Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

Identification of Generalized Peptide Regions for Designing Vaccine Effective for All Significant Mutated Strains of SARS-CoV-2

Author(s): Subhamoy Biswas, Smarajit Manna*, Tathagata Dey, Shreyans Chatterjee and Sumanta Dey

Volume 25, Issue 3, 2022

Published on: 01 June, 2021

Page: [414 - 428] Pages: 15

DOI: 10.2174/1386207324666210601122820

Price: $65

Abstract

Background: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection has become a worldwide pandemic and created an utmost crisis across the globe. To mitigate the crisis, the design of vaccine is the crucial solution. The frequent mutation of the virus demands generalized vaccine candidates, which would be effective for all mutated strains at present and for the strains that would evolve due to further new mutations in the virus.

Objective: The objective of this study is to identify more frequently occurring mutated variants of SARS-CoV-2 and to suggest peptide vaccine candidates effective against the viral strains considered.

Methods: In this study, we have identified all currently prevailing mutated strains of SARS-CoV-2 through 2D Polar plot and Quotient Radius (qR) characterization descriptor. Then, by considering the top eight mutation strains, which are significant due to their frequency of occurrence, peptide regions suitable for vaccine design have been identified with the help of a mathematical model, 2D Polygon Representation, followed by the evaluation of epitope potential, ensuring that there is no case of any autoimmune threat. Lastly, in order to verify whether this entire approach is applicable for vaccine design against any other virus in general, we have made a comparative study between the peptide vaccine candidates prescribed for the Zika virus using the current approach and a list of potential vaccine candidates for the same already established in the past.

Results: We have finally suggested three generalized peptide regions which would be suitable as sustainable peptide vaccine candidates against SARS-CoV-2 irrespective of its currently prevailing strains as well any other variant of the same that may appear in the future. We also observed that during the comparative study using the case of E protein of Zika virus, the peptide regions suggested using the new approach that matches with the already established results.

Conclusion: The study, therefore, illustrates an approach that would help in developing peptide vaccine against SARS-CoV-2 by suggesting those peptide regions which can be targeted irrespective of any mutated form of this virus. The consistency with which this entire approach was also able to figure out similar vaccine candidates for Zika virus with utmost accuracy proves that this protocol can be extended for peptide vaccine design against any other viruses in the future.

Keywords: SARS-CoV-2 mutation, graphical representations, 2D Polar Plot, Quotient Radius  , 2D Polygon Representation Model, epitope potential, autoimmune threat, peptide vaccine

