using molecular docking virtual screening, six short peptides including DDFEDY, DEFEDY, DEYEDY, DFVEDY, DFHEDY, and DSFEDY with high affinity for SARS-CoV-2 RBD were identified. The results of MD simulation further confirmed that DDFEDY, DEYEDY, and DFVEDY are expected to be effective inhibitors. Finally, the allergenicity, toxicity and solubility properties of the three peptide inhibitors were validated.
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Affiliation(s)
- Xiaofeng Liu
- Key Laboratory of Industrial Fermentation Microbiology of Ministry of Education; Tianjin Key Laboratory of Industrial Microbiology, PR China,College of Biotechnology, Tianjin University of Science & Technology, Tianjin 300457, PR China
| | - Luying Jiang
- Key Laboratory of Industrial Fermentation Microbiology of Ministry of Education; Tianjin Key Laboratory of Industrial Microbiology, PR China,College of Biotechnology, Tianjin University of Science & Technology, Tianjin 300457, PR China
| | - Li Li
- College of Marine and Environmental Science, Tianjin University of Science & Technology, Tianjin 300457, China
| | - Fuping Lu
- Key Laboratory of Industrial Fermentation Microbiology of Ministry of Education; Tianjin Key Laboratory of Industrial Microbiology, PR China,College of Biotechnology, Tianjin University of Science & Technology, Tianjin 300457, PR China
| | - Fufeng Liu
- Key Laboratory of Industrial Fermentation Microbiology of Ministry of Education; Tianjin Key Laboratory of Industrial Microbiology, PR China,College of Biotechnology, Tianjin University of Science & Technology, Tianjin 300457, PR China,Corresponding author. Key Laboratory of Industrial Fermentation Microbiology of Ministry of Education; Tianjin Key Laboratory of Industrial Microbiology, PR China.
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7
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Chen J, Wang R, Hozumi Y, Liu G, Qiu Y, Wei X, Wei GW. Emerging Dominant SARS-CoV-2 Variants. J Chem Inf Model 2023; 63:335-342. [PMID: 36577010 PMCID: PMC9843632 DOI: 10.1021/acs.jcim.2c01352] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Indexed: 12/29/2022]
Abstract
Accurate and reliable forecasting of emerging dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants enables policymakers and vaccine makers to get prepared for future waves of infections. The last three waves of SARS-CoV-2 infections caused by dominant variants, Omicron (BA.1), BA.2, and BA.4/BA.5, were accurately foretold by our artificial intelligence (AI) models built with biophysics, genotyping of viral genomes, experimental data, algebraic topology, and deep learning. On the basis of newly available experimental data, we analyzed the impacts of all possible viral spike (S) protein receptor-binding domain (RBD) mutations on the SARS-CoV-2 infectivity. Our analysis sheds light on viral evolutionary mechanisms, i.e., natural selection through infectivity strengthening and antibody resistance. We forecast that BP.1, BL*, BA.2.75*, BQ.1*, and particularly BN.1* have a high potential to become the new dominant variants to drive the next surge. Our key projection about these variants dominance made on Oct. 18, 2022 (see arXiv:2210.09485) became reality in late November 2022.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Yuta Hozumi
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Gengzhuo Liu
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Yuchi Qiu
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Xiaoqi Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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Rojas-Cruz AF, Gallego-Gómez JC, Bermúdez-Santana CI. RNA structure-altering mutations underlying positive selection on Spike protein reveal novel putative signatures to trace crossing host-species barriers in Betacoronavirus. RNA Biol 2022; 19:1019-1044. [PMID: 36102368 PMCID: PMC9481089 DOI: 10.1080/15476286.2022.2115750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Similar to other RNA viruses, the emergence of Betacoronavirus relies on cross-species viral transmission, which requires careful health surveillance monitoring of protein-coding information as well as genome-wide analysis. Although the evolutionary jump from natural reservoirs to humans may be mainly traced-back by studying the effect that hotspot mutations have on viral proteins, it is largely unexplored if other impacts might emerge on the structured RNA genome of Betacoronavirus. In this survey, the protein-coding and viral genome architecture were simultaneously studied to uncover novel insights into cross-species horizontal transmission events. We analysed 1,252,952 viral genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 distributed across the world in bats, intermediate animals, and humans to build a new landscape of changes in the RNA viral genome. Phylogenetic analyses suggest that bat viruses are the most closely related to the time of most recent common ancestor of Betacoronavirus, and missense mutations in viral proteins, mainly in the S protein S1 subunit: SARS-CoV (G > T; A577S); MERS-CoV (C > T; S746R and C > T; N762A); and SARS-CoV-2 (A > G; D614G) appear to have driven viral diversification. We also found that codon sites under positive selection on S protein overlap with non-compensatory mutations that disrupt secondary RNA structures in the RNA genome complement. These findings provide pivotal factors that might be underlying the eventual jumping the species barrier from bats to intermediate hosts. Lastly, we discovered that nearly half of the Betacoronavirus genomes carry highly conserved RNA structures, and more than 90% of these RNA structures show negative selection signals, suggesting essential functions in the biology of Betacoronavirus that have not been investigated to date. Further research is needed on negatively selected RNA structures to scan for emerging functions like the potential of coding virus-derived small RNAs and to develop new candidate antiviral therapeutic strategies.
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Affiliation(s)
- Alexis Felipe Rojas-Cruz
- Theoretical and Computational RNomics Group, Department of Biology, Faculty of Sciences, National University of Colombia, Bogota Colombia
| | - Juan Carlos Gallego-Gómez
- Molecular and Translational Medicine Group, Faculty of Medicine, University of Antioquia, Medellin Colombia
| | - Clara Isabel Bermúdez-Santana
- Theoretical and Computational RNomics Group, Department of Biology, Faculty of Sciences, National University of Colombia, Bogota Colombia
- Center of Excellence in Scientific Computing, National University of Colombia, Bogota Colombia
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Carvalho PPD, Alves NA. Featuring ACE2 binding SARS-CoV and SARS-CoV-2 through a conserved evolutionary pattern of amino acid residues. J Biomol Struct Dyn 2022; 40:11719-11728. [PMID: 34486937 PMCID: PMC8425439 DOI: 10.1080/07391102.2021.1965028] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Spike (S) glycoproteins mediate the coronavirus entry into the host cell. The S1 subunit of S-proteins contains the receptor-binding domain (RBD) that is able to recognize different host receptors, highlighting its remarkable capacity to adapt to their hosts along the viral evolution. While RBD in spike proteins is determinant for the virus-receptor interaction, the active residues lie at the receptor-binding motif (RBM), a region located in RBD that plays a fundamental role binding the outer surface of their receptors. Here, we address the hypothesis that SARS-CoV and SARS-CoV-2 strains able to use angiotensin-converting enzyme 2 (ACE2) proteins have adapted their RBM along the viral evolution to explore specific conformational topology driven by the residues YGF to infect host cells. We also speculate that this YGF-based mechanism can act as a protein signature located at the RBM to distinguish coronaviruses able to use ACE2 as a cell entry receptor.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Patrícia P. D. Carvalho
- Departamento de Física, FFCLRP, Universidade de São Paulo, Ribeirão Preto, SP, Brazil,CONTACT Patrícia P. D. Carvalho ;
| | - Nelson A. Alves
- Departamento de Física, FFCLRP, Universidade de São Paulo, Ribeirão Preto, SP, Brazil,Nelson Alves
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Bolivar-Muñoz J, Vits S, Bermudez-Santana CI, Galindo JF. Structural Analysis of the Spike Protein of SARS-CoV-2 Variants and Other Betacoronaviruses Using Molecular Dynamics. Chemphyschem 2022; 23:e202200382. [PMID: 35927218 DOI: 10.1002/cphc.202200382] [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: 06/06/2022] [Revised: 08/03/2022] [Indexed: 01/04/2023]
Abstract
A structural analysis over various spike proteins from three highly pathogenic Betacoronavirus was done to understand their structural differences. The proteins were modeled using crystal structures from SARS-CoV, MERS-CoV, and other Betacoronavirus that infect bats and pangolins. The group was split in two sets; the first set corresponds to the non-mutated spike proteins, while the second set corresponds to mutated spike variants alpha, beta, gamma, delta, omicron and mu; five of them classified as variants of concern and the last one as variant of interest. A conformational space exploration was carried out for every protein by using molecular dynamic simulations. Root mean square fluctuations, principal component and cross-correlation analysis were carried out over the dynamics to analyze the flexibility and rigidity of every protein in comparison to the wild type Spike protein from the SARS-CoV-2. The obtained results indicate that the proteins, which are not spread among humans, have smooth movements compared to those of SARS-CoV-2 and its variants. In addition, a relationship between the speed of the virulence and the movement of the protein can explain the behavior of delta and omicron variants.
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Affiliation(s)
- Jonathan Bolivar-Muñoz
- Department of Chemistry, Center of Excellence in Scientific Computing, Universidad Nacional de Colombia, Bogotá, 111321, Colombia
| | - Sofia Vits
- Department of Biology, Center of Excellence in Scientific Computing, Universidad Nacional de Colombia, Bogotá, 111321, Colombia
| | - Clara Isabel Bermudez-Santana
- Department of Biology, Center of Excellence in Scientific Computing, Universidad Nacional de Colombia, Bogotá, 111321, Colombia
| | - Johan Fabian Galindo
- Department of Chemistry, Center of Excellence in Scientific Computing, Universidad Nacional de Colombia, Bogotá, 111321, Colombia
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11
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Rana R, Kant R, Huirem RS, Bohra D, Ganguly NK. Omicron variant: Current insights and future directions. Microbiol Res 2022; 265:127204. [PMID: 36152612 PMCID: PMC9482093 DOI: 10.1016/j.micres.2022.127204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/22/2022] [Accepted: 09/13/2022] [Indexed: 01/08/2023]
Abstract
The global COVID-19 outbreak has returned with the identification of the SARS-CoV-2 Omicron variant (B.1.1.529) after appearing to be persistently spreading for the more than past two years. In comparison to prior SARS-CoV-2 variants, this new variant revealed a significant amount of mutation. This novel variety may have a greater rate of transmissibility which might impede the effectiveness of current diagnostic equipment as well as vaccination efficacy and also impede immunotherapies (Antibody / monoclonal antibody based). WHO designated B.1.1.529 as a variant of concern on November 26, 2021, identified as Omicron. The Omicron variant transmission method and severity, on the other hand, are well defined. The global spread of Omicron, which has now seized many nations, has resulted in numerous speculations regarding its origin and degree of infectivity. The following sections will go over its potential for transmission, omicron structure, and impact on COVID-19 vaccines, how it is different from delta variant and diagnostics.
