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Broni E, Miller WA. Computational Analysis Predicts Correlations among Amino Acids in SARS-CoV-2 Proteomes. Biomedicines 2023; 11:512. [PMID: 36831052 PMCID: PMC9953644 DOI: 10.3390/biomedicines11020512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/03/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious global challenge requiring urgent and permanent therapeutic solutions. These solutions can only be engineered if the patterns and rate of mutations of the virus can be elucidated. Predicting mutations and the structure of proteins based on these mutations have become necessary for early drug and vaccine design purposes in anticipation of future viral mutations. The amino acid composition (AAC) of proteomes and individual viral proteins provide avenues for exploitation since AACs have been previously used to predict structure, shape and evolutionary rates. Herein, the frequency of amino acid residues found in 1637 complete proteomes belonging to 11 SARS-CoV-2 variants/lineages were analyzed. Leucine is the most abundant amino acid residue in the SARS-CoV-2 with an average AAC of 9.658% while tryptophan had the least abundance of 1.11%. The AAC and ranking of lysine and glycine varied in the proteome. For some variants, glycine had higher frequency and AAC than lysine and vice versa in other variants. Tryptophan was also observed to be the most intolerant to mutation in the various proteomes for the variants used. A correlogram revealed a very strong correlation of 0.999992 between B.1.525 (Eta) and B.1.526 (Iota) variants. Furthermore, isoleucine and threonine were observed to have a very strong negative correlation of -0.912, while cysteine and isoleucine had a very strong positive correlation of 0.835 at p < 0.001. Shapiro-Wilk normality test revealed that AAC values for all the amino acid residues except methionine showed no evidence of non-normality at p < 0.05. Thus, AACs of SARS-CoV-2 variants can be predicted using probability and z-scores. AACs may be beneficial in classifying viral strains, predicting viral disease types, members of protein families, protein interactions and for diagnostic purposes. They may also be used as a feature along with other crucial factors in machine-learning based algorithms to predict viral mutations. These mutation-predicting algorithms may help in developing effective therapeutics and vaccines for SARS-CoV-2.
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Affiliation(s)
- Emmanuel Broni
- Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA
| | - Whelton A. Miller
- Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA
- Department of Molecular Pharmacology & Neuroscience, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA
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Zeller MA, Chang J, Vincent AL, Gauger PC, Anderson TK. Spatial and Temporal Coevolution of N2 Neuraminidase and H1 and H3 Hemagglutinin Genes of Influenza A Virus in United States Swine. Virus Evol 2021; 7:veab090. [PMID: 35223081 PMCID: PMC8864744 DOI: 10.1093/ve/veab090] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 09/14/2021] [Accepted: 10/07/2021] [Indexed: 11/12/2022] Open
Abstract
Abstract
The neuraminidase (NA) and hemagglutinin (HA) are essential surface glycoproteins of influenza A virus (IAV). In this study, the evolution of subtype N2 NA paired with H1 and H3 subtype HA in swine was evaluated to understand if genetic diversity of HA and NA were linked. Using time-scaled Bayesian phylodynamic analyses, the relationships of paired swine N2 with H1 or H3 from 2009 to 2018 were evaluated. These data demonstrated increased relative genetic diversity within the major N2 clades circulating in swine in the United States (N2.1998 between 2014-2017 and N2.2002 between 2010-2016). Preferential pairing was observed among specific NA and HA genetic clades. Gene reassortment between cocirculating influenza A strains resulted in novel pairings that persisted. The changes of genetic diversity in the NA gene were quantified using Bayesian phylodynamic analyses and increases in diversity were observed subsequent to novel NA-HA reassortment events. The rate of evolution among NA-N2 clades and HA-H1 and HA-H3 clades were similar. Bayesian phylodynamic analyses demonstrated strong spatial patterns in N2 genetic diversity, but frequent interstate movement of rare N2 clades provided opportunity for reassortment and emergence of new N2-HA pairings. The frequent regional movement of pigs and their influenza viruses is an explanation for the documented patterns of reassortment and subsequent changes in gene diversity. The reassortment and evolution of NA and linked HA evolution may result in antigenic drift of both major surface glycoproteins, reducing vaccine efficacy, with subsequent impact on animal health.
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Affiliation(s)
- Michael A Zeller
- Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA
| | - Jennifer Chang
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA 50010, USA
| | - Amy L Vincent
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA 50010, USA
| | - Phillip C Gauger
- Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA
| | - Tavis K Anderson
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA 50010, USA
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Identifying Potentially Beneficial Genetic Mutations Associated with Monophyletic Selective Sweep and a Proof-of-Concept Study with Viral Genetic Data. mSystems 2021; 6:6/1/e01151-20. [PMID: 33622855 PMCID: PMC8573955 DOI: 10.1128/msystems.01151-20] [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] [Indexed: 11/20/2022] Open
Abstract
Genetic mutations play a central role in evolution. For a significantly beneficial mutation, a one-time mutation event suffices for the species to prosper and predominate through the process called “monophyletic selective sweep.” However, existing methods that rely on counting the number of mutation events to detect selection are unable to find such a mutation in selective sweep. We here introduce a method to detect mutations at the single amino acid/nucleotide level that could be responsible for monophyletic selective sweep evolution. The method identifies a genetic signature associated with selective sweep using the population genetic test statistic Tajima’s D. We applied the algorithm to ebolavirus, influenza A virus, and severe acute respiratory syndrome coronavirus 2 to identify known biologically significant mutations and unrecognized mutations associated with potential selective sweep. The method can detect beneficial mutations, possibly leading to discovery of previously unknown biological functions and mechanisms related to those mutations. IMPORTANCE In biology, research on evolution is important to understand the significance of genetic mutation. When there is a significantly beneficial mutation, a population of species with the mutation prospers and predominates, in a process called “selective sweep.” However, there are few methods that can find such a mutation causing selective sweep from genetic data. We here introduce a novel method to detect such mutations. Applying the method to the genomes of ebolavirus, influenza viruses, and the novel coronavirus, we detected known biologically significant mutations and identified mutations the importance of which is previously unrecognized. The method can deepen our understanding of molecular and evolutionary biology.