Graphical Abstract

[1]
World Health Organization (WHO) Available from: https://www.who.int/
[2]
WHO Coronavirus disease (COVID-19) Dashboard. Available from: https://covid19.who.int/ [Accessed on: December 27, 2020]
[3]
Zhu, Z.; Lian, X.; Su, X.; Wu, W.; Marraro, G.A.; Zeng, Y. From SARS and MERS to COVID-19: A brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses. Respir. Res., 2020, 21(1), 224.
[http://dx.doi.org/10.1186/s12931-020-01479-w] [PMID: 32854739]
[4]
Konda, M.; Dodda, B.; Konala, V.M.; Naramala, S.; Adapa, S. Potential zoonotic origins of SARS-CoV-2 and insights for preventing future pandemics through one health approach. Cureus, 2020, 12(6)e8932
[http://dx.doi.org/10.7759/cureus.8932] [PMID: 32760632]
[5]
Ji, W.; Wang, W.; Zhao, X.; Zai, J.; Li, X. Cross-species transmission of the newly identified coronavirus 2019-nCoV. J. Med. Virol., 2020, 92(4), 433-440.
[http://dx.doi.org/10.1002/jmv.25682] [PMID: 31967321]
[6]
Lam, T.T.Y.; Jia, N.; Zhang, Y.W.; Shum, M.H.H.; Jiang, J.F.; Zhu, H.C.; Tong, Y.G.; Shi, Y.X.; Ni, X.B.; Liao, Y.S.; Li, W.J.; Jiang, B.G.; Wei, W.; Yuan, T.T.; Zheng, K.; Cui, X.M.; Li, J.; Pei, G.Q.; Qiang, X.; Cheung, W.Y.; Li, L.F.; Sun, F.F.; Qin, S.; Huang, J.C.; Leung, G.M.; Holmes, E.C.; Hu, Y.L.; Guan, Y.; Cao, W.C. Identifying SARS-CoV-2-related coronaviruses in Malayan pangolins. Nature, 2020, 583(7815), 282-285.
[http://dx.doi.org/10.1038/s41586-020-2169-0] [PMID: 32218527]
[7]
Ge, X.Y.; Li, J.L.; Yang, X.L.; Chmura, A.A.; Zhu, G.; Epstein, J.H.; Mazet, J.K.; Hu, B.; Zhang, W.; Peng, C.; Zhang, Y.J.; Luo, C.M.; Tan, B.; Wang, N.; Zhu, Y.; Crameri, G.; Zhang, S.Y.; Wang, L.F.; Daszak, P.; Shi, Z.L. Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor. Nature, 2013, 503(7477), 535-538.
[http://dx.doi.org/10.1038/nature12711] [PMID: 24172901]
[8]
Lau, S.K.; Woo, P.C.; Li, K.S.; Huang, Y.; Tsoi, H.W.; Wong, B.H.; Wong, S.S.; Leung, S.Y.; Chan, K.H.; Yuen, K.Y. Severe acute respiratory syndrome coronavirus-like virus in Chinese horseshoe bats. Proc. Natl. Acad. Sci. USA, 2005, 102(39), 14040-14045.
[http://dx.doi.org/10.1073/pnas.0506735102] [PMID: 16169905]
[9]
Mackenzie, J.S.; Smith, D.W. COVID-19: A novel zoonotic disease caused by a coronavirus from China: What we know and what we don’t. Microbiol. Aust., 2020, 41(1)MA20013
[http://dx.doi.org/10.1071/MA20013] [PMID: 32226946]
[10]
Aguirre, A.A.; Catherina, R.; Frye, H.; Shelley, L. Illicit wildlife trade, wet markets, and COVID‐19: Preventing future pandemics. World Med. Health Policy, 2020, 12(3), 256-265.
[http://dx.doi.org/10.1002/wmh3.348] [PMID: 32837772]
[11]
Woo, P.C.; Huang, Y.; Lau, S.K.; Yuen, K.Y. Coronavirus genomics and bioinformatics analysis. Viruses, 2010, 2(8), 1804-1820.
[http://dx.doi.org/10.3390/v2081803] [PMID: 21994708]
[12]
Khailany, R.A.; Safdar, M.; Ozaslan, M. Genomic characterization of a novel SARS-CoV-2. Gene Rep., 2020, 19100682
[http://dx.doi.org/10.1016/j.genrep.2020.100682] [PMID: 32300673]
[13]
Naqvi, A.A.T.; Fatima, K.; Mohammad, T.; Fatima, U.; Singh, I.K.; Singh, A.; Atif, S.M.; Hariprasad, G.; Hasan, G.M.; Hassan, M.I. Insights into SARS-CoV-2 genome, structure, evolution, pathogenesis and therapies: Structural genomics approach. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 2020. 165878