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Affiliation(s)
- Rashmi Rana
- Department of Research, Sir Ganga Ram Hospital, Delhi, India.
| | - Ravi Kant
- Department of Research, Sir Ganga Ram Hospital, Delhi, India
| | | | - Deepika Bohra
- Department of Research, Sir Ganga Ram Hospital, Delhi, India
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12
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Chen J, Qiu Y, Wang R, Wei GW. Persistent Laplacian projected Omicron BA.4 and BA.5 to become new dominating variants. Comput Biol Med 2022; 151:106262. [PMID: 36379191 PMCID: PMC10754203 DOI: 10.1016/j.compbiomed.2022.106262] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 10/21/2022] [Accepted: 10/30/2022] [Indexed: 11/15/2022]
Abstract
Due to its high transmissibility, Omicron BA.1 ousted the Delta variant to become a dominating variant in late 2021 and was replaced by more transmissible Omicron BA.2 in March 2022. An important question is which new variants will dominate in the future. Topology-based deep learning models have had tremendous success in forecasting emerging variants in the past. However, topology is insensitive to homotopic shape evolution in virus-human protein-protein binding, which is crucial to viral evolution and transmission. This challenge is tackled with persistent Laplacian, which is able to capture both the topological change and homotopic shape evolution of data. Persistent Laplacian-based deep learning models are developed to systematically evaluate variant infectivity. Our comparative analysis of Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron BA.1, BA.1.1, BA.2, BA.2.11, BA.2.12.1, BA.3, BA.4, and BA.5 unveils that Omicron BA.2.11, BA.2.12.1, BA.3, BA.4, and BA.5 are more contagious than BA.2. In particular, BA.4 and BA.5 are about 36% more infectious than BA.2 and are projected to become new dominant variants by natural selection. Moreover, the proposed models outperform the state-of-the-art methods on three major benchmark datasets for mutation-induced protein-protein binding free energy changes. Our key projection about BA4 and BA.5's dominance made on May 1, 2022 (see arXiv:2205.00532) became a reality in late June 2022.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Yuchi Qiu
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
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13
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Chen J, Wang R, Hozumi Y, Liu G, Qiu Y, Wei X, Wei GW. Emerging dominant SARS-CoV-2 variants. ARXIV 2022:arXiv:2210.09485v1. [PMID: 36299737 PMCID: PMC9603820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Accurate and reliable forecasting of emerging dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants enables policymakers and vaccine makers to get prepared for future waves of infections. The last three waves of SARS-CoV-2 infections caused by dominant variants Omicron (BA.1), BA.2, and BA.4/BA.5 were accurately foretold by our artificial intelligence (AI) models built with biophysics, genotyping of viral genomes, experimental data, algebraic topology, and deep learning. Based on newly available experimental data, we analyzed the impacts of all possible viral spike (S) protein receptor-binding domain (RBD) mutations on the SARS-CoV-2 infectivity. Our analysis sheds light on viral evolutionary mechanisms, i.e., natural selection through infectivity strengthening and antibody resistance. We forecast that BA.2.10.4, BA.2.75, BQ.1.1, and particularly, BA.2.75+R346T, have high potential to become new dominant variants to drive the next surge.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Yuta Hozumi
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Gengzhuo Liu
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Yuchi Qiu
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Xiaoqi Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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14
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Beeraka NM, Sukocheva OA, Lukina E, Liu J, Fan R. Development of antibody resistance in emerging mutant strains of SARS CoV-2: Impediment for COVID-19 vaccines. Rev Med Virol 2022; 32:e2346. [PMID: 35416390 PMCID: PMC9111059 DOI: 10.1002/rmv.2346] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 01/28/2022] [Accepted: 03/06/2022] [Indexed: 02/05/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a highly infectious agent associated with unprecedented morbidity and mortality. A failure to stop growth of COVID-19-linked morbidity rates is caused by SARS-CoV-2 mutations and the emergence of new highly virulent SARS-CoV-2 strains. Several acquired SARS-CoV-2 mutations reflect viral adaptations to host immune defence. Mutations in the virus Spike-protein were associated with the lowered effectiveness of current preventive therapies, including vaccines. Recent in vitro studies detected diminished neutralisation capacity of vaccine-induced antibodies, which are targeted to bind Spike receptor-binding and N-terminal domains in the emerging strains. Lower than expected inhibitory activity of antibodies was reported against viruses with E484K Spike mutation, including B.1.1.7 (UK), P.1 (Brazil), B.1.351 (South African), and new Omicron variant (B.1.1.529) with E484A mutation. The vaccine effectiveness is yet to be examined against new mutant strains of SARS-CoV-2 originating in Europe, Nigeria, Brazil, South Africa, and India. To prevent the loss of anti-viral protection in vivo, often defined as antibody resistance, it is required to target highly conserved viral sequences (including Spike protein) and enhance the potency of antibody cocktails. In this review, we assess the reported mutation-acquiring potential of coronaviruses and compare efficacies of current COVID-19 vaccines against 'parent' and 'mutant' strains of SARS-CoV-2 (Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529)).
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Affiliation(s)
- Narasimha M. Beeraka
- Department of Radiation OncologyCancer CenterThe First Affiliated Hospital of ZhengzhouZhengzhouChina
- Department of Human AnatomyI.M. Sechenov First Moscow State Medical University (Sechenov University)MoscowRussian Federation
| | - Olga A. Sukocheva
- Discipline of Health SciencesCollege of Nursing and Health SciencesFlinders University of South AustraliaBedford ParkAustralia
| | - Elena Lukina
- Discipline of BiologyCollege of SciencesFlinders University of South AustraliaBedford ParkAustralia
| | - Junqi Liu
- Department of Radiation OncologyCancer CenterThe First Affiliated Hospital of ZhengzhouZhengzhouChina
| | - Ruitai Fan
- Department of Radiation OncologyCancer CenterThe First Affiliated Hospital of ZhengzhouZhengzhouChina
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15
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Lin F, Zhang H, Li L, Yang Y, Zou X, Chen J, Tang X. PEDV: Insights and Advances into Types, Function, Structure, and Receptor Recognition. Viruses 2022; 14:v14081744. [PMID: 36016366 PMCID: PMC9416423 DOI: 10.3390/v14081744] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/06/2022] [Accepted: 08/06/2022] [Indexed: 11/16/2022] Open
Abstract
Porcine epidemic diarrhea virus (PEDV) has been endemic in most parts of the world since its emergence in the 1970s. It infects the small intestine and intestinal villous cells, spreads rapidly, and causes infectious intestinal disease characterized by vomiting, diarrhea, and dehydration, leading to high mortality in newborn piglets and causing massive economic losses to the pig industry. The entry of PEDV into cells is mediated by the binding of its spike protein (S protein) to a host cell receptor. Here, we review the structure of PEDV, its strains, and the structure and function of the S protein shared by coronaviruses, and summarize the progress of research on possible host cell receptors since the discovery of PEDV.
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Affiliation(s)
- Feng Lin
- College of Animal Sciences, Jilin University, Changchun 130062, China
| | - Huanyu Zhang
- College of Animal Sciences, Jilin University, Changchun 130062, China
| | - Linquan Li
- College of Animal Sciences, Jilin University, Changchun 130062, China
| | - Yang Yang
- College of Animal Sciences, Jilin University, Changchun 130062, China
| | - Xiaodong Zou
- College of Animal Sciences, Jilin University, Changchun 130062, China
| | - Jiahuan Chen
- College of Animal Sciences, Jilin University, Changchun 130062, China
| | - Xiaochun Tang
- College of Animal Sciences, Jilin University, Changchun 130062, China
- Chongqing Research Institute, Jilin University, Chongqing 401120, China
- Correspondence:
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16
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Li Y, Zheng P, Liu T, Shi C, Wang B, Xu Y, Jin T. Structural Requirements and Plasticity of Receptor-Binding Domain in Human Coronavirus Spike. Front Mol Biosci 2022; 9:930931. [PMID: 35903152 PMCID: PMC9315343 DOI: 10.3389/fmolb.2022.930931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/06/2022] [Indexed: 11/22/2022] Open
Abstract
The most recent human coronaviruses including severe acute respiratory syndrome coronavirus-2 causing severe respiratory tract infection and high pathogenicity bring significant global public health concerns. Infections are initiated by recognizing host cell receptors by coronavirus spike protein S1 subunit, and then S2 mediates membrane fusion. However, human coronavirus spikes undergo frequent mutation, which may result in diverse pathogenesis and infectivity. In this review, we summarize some of these recent structural and mutational characteristics of RBD of human coronavirus spike protein and their interaction with specific human cell receptors and analyze the structural requirements and plasticity of RBD. Stability of spike protein, affinity toward receptor, virus fitness, and infectivity are the factors controlling the viral tropisms. Thus, understanding the molecular details of RBDs and their mutations is critical in deciphering virus evolution. Structural information of spike and receptors of human coronaviruses not only reveals the molecular mechanism of host–microbe interaction and pathogenesis but also helps develop effective drug to control these infectious pathogens and cope with the future emerging coronavirus outbreaks.
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Affiliation(s)
- Yajuan Li
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Peiyi Zheng
- Laboratory of Structural Immunology, CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Tingting Liu
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Cuixiao Shi
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Bo Wang
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yuanhong Xu
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Tengchuan Jin
- Laboratory of Structural Immunology, CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
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17
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Chen J, Wei GW. Mathematical artificial intelligence design of mutation-proof COVID-19 monoclonal antibodies. COMMUNICATIONS IN INFORMATION AND SYSTEMS 2022; 22:339-361. [PMID: 36713633 PMCID: PMC9881605 DOI: 10.4310/cis.2022.v22.n3.a3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have compromised existing vaccines and posed a grand challenge to coronavirus disease 2019 (COVID-19) prevention, control, and global economic recovery. For COVID-19 patients, one of the most effective COVID-19 medications is monoclonal antibody (mAb) therapies. The United States Food and Drug Administration (U.S. FDA) has given the emergency use authorization (EUA) to a few mAbs, including those from Regeneron, Eli Elly, etc. However, they are also undermined by SARS-CoV-2 mutations. It is imperative to develop effective mutation-proof mAbs for treating COVID-19 patients infected by all emerging variants and/or the original SARS-CoV-2. We carry out a deep mutational scanning to present the blueprint of such mAbs using algebraic topology and artificial intelligence (AI). To reduce the risk of clinical trial-related failure, we select five mAbs either with FDA EUA or in clinical trials as our starting point. We demonstrate that topological AI-designed mAbs are effective for variants of concerns and variants of interest designated by the World Health Organization (WHO), as well as the original SARS-CoV-2. Our topological AI methodologies have been validated by tens of thousands of deep mutational data and their predictions have been confirmed by results from tens of experimental laboratories and population-level statistics of genome isolates from hundreds of thousands of patients.
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Affiliation(s)
- Jiahui Chen
- Department of mathematics, Michigan State University, East Lansing, MI 48823, USA
| | - Guo-Wei Wei
- Department of mathematics, Michigan State University, East Lansing, MI 48823, USA
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18
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Xie P, Fang Y, Baloch Z, Yu H, Zhao Z, Li R, Zhang T, Li R, Zhao J, Yang Z, Dong S, Xia X. A Mouse-Adapted Model of HCoV-OC43 and Its Usage to the Evaluation of Antiviral Drugs. Front Microbiol 2022; 13:845269. [PMID: 35755996 PMCID: PMC9220093 DOI: 10.3389/fmicb.2022.845269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 04/19/2022] [Indexed: 11/24/2022] Open
Abstract
The human coronavirus OC43 (HCoV-OC43) is one of the most common causes of common cold but can lead to fatal pneumonia in children and elderly. However, the available animal models of HCoV-OC43 did not show respiratory symptoms that are insufficient to assist in screening antiviral agents for respiratory diseases. In this study, we adapted the HCoV-OC43 VR-1558 strain by serial passage in suckling C57BL/6 mice and the resulting mouse-adapted virus at passage 9 (P9) contained 8 coding mutations in polyprotein 1ab, spike (S) protein, and nucleocapsid (N) protein. Pups infected with the P9 virus significantly lost body weight and died within 5 dpi. In cerebral and pulmonary tissues, the P9 virus replication induced the production of G-CSF, IFN-γ, IL-6, CXCL1, MCP-1, MIP-1α, RANTES, IP-10, MIP-1β, and TNF-α, as well as pathological alterations including reduction of neuronal cells and typical symptoms of viral pneumonia. We found that the treatment of arbidol hydrochloride (ARB) or Qingwenjiere Mixture (QJM) efficiently improved the symptoms and decreased n gene expression, inflammatory response, and pathological changes. Furthermore, treating with QJM or ARB raised the P9-infected mice’s survival rate within a 15 day observation period. These findings suggested that the new mouse-adapted HCoV-OC43 model is applicable and reproducible for antiviral studies of HCoV-OC43.