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Trigueiro-Louro J, Correia V, Figueiredo-Nunes I, Gíria M, Rebelo-de-Andrade H. Unlocking COVID therapeutic targets: A structure-based rationale against SARS-CoV-2, SARS-CoV and MERS-CoV Spike. Comput Struct Biotechnol J 2020; 18:2117-2131. [PMID: 32913581 PMCID: PMC7452956 DOI: 10.1016/j.csbj.2020.07.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 07/20/2020] [Accepted: 07/22/2020] [Indexed: 12/11/2022] Open
Abstract
There are no approved target therapeutics against SARS-CoV-2 or other beta-CoVs. The beta-CoV Spike protein is a promising target considering the critical role in viral infection and pathogenesis and its surface exposed features. We performed a structure-based strategy targeting highly conserved druggable regions resulting from a comprehensive large-scale sequence analysis and structural characterization of Spike domains across SARSr- and MERSr-CoVs. We have disclosed 28 main consensus druggable pockets within the Spike. The RBD and SD1 (S1 subunit); and the CR, HR1 and CH (S2 subunit) represent the most promising conserved druggable regions. Additionally, we have identified 181 new potential hot spot residues for the hSARSr-CoVs and 72 new hot spot residues for the SARSr- and MERSr-CoVs, which have not been described before in the literature. These sites/residues exhibit advantageous structural features for targeted molecular and pharmacological modulation. This study establishes the Spike as a promising anti-CoV target using an approach with a potential higher resilience to resistance development and directed to a broad spectrum of Beta-CoVs, including the new SARS-CoV-2 responsible for COVID-19. This research also provides a structure-based rationale for the design and discovery of chemical inhibitors, antibodies or other therapeutic modalities successfully targeting the Beta-CoV Spike protein.
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Key Words
- ACE2, angiotensin-converting enzyme2
- Bat-SL-CoVs, bat SARS-like coronavirus
- Beta-CoVs, betacoronavirus
- Betacoronavirus
- CC, conserved cluster
- CD, connector domain
- CDP, consensus druggable pocket
- CDR, consensus druggable residue
- CH, central helix
- CP, cytoplasmic domain
- CR, connecting region
- CS, conservation score
- CoVs, coronavirus
- Coronavirus disease
- DGSS, DoGSiteScorer
- DPP4, dipeptidyl peptidase-4
- Druggability prediction
- FP, fusion peptide
- HR1, heptad repeat 1
- HR2, heptad repeat 2
- MERS-CoVs, middle east respiratory syndrome coronavirus
- MERSr-CoVs, middle east respiratory syndrome-related coronavirus
- MSA, multiple sequence alignment
- NTD, N-terminal domain
- Novel antiviral targets
- PDB, Protein Data Bank
- PDS, PockDrug-Server
- RBD, Receptor-Binding Domain
- S, Spike
- SARS-CoV-2
- SARS-CoV-2, severe acute respiratory syndrome coronavirus 2
- SARS-CoVs, severe acute respiratory syndrome coronavirus
- SARSr-CoVs, severe acute respiratory syndrome-related coronavirus
- SD1, subdomain 1
- SD2, subdomain 2
- SF, SiteFinder from MOE
- SP, small pocket
- Sequence conservation
- Spike protein
- Sv, shorter variant
- T-RHS, top-ranked hot spots
- TMPRSS2, transmembrane protease serine 2
- aa, amino acid
- hSARSr-CoVs, human Severe acute respiratory syndrome-related coronavirus
- nts, nucleotides
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Affiliation(s)
- João Trigueiro-Louro
- Antiviral Resistance Lab, Research & Development Unit, Infectious Diseases Department, Instituto Nacional de Saúde Doutor Ricardo Jorge, IP, Av. Padre Cruz, 1649-016 Lisbon, Portugal
- Host-Pathogen Interaction Unit, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Av. Professor Gama Pinto, 1649-003 Lisbon, Portugal
| | - Vanessa Correia
- Antiviral Resistance Lab, Research & Development Unit, Infectious Diseases Department, Instituto Nacional de Saúde Doutor Ricardo Jorge, IP, Av. Padre Cruz, 1649-016 Lisbon, Portugal
| | - Inês Figueiredo-Nunes
- Host-Pathogen Interaction Unit, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Av. Professor Gama Pinto, 1649-003 Lisbon, Portugal
| | - Marta Gíria
- Host-Pathogen Interaction Unit, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Av. Professor Gama Pinto, 1649-003 Lisbon, Portugal
| | - Helena Rebelo-de-Andrade
- Antiviral Resistance Lab, Research & Development Unit, Infectious Diseases Department, Instituto Nacional de Saúde Doutor Ricardo Jorge, IP, Av. Padre Cruz, 1649-016 Lisbon, Portugal
- Host-Pathogen Interaction Unit, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Av. Professor Gama Pinto, 1649-003 Lisbon, Portugal
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Paules CI, McDermott AB, Fauci AS. Immunity to Influenza: Catching a Moving Target To Improve Vaccine Design. THE JOURNAL OF IMMUNOLOGY 2019; 202:327-331. [PMID: 30617113 DOI: 10.4049/jimmunol.1890025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Catharine I Paules
- Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033
| | - Adrian B McDermott
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892; and
| | - Anthony S Fauci
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892
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