[14]
Ziebuhr, J.; Snijder, E.J.; Gorbalenya, A.E. Virus-encoded proteinases and proteolytic processing in the Nidovirales. J. Gen. Virol., 2000, 81(Pt 4), 853-879.
[http://dx.doi.org/10.1099/0022-1317-81-4-853] [PMID: 10725411]
[15]
Hoffmann, M.; Kleine-Weber, H.; Schroeder, S.; Krüger, N.; Herrler, T.; Erichsen, S.; Schiergens, T.S.; Herrler, G.; Wu, N.H.; Nitsche, A.; Müller, M.A.; Drosten, C.; Pöhlmann, S. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell, 2020, 181(2), 271-280.e8.
[http://dx.doi.org/10.1016/j.cell.2020.02.052] [PMID: 32142651]
[16]
Wang, Q.; Zhang, Y.; Wu, L.; Niu, S.; Song, C.; Zhang, Z.; Lu, G.; Qiao, C.; Hu, Y.; Yuen, K.Y.; Wang, Q.; Zhou, H.; Yan, J.; Qi, J. Structural and functional basis of SARS-CoV-2 entry by using human ACE2. Cell, 2020, 181(4), 894-904.e9.
[http://dx.doi.org/10.1016/j.cell.2020.03.045] [PMID: 32275855]
[17]
Siddiqui, A.J.; Jahan, S.; Ashraf, S.A.; Alreshidi, M.; Ashraf, M.S.; Patel, M.; Snoussi, M.; Singh, R.; Adnan, M. Current status and strategic possibilities on potential use of combinational drug therapy against COVID-19 caused by SARS-CoV-2. J. Biomol. Struct. Dyn., 2020, 1-14.
[http://dx.doi.org/10.1080/07391102.2020.1802345] [PMID: 32752944]
[18]
Gautret, P.; Lagier, J-C.; Parola, P.; Hoang, V.T.; Meddeb, L.; Mailhe, M.; Doudier, B.; Courjon, J.; Giordanengo, V.; Vieira, V.E.; Tissot Dupont, H.; Honoré, S.; Colson, P.; Chabrière, E.; La Scola, B.; Rolain, J-M.; Brouqui, P.; Raoult, D. Hydroxychloroquine and azithromycin as a treatment of COVID-19: Results of an open-label non-randomized clinical trial. Int. J. Antimicrob. Agents, 2020, 56(1)105949
[http://dx.doi.org/10.1016/j.ijantimicag.2020.105949] [PMID: 32205204]
[19]
Liu, J.; Cao, R.; Xu, M.; Wang, X.; Zhang, H.; Hu, H.; Li, Y.; Hu, Z.; Zhong, W.; Wang, M. Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro. Cell Discov., 2020, 6, 16.
[http://dx.doi.org/10.1038/s41421-020-0156-0]
[20]
Andreani, J.; Le Bideau, M.; Duflot, I.; Jardot, P.; Rolland, C.; Boxberger, M.; Wurtz, N.; Rolain, J.M.; Colson, P.; La Scola, B.; Raoult, D. in vitro testing of combined hydroxychloroquine and azithromycin on SARS-CoV-2 shows synergistic effect. Microb. Pathog., 2020, 145104228
[http://dx.doi.org/10.1016/j.micpath.2020.104228] [PMID: 32344177]
[21]
Asai, A.; Konno, M.; Ozaki, M.; Otsuka, C.; Vecchione, A.; Arai, T.; Kitagawa, T.; Ofusa, K.; Yabumoto, M.; Hirotsu, T.; Taniguchi, M.; Eguchi, H.; Doki, Y.; Ishii, H. COVID-19 drug discovery using intensive approaches. Int. J. Mol. Sci., 2020, 21(8), 2839.
[http://dx.doi.org/10.3390/ijms21082839] [PMID: 32325767]
[22]
Augustin, M.; Hallek, M.; Nitschmann, S. COVID-19 drug discovery using intensive approaches. Int. J. Mol. Sci., 2020, 21(8), 2839.
[23]
Hendaus, M.A. Remdesivir in the treatment of coronavirus disease 2019 (COVID-19): A simplified summary. J. Biomol. Struct. Dyn., 2020, 6, 1-6.
[24]
Caly, L.; Druce, J.D.; Catton, M.G.; Jans, D.A.; Wagstaff, K.M. The FDA-approved drug ivermectin inhibits the replication of SARS-CoV-2 in vitro. Antiviral Res., 2020, 178104787
[http://dx.doi.org/10.1016/j.antiviral.2020.104787] [PMID: 32251768]
[25]