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Affiliation(s)
- Peifang Xie
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Yue Fang
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Zulqarnain Baloch
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Huanhuan Yu
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Zeyuan Zhao
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Rongqiao Li
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Tongtong Zhang
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Runfeng Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jincun Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zifeng Yang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shuwei Dong
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Xueshan Xia
- The Affiliated AnNing First Hospital, Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
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19
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Li S, Yang R, Zhang D, Han P, Xu Z, Chen Q, Zhao R, Zhao X, Qu X, Zheng A, Wang L, Li L, Hu Y, Zhang R, Su C, Niu S, Zhang Y, Qi J, Liu K, Wang Q, Gao GF. Cross-species recognition and molecular basis of SARS-CoV-2 and SARS-CoV binding to ACE2s of marine animals. Natl Sci Rev 2022; 9:nwac122. [PMID: 36187898 PMCID: PMC9517163 DOI: 10.1093/nsr/nwac122] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 06/04/2022] [Accepted: 06/15/2022] [Indexed: 11/21/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has an extremely broad host range that includes hippopotami, which are phylogenetically closely related to whales. The cellular ACE2 receptor is one of the key determinants of the host range. Here, we found that ACE2s from several marine mammals and hippopotami could efficiently bind to the receptor-binding domain (RBD) of both SARS-CoV and SARS-CoV-2 and facilitate the transduction of SARS-CoV and SARS-CoV-2 pseudoviruses into ACE2-expressing cells. We further resolved the cryo-electron microscopy complex structures of the minke whale ACE2 and sea lion ACE2, respectively, bound to the RBDs, revealing that they have similar binding modes to human ACE2 when it comes to the SARS-CoV-2 RBD and SARS-CoV RBD. Our results indicate that marine mammals could potentially be new victims or virus carriers of SARS-CoV-2, which deserves further careful investigation and study. It will provide an early warning for the prospective monitoring of marine mammals.
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Affiliation(s)
| | | | | | | | - Zepeng Xu
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Faculty of Health Sciences, University of Macau, Macau, China
| | - Qian Chen
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Institute of Physical Science and Information, Anhui University, Hefei230039, China
| | - Runchu Zhao
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Institute of Physical Science and Information, Anhui University, Hefei230039, China
| | - Xin Zhao
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Center for Influenza Research and Early-Warning (CASCIRE), Chinese Academy of Sciences, Beijing100101, China
| | - Xiao Qu
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China
| | - Anqi Zheng
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China
| | - Liang Wang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Center for Influenza Research and Early-Warning (CASCIRE), Chinese Academy of Sciences, Beijing100101, China
| | - Linjie Li
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Savaid Medical School, University of Chinese Academy of Sciences, Beijing100049, China
| | - Yu Hu
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,School of Life Sciences, University of Science and Technology of China, Hefei230026, China
| | - Rong Zhang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning530004, China
| | - Chao Su
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China
| | - Sheng Niu
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong030801, China
| | - Yanfang Zhang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China
| | - Jianxun Qi
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China,Savaid Medical School, University of Chinese Academy of Sciences, Beijing100049, China
| | - Kefang Liu
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing100101, China
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20
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Gröhs Ferrareze PA, Zimerman RA, Franceschi VB, Caldana GD, Netz PA, Thompson CE. Molecular evolution and structural analyses of the spike glycoprotein from Brazilian SARS-CoV-2 genomes: the impact of selected mutations. J Biomol Struct Dyn 2022; 41:3110-3128. [PMID: 35594172 DOI: 10.1080/07391102.2022.2076154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
The COVID-19 pandemic caused by SARS-CoV-2 has reached by February 2022 more than 380 million cases and 5.5 million deaths worldwide since its beginning in late 2019, leading to enhanced concern in the scientific community and the general population. One of the most important pieces of this host-pathogen interaction is the spike protein, which binds to the hACE2 cell receptor, mediates the membrane fusion and is the major target of neutralizing antibodies against SARS-CoV-2. The multiple amino acid substitutions observed in this region, specially in RBD have enhanced the hACE2 binding affinity and led to several modifications in the mechanisms of SARS-CoV-2 pathogenesis, improving the viral fitness and/or promoting immune evasion, with potential impact in the vaccine development. In this work, we identified 48 sites under selective pressures, 17 of them with the strongest evidence by the HyPhy tests, including VOC related mutation sites 138, 142, 222, 262, 484, 681, and 845, among others. The coevolutionary analysis identified 28 sites found not to be conditionally independent, such as E484K-N501Y. The molecular dynamics and free energy estimates showed the structural stabilizing effect and the higher impact of E484K for enhanced binding affinity between the spike RBD and hACE2 in P.1 and P.2 lineages (specially with L452V). Structural changes were also identified in the hACE molecule when interacting with B.1.1.7 RDB. Despite some destabilizing substitutions, a stabilizing effect was identified for the majority of the positively selected mutations.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Patrícia Aline Gröhs Ferrareze
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brazil
| | | | - Vinícius Bonetti Franceschi
- Center of Biotechnology, Graduate Program in Cell and Molecular Biology (PPGBCM), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Gabriel Dickin Caldana
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brazil
| | - Paulo Augusto Netz
- Graduate Program in Chemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Claudia Elizabeth Thompson
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brazil.,Center of Biotechnology, Graduate Program in Cell and Molecular Biology (PPGBCM), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.,Department of Pharmacosciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brazil
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21
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Chen J, Wei GW. Mathematical artificial intelligence design of mutation-proof COVID-19 monoclonal antibodies. ARXIV 2022:arXiv:2204.09471v1. [PMID: 35475234 PMCID: PMC9040270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have compromised existing vaccines and posed a grand challenge to coronavirus disease 2019 (COVID-19) prevention, control, and global economic recovery. For COVID-19 patients, one of the most effective COVID-19 medications is monoclonal antibody (mAb) therapies. The United States Food and Drug Administration (U.S. FDA) has given the emergency use authorization (EUA) to a few mAbs, including those from Regeneron, Eli Elly, etc. However, they are also undermined by SARS-CoV-2 mutations. It is imperative to develop effective mutation-proof mAbs for treating COVID-19 patients infected by all emerging variants and/or the original SARS-CoV-2. We carry out a deep mutational scanning to present the blueprint of such mAbs using algebraic topology and artificial intelligence (AI). To reduce the risk of clinical trial-related failure, we select five mAbs either with FDA EUA or in clinical trials as our starting point. We demonstrate that topological AI-designed mAbs are effective to variants of concerns and variants of interest designated by the World Health Organization (WHO), as well as the original SARS-CoV-2. Our topological AI methodologies have been validated by tens of thousands of deep mutational data and their predictions have been confirmed by results from tens of experimental laboratories and population-level statistics of genome isolates from hundreds of thousands of patients.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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22
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Structures of a deltacoronavirus spike protein bound to porcine and human receptors. Nat Commun 2022; 13:1467. [PMID: 35304871 PMCID: PMC8933513 DOI: 10.1038/s41467-022-29062-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 02/25/2022] [Indexed: 12/12/2022] Open
Abstract
Porcine deltacoronavirus (PDCoV) can experimentally infect a variety of animals. Human infection by PDCoV has also been reported. Consistently, PDCoV can use aminopeptidase N (APN) from different host species as receptors to enter cells. To understand this broad receptor usage and interspecies transmission of PDCoV, we determined the crystal structures of the receptor binding domain (RBD) of PDCoV spike protein bound to human APN (hAPN) and porcine APN (pAPN), respectively. The structures of the two complexes exhibit high similarity. PDCoV RBD binds to common regions on hAPN and pAPN, which are different from the sites engaged by two alphacoronaviruses: HCoV-229E and porcine respiratory coronavirus (PRCoV). Based on structure guided mutagenesis, we identified conserved residues on hAPN and pAPN that are essential for PDCoV binding and infection. We report the detailed mechanism for how a deltacoronavirus recognizes homologous receptors and provide insights into the cross-species transmission of PDCoV. As a potential zoonotic pathogen, porcine deltacoronavirus (PDCoV) has been shown to cause febrile illness in humans. Here, Ji et al. report the structures of PDCoV spike protein bound to porcine and human aminopeptidase receptors, pointing to the likely underlying mechanism of PDCoV zoonotic transmission.
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Wang R, Chen J, Hozumi Y, Yin C, Wei GW. Emerging Vaccine-Breakthrough SARS-CoV-2 Variants. ACS Infect Dis 2022; 8:546-556. [PMID: 35133792 PMCID: PMC8848511 DOI: 10.1021/acsinfecdis.1c00557] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Indexed: 12/28/2022]
Abstract
The surge of COVID-19 infections has been fueled by new SARS-CoV-2 variants, namely Alpha, Beta, Gamma, Delta, and so forth. The molecular mechanism underlying such surge is elusive due to the existence of 28 554 unique mutations, including 4 653 non-degenerate mutations on the spike protein. Understanding the molecular mechanism of SARS-CoV-2 transmission and evolution is a prerequisite to foresee the trend of emerging vaccine-breakthrough variants and the design of mutation-proof vaccines and monoclonal antibodies. We integrate the genotyping of 1 489 884 SARS-CoV-2 genomes, a library of 130 human antibodies, tens of thousands of mutational data, topological data analysis, and deep learning to reveal SARS-CoV-2 evolution mechanism and forecast emerging vaccine-breakthrough variants. We show that prevailing variants can be quantitatively explained by infectivity-strengthening and vaccine-escape (co-)mutations on the spike protein RBD due to natural selection and/or vaccination-induced evolutionary pressure. We illustrate that infectivity strengthening mutations were the main mechanism for viral evolution, while vaccine-escape mutations become a dominating viral evolutionary mechanism among highly vaccinated populations. We demonstrate that Lambda is as infectious as Delta but is more vaccine-resistant. We analyze emerging vaccine-breakthrough comutations in highly vaccinated countries, including the United Kingdom, the United States, Denmark, and so forth. Finally, we identify sets of comutations that have a high likelihood of massive growth: [A411S, L452R, T478K], [L452R, T478K, N501Y], [V401L, L452R, T478K], [K417N, L452R, T478K], [L452R, T478K, E484K, N501Y], and [P384L, K417N, E484K, N501Y]. We predict they can escape existing vaccines. We foresee an urgent need to develop new virus combating strategies.
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Affiliation(s)
- Rui Wang
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Hozumi
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Changchuan Yin
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, Illinois 60607, United States
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department of Biochemistry and Molecular Biology Michigan State University, East Lansing, Michigan 48824, United States
- Department of Electrical and Computer Engineering Michigan State University, East Lansing, Michigan 48824, United States
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24
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Polanco C, Uversky VN, Dayhoff GW, Huberman A, Buhse T, Márquez MF, Vargas-Alarcón G, Castañón-González JA, Andrés L, Dı́az-González JL, González-Bañales K. Bioinformatics-Based Characterization of Proteins Related to SARS-CoV- 2 Using the Polarity Index Method® (PIM®) and Intrinsic Disorder Predisposition. CURR PROTEOMICS 2022. [DOI: 10.2174/1570164618666210106114606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
The global outbreak of the 2019 novel Coronavirus Disease (COVID-19) caused by the infection with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which appeared in China at the end of
2019, signifies a major public health issue at the current time.
Objective:
The objective of the present study is to characterize the physicochemical properties of the SARS-CoV-2 proteins at a residues level, and to generate a “bioinformatics fingerprint” in the form of a “PIM® profile” created for each
sequence utilizing the Polarity Index Method® (PIM®), suitable for the identification of these proteins.