Choudhary, R.; Sharma, A.K. Potential use of hydroxychloroquine, ivermectin and azithromycin drugs in fighting COVID-19: Trends, scope and relevance. New Microbes New Infect., 2020, 35100684
[26]
Coomes, E.A.; Haghbayan, H. Favipiravir, an antiviral for COVID-19? J. Antimicrob. Chemother., 2020, 75(7), 2013-2014.
[http://dx.doi.org/10.1093/jac/dkaa171] [PMID: 32417899]
[27]
Costanzo, M.; De Giglio, M.A.R.; Roviello, G.N. SARS-CoV-2: Recent reports on antiviral therapies based on lopinavir/ritonavir, darunavir/umifenovir, hydroxychloroquine, remdesivir, favipiravir and other drugs for the treatment of the new coronavirus. Curr. Med. Chem., 2020, 27(27), 4536-4541.
[http://dx.doi.org/10.2174/0929867327666200416131117] [PMID: 32297571]
[28]
Pshenichnaya, N.Y.; Bulgakova, V.A.; Lvov, N.I.; Poromov, A.A.; Selkova, E.P.; Grekova, A.I.; Shestakova, I.V.; Maleev, V.V.; Leneva, I.A. Clinical efficacy of umifenovir in influenza and ARVI (study ARBITR). Ter. Arkh., 2019, 91(3), 56-63.
[http://dx.doi.org/10.26442/00403660.2019.03.000127] [PMID: 31094461]
[29]
Siddiqui, A.J.; Danciu, C.; Ashraf, S.A.; Moin, A.; Singh, R.; Alreshidi, M.; Patel, M.; Jahan, S.; Kumar, S.; Alkhinjar, M.I.M.; Badraoui, R.; Snoussi, M.; Adnan, M. Plants-derived biomolecules as potent antiviral phytomedicines: New insights on ethnobotanical evidences against coronaviruses. Plants (Basel), 2020, 9(9), 1244.
[http://dx.doi.org/10.3390/plants9091244] [PMID: 32967179]
[30]
Yao, R-Y.; Zou, Y-F.; Chen, X-F. Traditional use, pharmacology, toxicology, and quality control of species in genus Bupleurum L. Chin. Herb. Med., 2013, 5(4), 245-255.
[http://dx.doi.org/10.1016/S1674-6384(13)60036-2] [PMID: 32288759]
[31]
Yang, F.; Dong, X.; Yin, X.; Wang, W.; You, L.; Ni, J. Radix bupleuri: A review of traditional uses, botany, phytochemistry, pharmacology, and toxicology. BioMed Res. Int., 2017, 20177597596
[http://dx.doi.org/10.1155/2017/7597596] [PMID: 28593176]
[32]
Chen, J.; Duan, M.; Zhao, Y.; Ling, F.; Xiao, K.; Li, Q.; Li, B.; Lu, C.; Qi, W.; Zeng, Z.; Liao, M.; Liu, Y.; Chen, W. Saikosaponin a inhibits influenza a virus replication and lung immunopathology. Oncotarget, 2015, 6(40), 42541-42556.
[http://dx.doi.org/10.18632/oncotarget.6448] [PMID: 26637810]
[33]
Ieven, M.; van den Berghe, D.A.; Vlietinck, A.J. Plant antiviral agents. IV. Influence of lycorine on growth pattern of three animal viruses. Planta Med., 1983, 49(2), 109-114.
[http://dx.doi.org/10.1055/s-2007-969826] [PMID: 6318251]
[34]
Liu, J.; Yang, Y.; Xu, Y.; Ma, C.; Qin, C.; Zhang, L. Lycorine reduces mortality of human enterovirus 71-infected mice by inhibiting virus replication. Virol. J., 2011, 8, 483.
[http://dx.doi.org/10.1186/1743-422X-8-483] [PMID: 22029605]
[35]
Wang, H.; Guo, T.; Yang, Y.; Yu, L.; Pan, X.; Li, Y. Lycorine derivative LY-55 inhibits EV71 and CVA16 replication through downregulating autophagy. Front. Cell. Infect. Microbiol., 2019, 9, 277.
[http://dx.doi.org/10.3389/fcimb.2019.00277] [PMID: 31448243]
[36]
Mukhtar, M.; Arshad, M.; Ahmad, M.; Pomerantz, R.J.; Wigdahl, B.; Parveen, Z. Antiviral potentials of medicinal plants. Virus Res., 2008, 131(2), 111-120.
[http://dx.doi.org/10.1016/j.virusres.2007.09.008] [PMID: 17981353]
[37]
Ganjhu, R.K.; Mudgal, P.P.; Maity, H.; Dowarha, D.; Devadiga, S.; Nag, S.; Arunkumar, G. Herbal plants and plant preparations as remedial approach for viral diseases. Virusdisease, 2015, 26(4), 225-236.
[http://dx.doi.org/10.1007/s13337-015-0276-6] [PMID: 26645032]
[38]
Efferth, T.; Romero, M.R.; Wolf, D.G.; Stamminger, T.; Marin, J.J.G.; Marschall, M. The antiviral activities of artemisinin and artesunate. Clin. Infect. Dis., 2008, 47(6), 804-811.
[http://dx.doi.org/10.1086/591195] [PMID: 18699744]
[39]
Lin, L-T.; Hsu, W-C.; Lin, C-C. Antiviral natural products and herbal medicines. J. Tradit. Complement. Med., 2014, 4(1), 24-35.
[http://dx.doi.org/10.4103/2225-4110.124335] [PMID: 24872930]
[40]
Li, S-Y.; Chen, C.; Zhang, H-Q.; Guo, H-Y.; Wang, H.; Wang, L.; Zhang, X.; Hua, S-N.; Yu, J.; Xiao, P-G.; Li, R-S.; Tan, X. Identification of natural compounds with antiviral activities against SARS-associated coronavirus. Antiviral Res., 2005, 67(1), 18-23.
[http://dx.doi.org/10.1016/j.antiviral.2005.02.007] [PMID: 15885816]
[41]
Xiao, W.; Peng, Y.; Tan, Z.; Lv, Q.; Chan, C-O.; Yang, J.; Chen, S. Comparative evaluation of chemical profiles of pyrrosiae folium originating from three pyrrosia species by HPLC-DAD combined with multivariate statistical analysis. Molecules, 2017, 22(12), 2122.
[http://dx.doi.org/10.3390/molecules22122122] [PMID: 29194397]
[42]
Oh, J.; Rho, H.S.; Yang, Y.; Yoon, J.Y.; Lee, J.; Hong, Y.D.; Kim, H.C.; Choi, S.S.; Kim, T.W.; Shin, S.S. Extracellular signal-regulated kinase is a direct target of the anti-inflammatory compound amentoflavone derived from Torreya nucifera. Mediat. Inflamm.,, 2013, 1-11.
[43]
Law, S.; Leung, A.W.; Xu, C. Is the traditional Chinese herb “Artemisia annua” possible to fight against COVID-19? Integr. Med. Res., 2020, 9(3)100474
[http://dx.doi.org/10.1016/j.imr.2020.100474] [PMID: 32742919]
[44]
Liu, Y.; Albert, A.; Gayle, A.A.; Wilder-Smith, A.; Rocklöv, J. The reproductive number of COVID-19 is higher compared to SARS Coronavirus. J. Travel Med. 2020, 27(2) taaa021
[http://dx.doi.org/10.1093/jtm/taaa021]
[45]
Dey, T.; Chatterjee, S.; Manna, S.; Nandy, A.; Basak, S.C. New computational analysis to identify the mutational changes in SARS-CoV-2, MOLNET. International Conference on Multidisciplinary Sciences, USINEWS-04, UMN, DuluthUSA2020.
[46]
Chatterjee, S.; Dey, T.; Manna, S. Emergence of a pathogenic strain of COVID-19. J. Bioinfor. Systems Biol., 2020, 3(2020), 081-091.
[47]
Korber, B.; Fischer, W.M.; Gnanakaran, S.; Yoon, H.; Theiler, J.; Abfalterer, W.; Hengartner, N.; Giorgi, E.E.; Bhattacharya, T.; Foley, B.; Hastie, K.M.; Parker, M.D.; Partridge, D.G.; Evans, C.M.; Freeman, T.M.; de Silva, T.I.; McDanal, C.; Perez, L.G.; Tang, H.; Moon-Walker, A.; Whelan, S.P.; LaBranche, C.C.; Saphire, E.O.; Montefiori, D.C. Tracking changes in SARS-CoV-2 Spike: Evidence that D614G increases infectivity of the COVID-19 virus. Cell, 2020, 182(4), 812-827.e19.
[http://dx.doi.org/10.1016/j.cell.2020.06.043] [PMID: 32697968]
[48]
Dey, T.; Biswas, S.; Chatterjee, S.; Manna, S.; Nandy, A.; Basak, S.C. 2D polar co-ordinate representation of amino acid sequences with some applications to ebola virus, SARS and SARS-CoV-2 (COVID-19), MOL2NET International Conference on Multidisciplinary Sciences, 2020. USINEWS-04, UMN, Duluth, USA.