Methods:
Two different bioinformatics approaches were used to analyze sequence characteristics of these proteins at
the residues level, an in-house bioinformatics system PIM®, and a set of the commonly used algorithms for the predic-tion of protein intrinsic disorder predisposition, such as PONDR® VLXT, PONDR® VL3, PONDR® VSL2, PONDR®
FIT, IUPred_short and IUPred_long. The PIM® profile was generated for four SARS-CoV-2 structural proteins and
compared with the corresponding profiles of the SARS-CoV-2 non-structural proteins, SARS-CoV-2 putative proteins,
SARS-CoV proteins, MERS-CoV proteins, sets of bacterial, fungal, and viral proteins, cell-penetrating peptides, and a
set of intrinsically disordered proteins. We also searched for the UniProt proteins with PIM® profiles similar to those of
SARS-CoV-2 structural, non-structural, and putative proteins.
Results:
We show that SARS-CoV-2 structural, non-structural, and putative proteins are characterized by a unique
PIM® profile. A total of 1736 proteins were identified from the 562,253 “reviewed” proteins from the UniProt database,
whose PIM® profile was similar to that of the SARS-CoV-2 structural, non-structural, and putative proteins.
Conclusion:
The PIM® profile represents an important characteristic that might be useful for the identification of proteins similar to SARS-CoV-2 proteins.
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Affiliation(s)
- Carlos Polanco
- Department of Electromechanical Instrumentation, Instituto Nacional de Cardiología “Ignacio Chávez”, México City
14800, México
- Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de México, México
City 04510, México
| | - Vladimir N. Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer\'s Research Institute, Morsani
College of Medicine, University of South Florida, Tampa, FL33647, USA
- Protein Research Group, Institute for
Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center “Pushchino Scientific Center
for Biological Research of the Russian Academy of Sciences”, 142290 Pushchino, Moscow region, Russia
| | - Guy W. Dayhoff
- Department of Molecular Medicine and USF Health Byrd Alzheimer\'s Research Institute, Morsani
College of Medicine, University of South Florida, Tampa, FL33647, USA
| | - Alberto Huberman
- Department of Biochemistry, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, C.P. 14080 México City,
México
| | - Thomas Buhse
- Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, Cuernavaca Morelos
62209, México
| | - Manlio F. Márquez
- Subdirección de Investigación Clínica, Instituto Nacional de Cardiología “Ignacio Chávez”, México
City 14800, México
| | - Gilberto Vargas-Alarcón
- Dirección de Investigación, Instituto Nacional de Cardiología “Ignacio Chávez”, México City
14800, México
| | | | - Leire Andrés
- Department
of Pathology, Hospital de Cruces, 48903, Barakaldo, Spain
| | - Juan Luciano Dı́az-González
- Department of Computer Sciences, Instituto de
Ciencias Nucleares, Universidad Nacional Autónoma de México, México City 04510, México
| | - Karina González-Bañales
- Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de México, México
City 04510, México
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25
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Chen J, Wang R, Gilby NB, Wei GW. Omicron Variant (B.1.1.529): Infectivity, Vaccine Breakthrough, and Antibody Resistance. J Chem Inf Model 2022; 62:412-422. [PMID: 34989238 PMCID: PMC8751645 DOI: 10.1021/acs.jcim.1c01451] [Citation(s) in RCA: 415] [Impact Index Per Article: 207.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Indexed: 02/08/2023]
Abstract
The latest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant Omicron (B.1.1.529) has ushered panic responses around the world due to its contagious and vaccine escape mutations. The essential infectivity and antibody resistance of the SARS-CoV-2 variant are determined by its mutations on the spike (S) protein receptor-binding domain (RBD). However, a complete experimental evaluation of Omicron might take weeks or even months. Here, we present a comprehensive quantitative analysis of Omicron's infectivity, vaccine breakthrough, and antibody resistance. An artificial intelligence (AI) model, which has been trained with tens of thousands of experimental data and extensively validated by experimental results on SARS-CoV-2, reveals that Omicron may be over 10 times more contagious than the original virus or about 2.8 times as infectious as the Delta variant. On the basis of 185 three-dimensional (3D) structures of antibody-RBD complexes, we unveil that Omicron may have an 88% likelihood to escape current vaccines. The U.S. Food and Drug Administration (FDA)-approved monoclonal antibodies (mAbs) from Eli Lilly may be seriously compromised. Omicron may also diminish the efficacy of mAbs from AstraZeneca, Regeneron mAb cocktail, Celltrion, and Rockefeller University. However, its impacts on GlaxoSmithKline's sotrovimab appear to be mild. Our work calls for new strategies to develop the next generation mutation-proof SARS-CoV-2 vaccines and antibodies.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Nancy Benovich Gilby
- Spartan Innovations, 325 East Grand River Ave., Suite 355, East Lansing, MI 48823 USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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26
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Wang R, Chen J, Wei GW. Mechanisms of SARS-CoV-2 Evolution Revealing Vaccine-Resistant Mutations in Europe and America. J Phys Chem Lett 2021; 12:11850-11857. [PMID: 34873910 PMCID: PMC8672435 DOI: 10.1021/acs.jpclett.1c03380] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/02/2021] [Indexed: 05/20/2023]
Abstract
The importance of understanding SARS-CoV-2 evolution cannot be overlooked. Recent studies confirm that natural selection is the dominating mechanism of SARS-CoV-2 evolution, which favors mutations that strengthen viral infectivity. Here, we demonstrate that vaccine-breakthrough or antibody-resistant mutations provide a new mechanism of viral evolution. Specifically, vaccine-resistant mutation Y449S in the spike (S) protein receptor-binding domain, which occurred in co-mutations Y449S and N501Y, has reduced infectivity compared to that of the original SARS-CoV-2 but can disrupt existing antibodies that neutralize the virus. By tracking the evolutionary trajectories of vaccine-resistant mutations in more than 2.2 million SARS-CoV-2 genomes, we reveal that the occurrence and frequency of vaccine-resistant mutations correlate strongly with the vaccination rates in Europe and America. We anticipate that as a complementary transmission pathway, vaccine-breakthrough or antibody-resistant mutations, like those in Omicron, will become a dominating mechanism of SARS-CoV-2 evolution when most of the world's population is either vaccinated or infected. Our study sheds light on SARS-CoV-2 evolution and transmission and enables the design of the next-generation mutation-proof vaccines and antibody drugs.
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Affiliation(s)
- Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering Michigan State University, MI 48824, USA
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27
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Chen J, Wang R, Gilby NB, Wei GW. Omicron (B.1.1.529): Infectivity, vaccine breakthrough, and antibody resistance. ARXIV 2021:arXiv:2112.01318v1. [PMID: 34873578 PMCID: PMC8647651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
The latest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant Omicron (B.1.1.529) has ushered panic responses around the world due to its contagious and vaccine escape mutations. The essential infectivity and antibody resistance of the SARS-CoV-2 variant are determined by its mutations on the spike (S) protein receptor-binding domain (RBD). However, a complete experimental evaluation of Omicron might take weeks or even months. Here, we present a comprehensive quantitative analysis of Omicron's infectivity, vaccine-breakthrough, and antibody resistance. An artificial intelligence (AI) model, which has been trained with tens of thousands of experimental data points and extensively validated by experimental data on SARS-CoV-2, reveals that Omicron may be over ten times more contagious than the original virus or about twice as infectious as the Delta variant. Based on 132 three-dimensional (3D) structures of antibody-RBD complexes, we unveil that Omicron may be twice more likely to escape current vaccines than the Delta variant. The Food and Drug Administration (FDA)-approved monoclonal antibodies (mAbs) from Eli Lilly may be seriously compromised. Omicron may also diminish the efficacy of mAbs from Celltrion and Rockefeller University. However, its impact on Regeneron mAb cocktail appears to be mild.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Nancy Benovich Gilby
- Spartan Innovations, 325 East Grand River Ave., Suite 355, East Lansing, MI 48823 USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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28
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Peng MS, Li JB, Cai ZF, Liu H, Tang X, Ying R, Zhang JN, Tao JJ, Yin TT, Zhang T, Hu JY, Wu RN, Zhou ZY, Zhang ZG, Yu L, Yao YG, Shi ZL, Lu XM, Lu J, Zhang YP. The high diversity of SARS-CoV-2-related coronaviruses in pangolins alerts potential ecological risks. Zool Res 2021; 42:834-844. [PMID: 34766482 PMCID: PMC8645874 DOI: 10.24272/j.issn.2095-8137.2021.334] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/09/2021] [Indexed: 11/07/2022] Open
Abstract
Understanding the zoonotic origin and evolution history of SARS-CoV-2 will provide critical insights for alerting and preventing future outbreaks. A significant gap remains for the possible role of pangolins as a reservoir of SARS-CoV-2 related coronaviruses (SC2r-CoVs). Here, we screened SC2r-CoVs in 172 samples from 163 pangolin individuals of four species, and detected positive signals in muscles of four Manis javanica and, for the first time, one M. pentadactyla. Phylogeographic analysis of pangolin mitochondrial DNA traced their origins from Southeast Asia. Using in-solution hybridization capture sequencing, we assembled a partial pangolin SC2r-CoV (pangolin-CoV) genome sequence of 22 895 bp (MP20) from the M. pentadactyla sample. Phylogenetic analyses revealed MP20 was very closely related to pangolin-CoVs that were identified in M. javanica seized by Guangxi Customs. A genetic contribution of bat coronavirus to pangolin-CoVs via recombination was indicated. Our analysis revealed that the genetic diversity of pangolin-CoVs is substantially higher than previously anticipated. Given the potential infectivity of pangolin-CoVs, the high genetic diversity of pangolin-CoVs alerts the ecological risk of zoonotic evolution and transmission of pathogenic SC2r-CoVs.
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Affiliation(s)
- Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China. E-mail:
| | - Jian-Bo Li
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
| | - Zheng-Fei Cai
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, Yunnan 650091, China
| | - Hang Liu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
| | - Xiaolu Tang
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Ruochen Ying
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Jia-Nan Zhang
- Molbreeding Biotechnology Co., Ltd., Shijiazhuang, Hebei 050035, China
| | - Jia-Jun Tao
- Molbreeding Biotechnology Co., Ltd., Shijiazhuang, Hebei 050035, China
| | - Ting-Ting Yin
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Tao Zhang
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, Yunnan 650091, China
| | - Jing-Yang Hu
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, Yunnan 650091, China
| | - Ru-Nian Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Zhong-Yin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Zhi-Gang Zhang
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, Yunnan 650091, China
| | - Li Yu
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, Yunnan 650091, China
| | - Yong-Gang Yao
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan 650201, China
| | - Zheng-Li Shi
- CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, Hubei 430071, China
| | - Xue-Mei Lu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Jian Lu
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China. E-mail:
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, Yunnan 650091, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650201, China. E-mail:
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Khan A, Khan T, Ali S, Aftab S, Wang Y, Qiankun W, Khan M, Suleman M, Ali S, Heng W, Ali SS, Wei DQ, Mohammad A. SARS-CoV-2 new variants: Characteristic features and impact on the efficacy of different vaccines. Biomed Pharmacother 2021; 143:112176. [PMID: 34562770 PMCID: PMC8433040 DOI: 10.1016/j.biopha.2021.112176] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 01/10/2023] Open
Abstract
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its new variants reported in different countries have posed a serious threat to human health and social fabrics worldwide. In addition, these new variants hindered the efforts of vaccines and other therapeutic developments. In this review article, we explained the emergence of new variants of SARS-CoV-2, their transmission risk, mortality rate, and, more importantly, the impact of each new variant on the efficacy of the developed vaccines reported in different literature and findings. The literature reported that with the emergence of new variants, the efficacy of different vaccines is declined, hospitalization and the risk of reinfection is increased. The reports concluded that the emergence of a variant that entirely evades the immune response triggered by the vaccine is improbable. The emergence of new variants and reports of re-infections are creating a more distressing situation and therefore demands further investigation to formulate an effective therapeutic strategy.
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Affiliation(s)
- Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Taimoor Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Shughla Ali
- Department of Zoology, Swat College of Science and Technology (SCST), Swat, Khyber Pakhtunkhwa, Pakistan
| | - Summiya Aftab
- Department of Zoology, Government Girls Degree College, Thana, Khyber Pakhtunkhwa, Pakistan
| | - Yanjing Wang
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Wang Qiankun
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Mazhar Khan
- The CAS Key Laboratory of Innate Immunity and Chronic Diseases, Hefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, CAS Center for Excellence in Molecular Cell Science, University of Science and Technology of China (USTC), Collaborative Innovation Center of Genetics and Development, Hefei 230027, Anhui, PR China
| | - Muhammad Suleman
- Center for Biotechnology and Microbiology, University of Swat, Kanju Campus, Swat, Pakistan
| | - Shahid Ali
- Center for Biotechnology and Microbiology, University of Swat, Kanju Campus, Swat, Pakistan
| | - Wang Heng
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China.
| | - Syed Shujait Ali
- Center for Biotechnology and Microbiology, University of Swat, Kanju Campus, Swat, Pakistan
| | - Dong-Qing Wei
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China; Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong 518055, PR China; State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, PR China.
| | - Anwar Mohammad
- Department of Biochemistry and Molecular Biology, Dasman Diabetes Institute, Kuwait
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30
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Wang R, Chen J, Wei GW. The evolution of the mechanisms of SARS-CoV-2 evolution revealing vaccine-resistant mutations in Europe and America. ARXIV 2021:arXiv:2110.04626v1. [PMID: 34642638 PMCID: PMC8509097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The importance of understanding SARS-CoV-2 evolution cannot be overemphasized. Recent studies confirm that natural selection is the dominating mechanism of SARS-CoV-2 evolution, which favors mutations that strengthen viral infectivity. We demonstrate that vaccine-breakthrough or antibody-resistant mutations provide a new mechanism of viral evolution. Specifically, vaccine-resistant mutation Y449S in the spike (S) protein receptor-bonding domain (RBD), which occurred in co-mutation [Y449S, N501Y], has reduced infectivity compared to the original SARS-CoV-2 but can disrupt existing antibodies that neutralize the virus. By tracing the evolutionary trajectories of vaccine-resistant mutations in over 1.9 million SARS-CoV-2 genomes, we reveal that the occurrence and frequency of vaccine-resistant mutations correlate strongly with the vaccination rates in Europe and America. We anticipate that as a complementary transmission pathway, vaccine-resistant mutations will become a dominating mechanism of SARS-CoV-2 evolution when most of the world's population is vaccinated. Our study sheds light on SARS-CoV-2 evolution and transmission and enables the design of the next-generation mutation-proof vaccines and antibody drugs.
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Affiliation(s)
- Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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31
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Chen J, Wang R, Wei GW. Review of the mechanisms of SARS-CoV-2 evolution and transmission. ARXIV 2021:arXiv:2109.08148v1. [PMID: 34545334 PMCID: PMC8452100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution and transmission is elusive and its understanding, a prerequisite to forecast emerging variants, is of paramount importance. SARS-CoV-2 evolution is driven by the mechanisms at molecular and organism scales and regulated by the transmission pathways at the population scale. In this review, we show that infectivity-based natural selection was discovered as the mechanism for SARS-CoV-2 evolution and transmission in July 2020. In April 2021, we proved beyond all doubt that such a natural selection via infectivity-based transmission pathway remained the sole mechanism for SARS-CoV-2 evolution. However, we reveal that antibody-disruptive co-mutations [Y449S, N501Y] on the spike protein receptor-binding domain (RBD) debuted as a new vaccine-resistant transmission pathway of viral evolution in highly vaccinated populations a few months ago. Over one year ago, we foresaw that mutations on RBD residues, 452 and 501, would "both have high chances to mutate into significantly more infectious COVID-19 strains". Mutations on these residues underpin prevailing SARS-CoV-2 variants Alpha, Beta, Gamma, Delta, Epsilon, Theta, Kappa, Lambda, and Mu at present and are expected to be vital to emerging variants in the future. We anticipate that viral evolution will combine RBD co-mutations at these two sites, creating future variants that are about ten times more infectious than the original SARS-CoV-2. Additionally, two complementary transmission pathways of viral evolution, i.e., infectivity and vaccine resistance will prolong our battle with COVID-19 for years. We predict that RBD co-mutation sets [A411S, L452R, T478K], [L452R, T478K, N501Y], [L452R, T478K, E484K, N501Y], [K417N, L452R, T478K], and [P384L, K417N, E484K, N501Y] will have a high chance to grow into dominating variants due to their high infectivity and/or strong ability to break through current vaccines, calling for the development of new vaccines and antibody therapies.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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Wang R, Chen J, Hozumi Y, Yin C, Wei GW. Emerging vaccine-breakthrough SARS-CoV-2 variants. ARXIV 2021:arXiv:2109.04509v1. [PMID: 34518803 PMCID: PMC8437313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The recent global surge in COVID-19 infections has been fueled by new SARS-CoV-2 variants, namely Alpha, Beta, Gamma, Delta, etc. The molecular mechanism underlying such surge is elusive due to 4,653 non-degenerate mutations on the spike protein, which is the target of most COVID-19 vaccines. The understanding of the molecular mechanism of transmission and evolution is a prerequisite to foresee the trend of emerging vaccine-breakthrough variants and the design of mutation-proof vaccines and monoclonal antibodies. We integrate the genotyping of 1,489,884 SARS-CoV-2 genomes isolates, 130 human antibodies, tens of thousands of mutational data points, topological data analysis, and deep learning to reveal SARS-CoV-2 evolution mechanism and forecast emerging vaccine-escape variants. We show that infectivity-strengthening and antibody-disruptive co-mutations on the S protein RBD can quantitatively explain the infectivity and virulence of all prevailing variants. We demonstrate that Lambda is as infectious as Delta but is more vaccine-resistant. We analyze emerging vaccine-breakthrough co-mutations in 20 countries, including the United Kingdom, the United States, Denmark, Brazil, and Germany, etc. We envision that natural selection through infectivity will continue to be the main mechanism for viral evolution among unvaccinated populations, while antibody disruptive co-mutations will fuel the future growth of vaccine-breakthrough variants among fully vaccinated populations. Finally, we have identified the co-mutations that have the great likelihood of becoming dominant: [A411S, L452R, T478K], [L452R, T478K, N501Y], [V401L, L452R, T478K], [K417N, L452R, T478K], [L452R, T478K, E484K, N501Y], and [P384L, K417N, E484K, N501Y]. We predict they, particularly the last four, will break through existing vaccines. We foresee an urgent need to develop new vaccines that target these co-mutations.
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Affiliation(s)
- Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Yuta Hozumi
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Changchuan Yin
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
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Chen J, Gao K, Wang R, Wei GW. Revealing the Threat of Emerging SARS-CoV-2 Mutations to Antibody Therapies. J Mol Biol 2021; 433:167155. [PMID: 34273397 PMCID: PMC8277955 DOI: 10.1016/j.jmb.2021.167155] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/16/2021] [Accepted: 07/06/2021] [Indexed: 01/09/2023]
Abstract
The ongoing massive vaccination and the development of effective intervention offer the long-awaited hope to end the global rage of the COVID-19 pandemic. However, the rapidly growing SARS-CoV-2 variants might compromise existing vaccines and monoclonal antibody (mAb) therapies. Although there are valuable experimental studies about the potential threats from emerging variants, the results are limited to a handful of mutations and Eli Lilly and Regeneron mAbs. The potential threats from frequently occurring mutations on the SARS-CoV-2 spike (S) protein receptor-binding domain (RBD) to many mAbs in clinical trials are largely unknown. We fill the gap by developing a topology-based deep learning strategy that is validated with tens of thousands of experimental data points. We analyze 796,759 genome isolates from patients to identify 606 non-degenerate RBD mutations and investigate their impacts on 16 mAbs in clinical trials. Our findings, which are highly consistent with existing experimental results about Alpha, Beta, Gamma, Delta, Epsilon, and Kappa variants shed light on potential threats of 100 most observed mutations to mAbs not only from Eli Lilly and Regeneron but also from Celltrion and Rockefeller University that are in clinical trials. We unveil, for the first time, that high-frequency mutations R346K/S, N439K, G446V, L455F, V483F/A, F486L, F490L/S, Q493L, and S494P might compromise some of mAbs in clinical trials. Our study gives rise to a general perspective about how mutations will affect current vaccines.
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Affiliation(s)
- Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Kaifu Gao
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA.
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Szemiel AM, Merits A, Orton RJ, MacLean OA, Pinto RM, Wickenhagen A, Lieber G, Turnbull ML, Wang S, Furnon W, Suarez NM, Mair D, da Silva Filipe A, Willett BJ, Wilson SJ, Patel AH, Thomson EC, Palmarini M, Kohl A, Stewart ME. In vitro selection of Remdesivir resistance suggests evolutionary predictability of SARS-CoV-2. PLoS Pathog 2021; 17:e1009929. [PMID: 34534263 PMCID: PMC8496873 DOI: 10.1371/journal.ppat.1009929] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 10/07/2021] [Accepted: 08/30/2021] [Indexed: 01/18/2023] Open
Abstract
Remdesivir (RDV), a broadly acting nucleoside analogue, is the only FDA approved small molecule antiviral for the treatment of COVID-19 patients. To date, there are no reports identifying SARS-CoV-2 RDV resistance in patients, animal models or in vitro. Here, we selected drug-resistant viral populations by serially passaging SARS-CoV-2 in vitro in the presence of RDV. Using high throughput sequencing, we identified a single mutation in RNA-dependent RNA polymerase (NSP12) at a residue conserved among all coronaviruses in two independently evolved populations displaying decreased RDV sensitivity. Introduction of the NSP12 E802D mutation into our SARS-CoV-2 reverse genetics backbone confirmed its role in decreasing RDV sensitivity in vitro. Substitution of E802 did not affect viral replication or activity of an alternate nucleoside analogue (EIDD2801) but did affect virus fitness in a competition assay. Analysis of the globally circulating SARS-CoV-2 variants (>800,000 sequences) showed no evidence of widespread transmission of RDV-resistant mutants. Surprisingly, we observed an excess of substitutions in spike at corresponding sites identified in the emerging SARS-CoV-2 variants of concern (i.e., H69, E484, N501, H655) indicating that they can arise in vitro in the absence of immune selection. The identification and characterisation of a drug resistant signature within the SARS-CoV-2 genome has implications for clinical management and virus surveillance.
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Affiliation(s)
| | - Andres Merits
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Richard J. Orton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Oscar A. MacLean
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Rute Maria Pinto
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Arthur Wickenhagen
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Gauthier Lieber
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Matthew L. Turnbull
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Sainan Wang
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Nicolas M. Suarez
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Daniel Mair
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Ana da Silva Filipe
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Brian J. Willett
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Sam J. Wilson
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Arvind H. Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Emma C. Thomson
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Massimo Palmarini
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Alain Kohl
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Meredith E. Stewart
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
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Singh J, Pandit P, McArthur AG, Banerjee A, Mossman K. Evolutionary trajectory of SARS-CoV-2 and emerging variants. Virol J 2021; 18:166. [PMID: 34389034 PMCID: PMC8361246 DOI: 10.1186/s12985-021-01633-w] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/03/2021] [Indexed: 12/17/2022] Open
Abstract
The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more recently, the independent evolution of multiple SARS-CoV-2 variants has generated renewed interest in virus evolution and cross-species transmission. While all known human coronaviruses (HCoVs) are speculated to have originated in animals, very little is known about their evolutionary history and factors that enable some CoVs to co-exist with humans as low pathogenic and endemic infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1), while others, such as SARS-CoV, MERS-CoV and SARS-CoV-2 have evolved to cause severe disease. In this review, we highlight the origins of all known HCoVs and map positively selected for mutations within HCoV proteins to discuss the evolutionary trajectory of SARS-CoV-2. Furthermore, we discuss emerging mutations within SARS-CoV-2 and variants of concern (VOC), along with highlighting the demonstrated or speculated impact of these mutations on virus transmission, pathogenicity, and neutralization by natural or vaccine-mediated immunity.
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Affiliation(s)
- Jalen Singh
- School of Interdisciplinary Science, McMaster University, Hamilton, ON, Canada
| | - Pranav Pandit
- EpiCenter for Disease Dynamics, One Health Institute, School of Veterinary Medicine, University of California Davis, Davis, CA, USA
| | - Andrew G McArthur
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
| | - Arinjay Banerjee
- Vaccine and Infectious Disease Organization, University of Saskatchewan, Saskatoon, SK, Canada.
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
- Department of Biology, University of Waterloo, Waterloo, ON, Canada.
| | - Karen Mossman
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada.
- Department of Medicine, McMaster University, Hamilton, ON, Canada.
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada.
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36
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Wang R, Chen J, Gao K, Wei GW. Vaccine-escape and fast-growing mutations in the United Kingdom, the United States, Singapore, Spain, India, and other COVID-19-devastated countries. Genomics 2021; 113:2158-2170. [PMID: 34004284 PMCID: PMC8123493 DOI: 10.1016/j.ygeno.2021.05.006] [Citation(s) in RCA: 134] [Impact Index Per Article: 44.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 04/30/2021] [Accepted: 05/10/2021] [Indexed: 01/04/2023]
Abstract
Recently, the SARS-CoV-2 variants from the United Kingdom (UK), South Africa, and Brazil have received much attention for their increased infectivity, potentially high virulence, and possible threats to existing vaccines and antibody therapies. The question remains if there are other more infectious variants transmitted around the world. We carry out a large-scale study of 506,768 SARS-CoV-2 genome isolates from patients to identify many other rapidly growing mutations on the spike (S) protein receptor-binding domain (RBD). We reveal that essentially all 100 most observed mutations strengthen the binding between the RBD and the host angiotensin-converting enzyme 2 (ACE2), indicating the virus evolves toward more infectious variants. In particular, we discover new fast-growing RBD mutations N439K, S477N, S477R, and N501T that also enhance the RBD and ACE2 binding. We further unveil that mutation N501Y involved in United Kingdom (UK), South Africa, and Brazil variants may moderately weaken the binding between the RBD and many known antibodies, while mutations E484K and K417N found in South Africa and Brazilian variants, L452R and E484Q found in India variants, can potentially disrupt the binding between the RBD and many known antibodies. Among these RBD mutations, L452R is also now known as part of the California variant B.1.427. Finally, we hypothesize that RBD mutations that can simultaneously make SARS-CoV-2 more infectious and disrupt the existing antibodies, called vaccine escape mutations, will pose an imminent threat to the current crop of vaccines. A list of most likely vaccine escape mutations is given, including S494P, Q493L, K417N, F490S, F486L, R403K, E484K, L452R, K417T, F490L, E484Q, and A475S. Mutation T478K appears to make the Mexico variant B.1.1.222 the most infectious one. Our comprehensive genetic analysis and protein-protein binding study show that the genetic evolution of SARS-CoV-2 on the RBD, which may be regulated by host gene editing, viral proofreading, random genetic drift, and natural selection, gives rise to more infectious variants that will potentially compromise existing vaccines and antibody therapies.
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Affiliation(s)
- Rui Wang
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Jiahui Chen
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Kaifu Gao
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA.
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Anand U, Jakhmola S, Indari O, Jha HC, Chen ZS, Tripathi V, Pérez de la Lastra JM. Potential Therapeutic Targets and Vaccine Development for SARS-CoV-2/COVID-19 Pandemic Management: A Review on the Recent Update. Front Immunol 2021; 12:658519. [PMID: 34276652 PMCID: PMC8278575 DOI: 10.3389/fimmu.2021.658519] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 06/07/2021] [Indexed: 01/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a highly pathogenic novel virus that has caused a massive pandemic called coronavirus disease 2019 (COVID-19) worldwide. Wuhan, a city in China became the epicenter of the outbreak of COVID-19 in December 2019. The disease was declared a pandemic globally by the World Health Organization (WHO) on 11 March 2020. SARS-CoV-2 is a beta CoV of the Coronaviridae family which usually causes respiratory symptoms that resemble common cold. Multiple countries have experienced multiple waves of the disease and scientific experts are consistently working to find answers to several unresolved questions, with the aim to find the most suitable ways to contain the virus. Furthermore, potential therapeutic strategies and vaccine development for COVID-19 management are also considered. Currently, substantial efforts have been made to develop successful and safe treatments and SARS-CoV-2 vaccines. Some vaccines, such as inactivated vaccines, nucleic acid-based, and vector-based vaccines, have entered phase 3 clinical trials. Additionally, diverse small molecule drugs, peptides and antibodies are being developed to treat COVID-19. We present here an overview of the virus interaction with the host and environment and anti-CoV therapeutic strategies; including vaccines and other methodologies, designed for prophylaxis and treatment of SARS-CoV-2 infection with the hope that this integrative analysis could help develop novel therapeutic approaches against COVID-19.
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Affiliation(s)
- Uttpal Anand
- Department of Life Sciences, National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Shweta Jakhmola
- Discipline of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Indore, India
| | - Omkar Indari
- Discipline of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Indore, India
| | - Hem Chandra Jha
- Discipline of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Indore, India
| | - Zhe-Sheng Chen
- Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John’s University, Queens, NY, United States
| | - Vijay Tripathi
- Department of Molecular and Cellular Engineering, Jacob Institute of Biotechnology and Bioengineering, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, India
| | - José M. Pérez de la Lastra
- Instituto de Productos Naturales y Agrobiología (IPNA), Consejo Superior de Investigaciones científicas (CSIS), Santa Cruz de Tenerife, Spain
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Magrone T, Magrone M, Jirillo E. Focus on Receptors for Coronaviruses with Special Reference to Angiotensin- Converting Enzyme 2 as a Potential Drug Target - A Perspective. Endocr Metab Immune Disord Drug Targets 2021; 20:807-811. [PMID: 32338224 DOI: 10.2174/1871530320666200427112902] [Citation(s) in RCA: 131] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 03/26/2020] [Accepted: 04/03/2020] [Indexed: 01/08/2023]
Affiliation(s)
- Thea Magrone
- Department of Basic Medical Sciences, Neuroscience and Sensory Organs, University of Bari, School of Medicine, Bari, Italy
| | - Manrico Magrone
- Department of Basic Medical Sciences, Neuroscience and Sensory Organs, University of Bari, School of Medicine, Bari, Italy
| | - Emilio Jirillo
- Department of Basic Medical Sciences, Neuroscience and Sensory Organs, University of Bari, School of Medicine, Bari, Italy
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39
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Faria NR, Mellan TA, Whittaker C, Claro IM, Candido DDS, Mishra S, Crispim MAE, Sales FCS, Hawryluk I, McCrone JT, Hulswit RJG, Franco LAM, Ramundo MS, de Jesus JG, Andrade PS, Coletti TM, Ferreira GM, Silva CAM, Manuli ER, Pereira RHM, Peixoto PS, Kraemer MUG, Gaburo N, Camilo CDC, Hoeltgebaum H, Souza WM, Rocha EC, de Souza LM, de Pinho MC, Araujo LJT, Malta FSV, de Lima AB, Silva JDP, Zauli DAG, Ferreira ACDS, Schnekenberg RP, Laydon DJ, Walker PGT, Schlüter HM, Dos Santos ALP, Vidal MS, Del Caro VS, Filho RMF, Dos Santos HM, Aguiar RS, Proença-Modena JL, Nelson B, Hay JA, Monod M, Miscouridou X, Coupland H, Sonabend R, Vollmer M, Gandy A, Prete CA, Nascimento VH, Suchard MA, Bowden TA, Pond SLK, Wu CH, Ratmann O, Ferguson NM, Dye C, Loman NJ, Lemey P, Rambaut A, Fraiji NA, Carvalho MDPSS, Pybus OG, Flaxman S, Bhatt S, Sabino EC. Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil. Science 2021; 372:815-821. [PMID: 33853970 PMCID: PMC8139423 DOI: 10.1126/science.abh2644] [Citation(s) in RCA: 905] [Impact Index Per Article: 301.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 04/11/2021] [Indexed: 12/17/2022]
Abstract
Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.
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Affiliation(s)
- Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - Thomas A Mellan
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Ingra M Claro
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Darlan da S Candido
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Myuki A E Crispim
- Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
- Diretoria de Ensino e Pesquisa, Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
| | - Flavia C S Sales
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Iwona Hawryluk
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Ruben J G Hulswit
- Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Lucas A M Franco
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Mariana S Ramundo
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Jaqueline G de Jesus
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Pamela S Andrade
- Departamento de Epidemiologia, Faculdade de Saúde Pública da Universidade de São Paulo, Sao Paulo, Brazil
| | - Thais M Coletti
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Giulia M Ferreira
- Laboratório de Virologia, Instituto de Ciências Biomédicas, Universidade Federal de Uberlândia, Uberlândia, Brazil
| | - Camila A M Silva
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Erika R Manuli
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | | | - Pedro S Peixoto
- Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil
| | | | | | | | | | - William M Souza
- Virology Research Centre, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Esmenia C Rocha
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Leandro M de Souza
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Mariana C de Pinho
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Leonardo J T Araujo
- Laboratory of Quantitative Pathology, Center of Pathology, Adolfo Lutz Institute, São Paulo, Brazil
| | | | | | | | | | | | | | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | | | | | | | | | | | | | - Renato S Aguiar
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - José L Proença-Modena
- Laboratory of Emerging Viruses, Department of Genetics, Evolution, Microbiology, and Immunology, Institute of Biology, University of Campinas (UNICAMP), São Paulo, Brazil
| | - Bruce Nelson
- Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil
| | - James A Hay
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Mélodie Monod
- Department of Mathematics, Imperial College London, London, UK
| | | | - Helen Coupland
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Raphael Sonabend
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Michaela Vollmer
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Axel Gandy
- Department of Mathematics, Imperial College London, London, UK
| | - Carlos A Prete
- Departamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica da Universidade de São Paulo, São Paulo, Brazil
| | - Vitor H Nascimento
- Departamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica da Universidade de São Paulo, São Paulo, Brazil
| | - Marc A Suchard
- Department of Biomathematics, Department of Biostatistics, and Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Thomas A Bowden
- Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Sergei L K Pond
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK
| | - Oliver Ratmann
- Department of Mathematics, Imperial College London, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | | | - Nick J Loman
- Institute for Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Nelson A Fraiji
- Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
- Diretoria Clínica, Fundação Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil
| | - Maria do P S S Carvalho
- Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
- Diretoria da Presidência, Fundação Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK
| | - Seth Flaxman
- Department of Mathematics, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Ester C Sabino
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
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40
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Jelinek HF, Mousa M, Alefishat E, Osman W, Spence I, Bu D, Feng SF, Byrd J, Magni PA, Sahibzada S, Tay GK, Alsafar HS. Evolution, Ecology, and Zoonotic Transmission of Betacoronaviruses: A Review. Front Vet Sci 2021; 8:644414. [PMID: 34095271 PMCID: PMC8173069 DOI: 10.3389/fvets.2021.644414] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/25/2021] [Indexed: 12/18/2022] Open
Abstract
Coronavirus infections have been a part of the animal kingdom for millennia. The difference emerging in the twenty-first century is that a greater number of novel coronaviruses are being discovered primarily due to more advanced technology and that a greater number can be transmitted to humans, either directly or via an intermediate host. This has a range of effects from annual infections that are mild to full-blown pandemics. This review compares the zoonotic potential and relationship between MERS, SARS-CoV, and SARS-CoV-2. The role of bats as possible host species and possible intermediate hosts including pangolins, civets, mink, birds, and other mammals are discussed with reference to mutations of the viral genome affecting zoonosis. Ecological, social, cultural, and environmental factors that may play a role in zoonotic transmission are considered with reference to SARS-CoV, MERS, and SARS-CoV-2 and possible future zoonotic events.
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Affiliation(s)
- Herbert F. Jelinek
- Center for Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Biomedical Engineering, College of Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Center of Heath Engineering Innovation, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Mira Mousa
- Nuffield Department of Women's and Reproduction Health, Oxford University, Oxford, United Kingdom
| | - Eman Alefishat
- Center for Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Pharmacology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Wael Osman
- Department of Chemistry, College of Arts and Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Ian Spence
- Discipline of Pharmacology, University of Sydney, Sydney, NSW, Australia
| | - Dengpan Bu
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Samuel F. Feng
- Center for Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Mathematics, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Jason Byrd
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, United States
| | - Paola A. Magni
- Discipline of Medical, Molecular and Forensic Sciences, Murdoch University, Murdoch, WA, Australia
- Murdoch University Singapore, King's Centre, Singapore, Singapore
| | - Shafi Sahibzada
- Antimicrobial Resistance and Infectious Diseases Laboratory, College of Science, Health, Engineering and Education, Murdoch University, Murdoch, WA, Australia
| | - Guan K. Tay
- Center for Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Division of Psychiatry, Faculty of Health and Medical Sciences, The University of Western Australia, Crawley, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Habiba S. Alsafar
- Center for Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Biomedical Engineering, College of Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Genetics and Molecular Biology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
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41
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Singh A, Dhar R. A large-scale computational screen identifies strong potential inhibitors for disrupting SARS-CoV-2 S-protein and human ACE2 interaction. J Biomol Struct Dyn 2021; 40:9004-9017. [PMID: 33998954 PMCID: PMC8146306 DOI: 10.1080/07391102.2021.1921034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 04/19/2021] [Indexed: 02/07/2023]
Abstract
SARS-CoV-2 has infected millions of individuals across the globe and has killed over 2.7 million people. Even though vaccines against this virus have recently been introduced, the antibody generated in the process has been reported to decline quickly. This can reduce the efficacy of vaccines over time and can result in re-infections. Thus, drugs that are effective against COVID-19 can provide a second line of defence and can prevent occurrence of the severe form of the disease. The interaction between SARS-CoV2 S-protein and human ACE2 (hACE2) is essential for the infection of the virus. Thus, drugs that block this interaction could potentially inhibit SARS-CoV-2 infection into the host cells. To identify such drugs, we first analyzed the recently published crystal structure of S-protein-hACE2 complex and identified essential residues of both S-protein and hACE2 for this interaction. We used this knowledge to virtually dock a drug library containing 4115 drug molecules against S-protein for repurposing drugs that could inhibit binding of S-protein to hACE2. We identified several potential inhibitors based on their docking scores, pharmacological effects and ability to block residues of S protein required for interaction with hACE2. The top inhibitors included drugs used for the treatment of hepatitis C (velpatasvir, pibrentasvir) as well as several vitamin D derivatives. Several molecules obtained from our screen already have good experimental support in published literature. Thus, we believe that our results will facilitate the discovery of an effective drug against COVID-19. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Adarsh Singh
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India
| | - Riddhiman Dhar
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India
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42
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Chen J, Gao K, Wang R, Wei GW. Revealing the threat of emerging SARS-CoV-2 mutations to antibody therapies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.04.12.439473. [PMID: 33880470 PMCID: PMC8057235 DOI: 10.1101/2021.04.12.439473] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
The ongoing massive vaccination and the development of effective intervention offer the long-awaited hope to end the global rage of the COVID-19 pandemic. However, the rapidly growing SARS-CoV-2 variants might compromise existing vaccines and monoclonal antibody (mAb) therapies. Although there are valuable experimental studies about the potential threats from emerging variants, the results are limited to a handful of mutations and Eli Lilly and Regeneron mAbs. The potential threats from frequently occurring mutations on the SARS-CoV-2 spike (S) protein receptor-binding domain (RBD) to many mAbs in clinical trials are largely unknown. We fill the gap by developing a topology-based deep learning strategy that is validated with tens of thousands of experimental data points. We analyze 261,348 genome isolates from patients to identify 514 non-degenerate RBD mutations and investigate their impacts on 16 mAbs in clinical trials. Our findings, which are highly consistent with existing experimental results about variants from the UK, South Africa, Brazil, US-California, and Mexico shed light on potential threats of 95 high-frequency mutations to mAbs not only from Eli Lilly and Regeneron but also from Celltrion and Rockefeller University that are in clinical trials. We unveil, for the first time, that high-frequency mutations R346K/S, N439K, G446V, L455F, V483F/A, E484Q/V/A/G/D, F486L, F490L/V/S, Q493L, and S494P/L might compromise some of mAbs in clinical trials. Our study gives rise to a general perspective about how mutations will affect current vaccines.
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43
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Li JY, Wang Q, Liao CH, Qiu Y, Ge XY. The 442th amino acid residue of the spike protein is critical for the adaptation to bat hosts for SARS-related coronaviruses. Virus Res 2021; 295:198307. [PMID: 33476695 PMCID: PMC7813513 DOI: 10.1016/j.virusres.2021.198307] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 01/12/2021] [Accepted: 01/13/2021] [Indexed: 11/24/2022]
Abstract
Bats carry diverse severe acute respiratory syndrome-related coronaviruses (SARSr-CoVs). The suspected interspecies transmission of SARSr-CoVs from bats to humans has caused two severe CoV pandemics, the SARS pandemic in 2003 and the recent COVID-19 pandemic. The receptor utilization of SARSr-CoV plays the key role in determining the host range and the interspecies transmission ability of the virus. Both SARS-CoV and SARS-CoV-2 use angiotensin-converting enzyme 2 (ACE2) as their receptor. Previous studies showed that WIV1 strain, the first living coronavirus isolated from bat using ACE2 as its receptor, is the prototype of SARS-CoV. The receptor-binding domain (RBD) in the spike protein (S) of SARS-CoV and WIV1 is responsible for ACE2 binding and medicates the viral entry. Comparing to SARS-CoV, WIV1 has three distinct amino acid residues (442, 472, and 487) in its RBD. This study aimed at exploring whether these three residues could alter the receptor utilization of SARSr-CoVs. We replaced the three residues in SARS-CoV (BJ01 strain) S with their counterparts in WIV1 S, and then evaluated the change of their utilization of bat, civet, and human ACE2s using a lentivirus-based pseudovirus infection system. To further validate the S-ACE2 interactions, the binding affinity between the RBDs of these S proteins and the three ACE2s were verified by flow cytometry. The results showed that the single amino acid substitution Y442S in the RBD of BJ01 S enhanced its utilization of bat ACE2 and its binding affinity to bat ACE2. On the contrary, the reverse substitution in WIV1 S (S442Y) significantly attenuated the pseudovirus utilization of bat, civet and human ACE2s for cell entry, and reduced its binding affinity with the three ACE2s. These results suggest that the S442 is critical for WIV1 adapting to bats as its natural hosts. These findings will enhance our understanding of host adaptations and cross-species infections of coronaviruses, contributing to the prediction and prevention of coronavirus epidemics.
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Affiliation(s)
- Jin-Yan Li
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, 27 Tianma Rd., Changsha, Hunan, 410012, China.
| | - Qiong Wang
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, 27 Tianma Rd., Changsha, Hunan, 410012, China.
| | - Ce-Heng Liao
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, 27 Tianma Rd., Changsha, Hunan, 410012, China.
| | - Ye Qiu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, 27 Tianma Rd., Changsha, Hunan, 410012, China.
| | - Xing-Yi Ge
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, 27 Tianma Rd., Changsha, Hunan, 410012, China.
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44
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Arif A, Ansari S, Ahsan H, Mahmood R, Khan FH. An overview of Covid-19 pandemic: immunology and pharmacology. J Immunoassay Immunochem 2021; 42:493-512. [PMID: 33788668 DOI: 10.1080/15321819.2021.1904414] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
In this review, we present an elaborate account of coronavirus in context to Covid-19 focusing on its origin, genome, life cycle, and immunology with a basic understanding of the disease and its cause. Further, the transmission, prevention and advances in therapeutics have also been discussed anticipating the possible outcomes in the near future. Moreover, the recently emerged unconventional approaches to this viral disease like drug repurposing, plasma therapy, nasal spray, and other preventive measures worldwide are studied for a long-term impact and relevance. Hence, this account on coronavirus and the ongoing pandemic serves a purpose of spreading awareness and to pass on relevant knowledge for a better chance to combat such unfortunate health crisis in future.
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Affiliation(s)
- Amin Arif
- Department of Biochemistry, Faculty of Life Sciences, Aligarh Muslim University, Aligarh India
| | - Sana Ansari
- Department of Biochemistry, Faculty of Life Sciences, Aligarh Muslim University, Aligarh India
| | - Haseeb Ahsan
- Faculty of Dentistry, Department of Biochemistry, Jamia Millia Islamia, New Delhi India
| | - Riaz Mahmood
- Department of Biochemistry, Faculty of Life Sciences, Aligarh Muslim University, Aligarh India
| | - Fahim Halim Khan
- Department of Biochemistry, Faculty of Life Sciences, Aligarh Muslim University, Aligarh India
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45
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Stalin A, Lin D, Senthamarai Kannan B, Feng Y, Wang Y, Zhao W, Ignacimuthu S, Wei DQ, Chen Y. An in-silico approach to identify the potential hot spots in SARS-CoV-2 spike RBD to block the interaction with ACE2 receptor. J Biomol Struct Dyn 2021; 40:7408-7423. [PMID: 33685364 DOI: 10.1080/07391102.2021.1897682] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
A novel acute viral pneumonia induced by SARS-CoV-2 exploded at the end of 2019, causing a severe medical and economic crisis. For developing specific pharmacotherapy against SARS-CoV-2, an in silico virtual screening was developed for the available in-house molecules. The conserved domain analysis was performed to identify the highly conserved and exposed amino acid regions in the SARS-CoV-2-S RBD sites. The Protein-Protein interaction analyses demonstrated the higher affinity between the SARS-CoV-2-S and ACE2 due to varieties of significant interactions between them. The computational alanine scanning mutation study has recognized the highly stabilized amino acids in the SARS-CoV-2-S RBD/ACE2 complex. The cumulative sequence investigations have inferred that Lys417, Phe486, Asn487, Tyr489, and Gln493 are perhaps the iconic target amino acids to develop a drug molecule or vaccine against SARS-CoV-2 infection. Most of the selected compounds include luteolin, zhebeirine, 3-dehydroverticine, embelin, andrographolide, ophiopogonin D, crocin-1, sprengerinin A, B, C, peimine, etc. were exhibited distinguish drug actions through the strong hydrogen bonding with the hot spots of the RBD. Besides, the 100 ns molecular dynamics simulation and free energy binding analysis showed the significant efficacy of luteolin to inhibit the infection of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Antony Stalin
- State Key Laboratory of Subtropical Silviculture, Department of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou, China
| | - Ding Lin
- State Key Laboratory of Subtropical Silviculture, Department of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou, China
| | | | - Yue Feng
- College of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yanjing Wang
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Wei Zhao
- State Key Laboratory of Subtropical Silviculture, Department of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou, China
| | | | - Dong-Qing Wei
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China.,Peng Cheng Laboratory, Shenzhen, Guangdong, P.R China
| | - Yuan Chen
- State Key Laboratory of Subtropical Silviculture, Department of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou, China
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46
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Faria NR, Mellan TA, Whittaker C, Claro IM, Candido DDS, Mishra S, Crispim MAE, Sales FC, Hawryluk I, McCrone JT, Hulswit RJG, Franco LAM, Ramundo MS, de Jesus JG, Andrade PS, Coletti TM, Ferreira GM, Silva CAM, Manuli ER, Pereira RHM, Peixoto PS, Kraemer MU, Gaburo N, Camilo CDC, Hoeltgebaum H, Souza WM, Rocha EC, de Souza LM, de Pinho MC, Araujo LJT, Malta FSV, de Lima AB, Silva JDP, Zauli DAG, de S. Ferreira AC, Schnekenberg RP, Laydon DJ, Walker PGT, Schlüter HM, dos Santos ALP, Vidal MS, Del Caro VS, Filho RMF, dos Santos HM, Aguiar RS, Modena JLP, Nelson B, Hay JA, Monod M, Miscouridou X, Coupland H, Sonabend R, Vollmer M, Gandy A, Suchard MA, Bowden TA, Pond SLK, Wu CH, Ratmann O, Ferguson NM, Dye C, Loman NJ, Lemey P, Rambaut A, Fraiji NA, Carvalho MDPSS, Pybus OG, Flaxman S, Bhatt S, Sabino EC. Genomics and epidemiology of a novel SARS-CoV-2 lineage in Manaus, Brazil. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.02.26.21252554. [PMID: 33688664 PMCID: PMC7941639 DOI: 10.1101/2021.02.26.21252554] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Cases of SARS-CoV-2 infection in Manaus, Brazil, resurged in late 2020, despite high levels of previous infection there. Through genome sequencing of viruses sampled in Manaus between November 2020 and January 2021, we identified the emergence and circulation of a novel SARS-CoV-2 variant of concern, lineage P.1, that acquired 17 mutations, including a trio in the spike protein (K417T, E484K and N501Y) associated with increased binding to the human ACE2 receptor. Molecular clock analysis shows that P.1 emergence occurred around early November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.4-2.2 times more transmissible and 25-61% more likely to evade protective immunity elicited by previous infection with non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.
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Affiliation(s)
- Nuno R. Faria
- Department of Infectious Disease Epidemiology, Imperial College London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Department of Zoology, University of Oxford, UK
| | - Thomas A. Mellan
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Charles Whittaker
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Ingra M. Claro
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Darlan da S. Candido
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Department of Zoology, University of Oxford, UK
| | - Swapnil Mishra
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Myuki A. E. Crispim
- Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
- Diretoria de Ensino e Pesquisa, Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
| | - Flavia C. Sales
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Iwona Hawryluk
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - John T. McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Ruben J. G. Hulswit
- Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Lucas A. M. Franco
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Mariana S. Ramundo
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Jaqueline G. de Jesus
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Pamela S. Andrade
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Thais M. Coletti
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Giulia M. Ferreira
- Laboratório de Virologia, Instituto de Ciências Biomédicas, Universidade Federal de Uberlândia, Uberlândia, Brazil
| | - Camila A. M. Silva
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Erika R. Manuli
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | | | - Pedro S. Peixoto
- Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil
| | | | | | | | | | - William M. Souza
- Virology Research Centre, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Esmenia C. Rocha
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Leandro M. de Souza
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Mariana C. de Pinho
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Leonardo J. T Araujo
- Laboratory of Quantitative Pathology, Center of Pathology, Adolfo Lutz Institute, São Paulo, Brazil
| | | | | | | | | | | | | | - Daniel J. Laydon
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | | | | | | | | | | | | | | | - Renato S. Aguiar
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - José L. P. Modena
- Laboratory of Emerging Viruses, Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas (UNICAMP), São Paulo, Brazil
| | - Bruce Nelson
- Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil
| | - James A. Hay
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA
- Center for Communicable Disease Dynamics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Melodie Monod
- Department of Mathematics, Imperial College London, UK
| | | | - Helen Coupland
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Raphael Sonabend
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Michaela Vollmer
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Axel Gandy
- Department of Mathematics, Imperial College London, UK
| | - Marc A. Suchard
- Department of Biomathematics, Department of Biostatistics and Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Thomas A. Bowden
- Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Sergei L. K. Pond
- Institute for Genomics and Evolutionary Medicine, Temple University, USA
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK
| | | | - Neil M. Ferguson
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | | | - Nick J. Loman
- Institute for Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Nelson A. Fraiji
- Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
- Diretoria Clínica, Fundação Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil
| | - Maria do P. S. S. Carvalho
- Fundação Hospitalar de Hematologia e Hemoterapia, Manaus, Brazil
- Diretoria da Presidência, Fundação Hospitalar de Hematologia e Hemoterapia do Amazonas, Manaus, Brazil
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, UK
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK
| | - Seth Flaxman
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - Samir Bhatt
- Department of Infectious Disease Epidemiology, Imperial College London, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Denmark
| | - Ester C. Sabino
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
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Wang R, Chen J, Gao K, Hozumi Y, Yin C, Wei GW. Analysis of SARS-CoV-2 mutations in the United States suggests presence of four substrains and novel variants. Commun Biol 2021; 4:228. [PMID: 33589648 PMCID: PMC7884689 DOI: 10.1038/s42003-021-01754-6] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 11/13/2020] [Indexed: 02/07/2023] Open
Abstract
SARS-CoV-2 has been mutating since it was first sequenced in early January 2020. Here, we analyze 45,494 complete SARS-CoV-2 geneome sequences in the world to understand their mutations. Among them, 12,754 sequences are from the United States. Our analysis suggests the presence of four substrains and eleven top mutations in the United States. These eleven top mutations belong to 3 disconnected groups. The first and second groups consisting of 5 and 8 concurrent mutations are prevailing, while the other group with three concurrent mutations gradually fades out. Moreover, we reveal that female immune systems are more active than those of males in responding to SARS-CoV-2 infections. One of the top mutations, 27964C > T-(S24L) on ORF8, has an unusually strong gender dependence. Based on the analysis of all mutations on the spike protein, we uncover that two of four SASR-CoV-2 substrains in the United States become potentially more infectious.
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Affiliation(s)
- Rui Wang
- Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA
| | - Jiahui Chen
- Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA
| | - Kaifu Gao
- Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA
| | - Yuta Hozumi
- Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA
| | - Changchuan Yin
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL, 60607, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA.
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA.
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA.
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48
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Animal Coronaviruses and SARS-COV-2 in Animals, What Do We Actually Know? Life (Basel) 2021; 11:life11020123. [PMID: 33562645 PMCID: PMC7914637 DOI: 10.3390/life11020123] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/17/2022] Open
Abstract
Coronaviruses (CoVs) are a well-known group of viruses in veterinary medicine. We currently know four genera of Coronavirus, alfa, beta, gamma, and delta. Wild, farmed, and pet animals are infected with CoVs belonging to all four genera. Seven human respiratory coronaviruses have still been identified, four of which cause upper-respiratory-tract diseases, specifically, the common cold, and the last three that have emerged cause severe acute respiratory syndromes, SARS-CoV-1, MERS-CoV, and SARS-CoV-2. In this review we briefly describe animal coronaviruses and what we actually know about SARS-CoV-2 infection in farm and domestic animals.
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Karki N, Verma N, Trozzi F, Tao P, Kraka E, Zoltowski B. Predicting Potential SARS-COV-2 Drugs-In Depth Drug Database Screening Using Deep Neural Network Framework SSnet, Classical Virtual Screening and Docking. Int J Mol Sci 2021; 22:1573. [PMID: 33557253 PMCID: PMC7915186 DOI: 10.3390/ijms22041573] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 01/24/2021] [Accepted: 01/29/2021] [Indexed: 12/14/2022] Open
Abstract
Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted in the identification of potential pharmaceutical treatments for CoVID-19 using existing drugs, as well as the discovery of multiple vaccines. During an urgent crisis, rapidly identifying potential new treatments requires global and cross-discipline cooperation, together with an enhanced open-access research model to distribute new ideas and leads. Herein, we introduce an application of a deep neural network based drug screening method, validating it using a docking algorithm on approved drugs for drug repurposing efforts, and extending the screen to a large library of 750,000 compounds for de novo drug discovery effort. The results of large library screens are incorporated into an open-access web interface to allow researchers from diverse fields to target molecules of interest. Our combined approach allows for both the identification of existing drugs that may be able to be repurposed and de novo design of ACE2-regulatory compounds. Through these efforts we demonstrate the utility of a new machine learning algorithm for drug discovery, SSnet, that can function as a tool to triage large molecular libraries to identify classes of molecules with possible efficacy.
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Affiliation(s)
| | | | | | | | | | - Brian Zoltowski
- Department of Chemistry, Southern Methodist University, Dallas, TX 75205, USA; (N.K.); (N.V.); (F.T.); (P.T.); (E.K.)
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50
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Zarandi PK, Zinatizadeh MR, Zinatizadeh M, Yousefi MH, Rezaei N. SARS-CoV-2: From the pathogenesis to potential anti-viral treatments. Biomed Pharmacother 2021; 137:111352. [PMID: 33550050 PMCID: PMC7969672 DOI: 10.1016/j.biopha.2021.111352] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 01/26/2021] [Accepted: 01/29/2021] [Indexed: 12/12/2022] Open
Abstract
Introduction The world is witnessing the spread of one of the members of Coronaviruses (CoVs) family, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the 21st century. Considering the short time spent after its prevalence, limited information is known about the effect of the virus mechanism on different organs of the body; meanwhile the lack of specific treatment and vaccine for this virus has exposed millions of people to a big challenge. Areas covered The review article aims to describe the general and particular characteristics of CoVs, their classification, genome structure, host cell infection, cytokine storm, anti-viral treatments, and inhibition of COVID-19-related ER-mitochondrial stress. In addition, it refers to drugs such as Chloroquine/Hydroxychloroquine, Lopinavir/Ritonavir, darunavir, ribavirin, remdesivir, and favipiravir, which have undergone clinical trials for coronavirus disease 2019 (COVID-19) treatment. This analysis was derived from an extensive scientific literature search including Pubmed, ScienceDirect, and Google Scholar performed. Expert opinion The effectiveness rate and complications of these drugs can reveal new insights into the potential therapeutic goals for the disease. Moreover, lifestyle change can effectively prevent SARS-CoV-2 infection.
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Affiliation(s)
- Peyman Kheirandish Zarandi
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran; Cancer Biology Signaling Pathway Interest Group (CBSPIG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Mohammad Reza Zinatizadeh
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran; Cancer Biology Signaling Pathway Interest Group (CBSPIG), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
| | - Maryam Zinatizadeh
- Department of Anesthesiology, Semnan Branch, Islamic Azad University, Shahrood, Iran
| | - Mohammad Hadi Yousefi
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran; Department of Mycobacteriology and Pulmonary Research, Microbiology Research Center (MRC), Pasteur Institute of Iran, Tehran, Iran
| | - Nima Rezaei
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran; Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
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