[49]
Nandy, A.; Ghosh, A.; Nandy, P. Numerical characterization of protein sequences and application to voltage-gated sodium channel α subunit phylogeny. In Silico Biol., 2009, 9(3), 77-87.
[http://dx.doi.org/10.3233/ISB-2009-0389] [PMID: 19795567]
[50]
Purcell, A.W.; McCluskey, J.; Rossjohn, J. More than one reason to rethink the use of peptides in vaccine design. Nat. Rev. Drug Discov., 2007, 6(5), 404-414.
[http://dx.doi.org/10.1038/nrd2224] [PMID: 17473845]
[51]
Nandy, A.; Basak, S.C. A brief review of computer-assisted approaches to rational design of peptide vaccines. Int. J. Mol. Sci., 2016, 17(5)E666
[http://dx.doi.org/10.3390/ijms17050666] [PMID: 27153063]
[52]
Poland, G.A.; Whitaker, J.A.; Poland, C.M.; Ovsyannikova, I.G.; Kennedy, R.B. Vaccinology in the third millennium: Scientific and social challenges. Curr. Opin. Virol., 2016, 17, 116-125.
[http://dx.doi.org/10.1016/j.coviro.2016.03.003] [PMID: 27039875]
[53]
Poland, G.A.; Kennedy, R.B.; Ovsyannikova, I.G. Vaccinomics and personalized vaccinology: Is science leading us toward a new path of directed vaccine development and discovery? PLoS Pathog., 2011, 7(12)e1002344
[http://dx.doi.org/10.1371/journal.ppat.1002344] [PMID: 22241978]
[54]
Li, W.; Joshi, M.D.; Singhania, S.; Ramsey, K.H.; Murthy, A.K. Peptide vaccine: Progress and challenges. Vaccines (Basel), 2014, 2(3), 515-536.
[http://dx.doi.org/10.3390/vaccines2030515] [PMID: 26344743]
[55]
Biswas, S.; Chatterjee, S.; Dey, T.; Manna, S.; Nandy, A.; Das, S.; Nandy, P.; Basak, S.C. A novel approach to peptide vaccine design for ebola virus, MDPI, MOL2NET International Conference on Multidisciplinary Sciences, 5th edition session USINEWS-03: US-IN-EU Worldwide Science Workshop Series, (5th) 2019. Duluth, USA
[56]
Biswas, S.; Chatterjee, S.; Dey, T.; Dey, S.; Manna, S.; Nandy, A.; Basak, S.C. In silico approach for peptide vaccine design for CoVID 19, MDPI, MOL2NET 2020 International Conference on Multidisciplinary Sciences, 6th edition session USINEWS-04: USIN- EU Worldwide Science Workshop Series, (6th), 2020. USA
[57]
Biswas, S.; Dey, T.; Chatterjee, S.; Manna, S.; Nandy, A.; Das, S.; Nandy, P.; Basak, S.C. Novel Algorithms for In Silico Peptide Vaccine Design with Reference to Ebola Virus IEEE Xplore International Conference on Computer, Electrical & Communication Engineering (ICCECE), Kolkata, India2020, pp. 1-8.
[58]
Dey, S.; Nandy, A.; Basak, S.C.; Nandy, P.; Das, S. A Bioinformatics approach to designing a Zika virus vaccine. Comput. Biol. Chem., 2017, 68, 143-152.
[http://dx.doi.org/10.1016/j.compbiolchem.2017.03.002] [PMID: 28342423]
[59]
Ghosh, A.; Chattopadhyay, S.; Chawla-Sarkar, M.; Nandy, P.; Nandy, A. In silico study of rotavirus VP7 surface accessible conserved regions for antiviral drug/vaccine design. PLoS One, 2012, 7(7)e40749
[http://dx.doi.org/10.1371/journal.pone.0040749] [PMID: 22844409]
[60]
National Center for Biotechnology Information (NCBI)[Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information, 1988. Available from: https://www.ncbi.nlm.nih.gov/
[62]
Nandy, A. The granch techniques for analysis of DNA, RNA and protein sequences; Adv. Math. Chem. App, 2015, pp. 96-124.
[63]
Dey, T.; Chatterjee, S.; Manna, S.; Nandy, A.; Basak, S.C. Identification and computational analysis of mutations in SARS-CoV-2. Comput. Biol. Med., 2020.104166
[64]
Adamczak, R.; Porollo, A.; Meller, J. Accurate prediction of solvent accessibility using neural networks-based regression. Proteins, 2004, 56(4), 753-767.
[http://dx.doi.org/10.1002/prot.20176] [PMID: 15281128]
[65]
Wagner, M.; Adamczak, R.; Porollo, A.; Meller, J. Linear regression models for solvent accessibility prediction in proteins. J. Comput. Biol., 2005, 12(3), 355-369.
[http://dx.doi.org/10.1089/cmb.2005.12.355] [PMID: 15857247]
[66]
Porollo, A.; Adamczak, R.; Wagner, M.; Meller, J. Maximum feasibility approach for consensus classifiers. App. Protein Structure Prediction; , 2003. CIRAS
[67]
SABLE Protein Prediction Server, Available from: https://sable.cchmc.org/
[68]
Ponomarenko, J.; Bui, H.H.; Li, W.; Fusseder, N.; Bourne, P.E.; Sette, A.; Peters, B. ElliPro: A new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 2008, 9, 514.
[http://dx.doi.org/10.1186/1471-2105-9-514] [PMID: 19055730]
[69]
Wang, Y.; Geer, L.Y.; Chappey, C.; Kans, J.A.; Bryant, S.H. Cn3D: Sequence and structure views for Entrez. Trends Biochem. Sci., 2000, 25(6), 300-302.
[http://dx.doi.org/10.1016/S0968-0004(00)01561-9] [PMID: 10838572]
[70]
Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The protein data bank. Nucleic Acids Res., 2000, 28(1), 235-242.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID: 10592235]
[71]
Walls, A.C.; Park, Y.; Tortorici, M.A.; Wall, A.; McGuire, A.T.; Vessler, D. Structure, function and antigenicity of the SARS-CoV-2 spike glycoproteinElsevier Inc., 2020.
[72]
Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol., 1990, 215(3), 403-410.
[http://dx.doi.org/10.1016/S0022-2836(05)80360-2] [PMID: 2231712]
[73]
Python Programming Language. Available from: https://www.python.org/
[74]
Google Colaboratory. Available from: https://colab.research.google.com/
[75]
Protein [Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; [1988]. Accession No. QOP61471.1, surface glycoprotein [Severe acute respiratory syndrome coronavirus 2] 1988. Available from: https://www.ncbi.nlm.nih.gov/protein/QOP61471.1
[76]
Paul, S.; Lindestam Arlehamn, C.S.; Scriba, T.J.; Dillon, M.B.; Oseroff, C.; Hinz, D.; McKinney, D.M.; Carrasco Pro, S.; Sidney, J.; Peters, B.; Sette, A. Development and validation of a broad scheme for prediction of HLA class II restricted T cell epitopes. J. Immunol. Methods, 2015, 422, 28-34.
[http://dx.doi.org/10.1016/j.jim.2015.03.022] [PMID: 25862607]
[77]
Kerfeld, C.A.; Scott, K.M. Using blast to teach “E-value-tionary” concepts. PLoS Biol., 2011, 9(2)e1001014
[http://dx.doi.org/10.1371/journal.pbio.1001014]
[78]
Pindi, C.; Chirasani, V.R.; Rahman, M.H.; Ahsan, M.; Revanasiddappa, P.D.; Senapati, S. Molecular basis of differential stability and temperature sensitivity of ZIKA versus dengue virus protein shells. Sci. Rep., 2020, 10(1), 8411.
[http://dx.doi.org/10.1038/s41598-020-65288-3] [PMID: 32439929]
[79]
National Library of Medicine (US), National Center for Biotechnology Information, 1988. Available from: https://www.ncbi.nlm.nih.gov/protein/592746960

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy