USING AN IMMUNOINFORMATIC APPROACH, IDENTIFICATION OF B-CELL ENVELOPE PROTEOME FOR MULTIPATHOGENIC DENGUE AND ZIKA VIRUSES
HTML Full TextUSING AN IMMUNOINFORMATIC APPROACH, IDENTIFICATION OF B-CELL ENVELOPE PROTEOME FOR MULTIPATHOGENIC DENGUE AND ZIKA VIRUSES
Neeraj Kumar Dixit
Department of Biotechnology, Saroj Institute of Technology & Management, Lucknow, Uttar Pradesh, India.
ABSTRACT: Mosquitoes are carriers of the DENV and ZIKV diseases. DENV and ZIKV are epitopes. The current performance and technique of some of the most frequently used B-cell epitope predictors used for DV and ZV proteomes are reviewed in this paper. Our specific prediction methods, ABC pred, BC pred, and AAP Methods, as well as FBC pred, were utilized to predict 1529 B cell epitopes. For the B cell epitops, the stability index, aliphatic index, GRAVY, antigen city, allergen city, toxicity, clustering, and conservancy were investigated further. The anticipated immunogenic epitopes PLPWHAGADTGTPHWNNKEA, GGFGSLGLDCEPRTGLDFSD of ZIKV and IGVEPGQLKLSWFKKGSSIG, VEPGQLKLSWFKKGSSIGQM, IEAKLTNTTTASRCPTQGEP, LPLPWLPGADTQGSNW of DENV were 100 percent conserved. The goal of this study is Flaviviridae viruses that now affect 128 nations throughout the world. And they may both be fatal and life-threatening. A quicker and less expensive vaccine design procedure used to identify the B cell was to use computer simulations to find potential vaccination candidates and antiviral efficacy testing. The study's goal is to develop patient therapies that are both safe and effective.
Keywords: B-cell epitopes, E proteins, Dengue virus, Zika virus
INTRODUCTION: Mosquitoes carry the DEN and ZIK viruses, which are health risks and burdens that have lately attracted public attention 1. The principal vector for horizontal transfer of Viruses to humans is Aedes aegypti 2. As a result of population increase and mobility, urbanization and climate change, predictive models show that the global spread of Aedes aegypti will continue to expand 3.
DENV and ZIKV replicate their DNA via viral protein receptor-mediated endocytosis in host cells. The extrinsic incubation period is the time it takes for a virus to enter the mosquito's midgut and then be secreted in mosquito saliva. The EIP of different viral species varies. Flaviviruses like DENV and ZIKV have an estimated extrinsic incubation period of 10 to 14 days 4.
Infection of the salivary glands also changes the content of saliva, affecting blood acquisition and skin infection 5. DENV ZIKV and CHIKV infections activate the c-jun N terminal kinase (JNK) pathway, activating complement and apoptotic effectors, resulting in a broad antiviral response 6. The ZIKV pandemic was a "perfect storm" in which a novel American subclade arose from the virus's Asian origin and was introduced into a uniformly susceptible population that had never been exposed to ZIKV before 7. In some areas, such as India and Southeast Asia, where substantial populations of pregnant women are vulnerable to the virus, outbreaks and infection clusters continue to occur 8. Prior dengue infection and anti-DENV antibodies were found to diminish rather than increase the likelihood of ZIKV infection and illness in people in prospective investigations 9.
With a non-segmented, single-stranded, positive-sense RNA genome of 10 794 kb in length and two flanked non-coding regions, ZIKV, like DENV, is encapsulated and icosahedral. (5′ and 3′ NCR) and a long single open reading frame encoding a polyprotein: 5′-(C, pr, M, E, NS1, NS2A, NS2B, NS3, NS4A, NS4B, NS5)-3′ 10. Dengue infection usually causes asymptomatic, flu-like symptoms; however, the severe and fatal form, called dengue hemorrhagic fever, can cause bleeding, shock, and death. ZIKV infections are usually asymptomatic or minimally symptomatic, with symptoms of self-limiting acute febrile sickness, rash, joint discomfort, myalgia, and conjunctivitis. Severe sickness consequences, such as Guillain–Barré syndrome in adults and congenital ZIKV syndrome in neonates, have posed significant public health challenges 11.
Controlled human challenge infection models are being investigated as an alternative method of acquiring efficacy proof for regulatory approval of a vaccine 12. There is currently no effective Zika vaccine available, including a ZIKV produced, and is presently being tested in clinical studies 13, 14. Dengvaxia is a licensed dengue vaccine that offers only limited protection and comes with a list of precautions 15, 16, 17, 18 which Sanofi Pasteur 19, 20, developed. As a result, my research aimed to identify possible vaccine candidates and antiviral effectiveness tests in silico. The research objective is to find safe and effective treatments for patients 21, 22, 23. The endemic zone of vectors has grown as a result of unplanned urbanization, highlighting the need for a powerful vaccination. Because the E protein's two-layer membrane is made up of two antiparallel monomer units, it engages in membrane fusion and receptor binding as soon as the antigen enters.
The structure of E proteins categorizes them into several groups. They either recognize a quaternary epitope on the E protein dimer interface or detect a quaternary epitope on the E protein dimer interface to block ZIKV and DENV vertical transmission 24.
The E proteins of DV and ZV had 35, 51 and 29 percent protein similarity in EDI, EDII, and EDIII, respectively. Cross reactivation was rapid in domains I and II, while it was gradual in domain III. B cells are involved in cell activation, serological testing, and signal transmission. B cell peptides are made up of hydrophilic amino acids present in protein antigen molecules or other macromolecules, and they're made by soluble or membrane bound immunoglobulin 25. The epitopes were employed to develop diagnostic reagents as well as vaccines. Because B cells are antigenic, they have a high chance of attaching to antibodies. Therefore, it is proposed that soluble ED III be included as an antigen in DENV and ZIKV candidate vaccines to produce neutralizing antibodies that impede viral attachment or hinder post-entry membrane fusion.
The covalently stabilized E dimer has consistently elicited protective antibody responses against ZIKV and DENV infection. The prediction of B cell epitopes may be made using a variety of approaches. There are used in several B cell epitope prediction approaches 26, 27. When both B cell epitopes are present on the same molecule, and some of them are more immunogenic than others, the immunostimulatory one, referred to as immunodominant, would successfully limit productive capacity while inducing antibody responses. With the use of these technologies, I was able to identify immunogenic B cell epitopes, and they may improve prediction performance. These techniques are quick, simple, and affordable. Similar techniques have been used to develop vaccines against viruses including SARS-CoV, Ebola, and Chikungunya 28, 29.
MATERIALS AND METHODS:
Viral Protein Selection: The amino acid sequences of DV and ZV were retrieved from the virus pathogen resource sequence database. DENV and ZIKV E viral proteins were extracted using the FASTA format.
Prediction of B-cell Epitope: Using E protein, we predicted possible 12, 16, and 20 mer B cell epitopes from all zika and dengue virus strains. ABC pred produced continuous B-cell epitopes by using a constant length pattern 30. BC Preds is made up of two fixed-length algorithms (BC Pred and AAP methods) and one flexible length algorithm (FBC Pred algorithm). This study used two fixed length techniques (BC Pred and AAP methods) and one flexible length method (FBC Pred algorithm) to predict B-cell epitopes by the user-entered epitope sequence.
Predictions of Instability Index, Aliphatic Index and GRAVY Analysis: To estimation of stability, aliphatic index, and GRAVY for a protein, Prot param was used as TrEMBLL 31. The aliphatic index is the relative quantity in the form of aliphatic facet chains (alanine, valine, isoleucine, and leucine). The extracellular matrix is one of the calculated metrics for GRAVY analysis.
Consensus Epitope Prediction: When the anticipated Zika and dengue virus serotype epitopes (12, 16 and 20 mer) were analyze, the consensus epitope produce a better chance of eliciting an immune response to the virus.
Predictions of Antigenicity and Allergenicity: VaxiJen is the first tool for predicting viral user-defined origin defense antigens without using alignment with a threshold value of 0.4. Above o.4 value the best immune response possible when the parental antigen is presented 32. Allergen FP was used to determine allergenicity. Non-allergenic proteins were chosen based on a similarity index 33.
Predictions of Toxicity, Hydrophobicity, Hydropathicity, Charge, and Molecular Weight: Toxin Pred is used to assess epitope toxicity, hydrophobicity, hydropathicity, and terms of epitope charge and molecular weight 34.
Epitope Cluster Predictions: Using the IEDB program, all epitopes were grouped into clusters based on sequence identity within a cluster and an 80 percent sequence similarity criterion 35. For conservation, we utilized the IEDB tool 36.
Conservancy Analysis: The conservancy study is used to assess epitope dispersion in a homologous protein sample. To help with the ideal degree of conservation in epitope collection, we used the IEDB tool for the conservancy.
RESULTS:
Selection of Viral Proteins for Vaccine Preparation: The virus pathogen resource sequence database was used to produce the multipathogenic vaccine. DENV and ZIKV E proteins developed b cellular response.
Prediction of B-cell Epitopes: The Zika and Dengue viral proteomes contained a total of 1529 B-cell epitopes. The ABC pred server predicted the most B-cell epitopes (669,628) for Zika and Dengue. The BC pred server predicted 32 and 44 epitopes for Zika and Dengue, respectively, whereas AAP methods predicted 34, 43 epitopes for Zika and Dengue. 1450 epitopes were studied with the use of a fixed-length pattern (12, 16, 20 mer). The FBC pred flexible length pattern predicted 33 and 46 epitopes for Zika and Dengue. 412 epitopes, 26.94% were 12 mer, 500 epitopes, 32.70% were 16 mer, and 617 epitopes, 40.35% were 20 mer developed, respectively. A total of 82,106 epitopes were chosen for Zika and Dengue further study based on a score value of 0.9 or above.
FIG. 1: EPITOPE PREDICTION BY ABCPRED, BCPRED, AAP METHODS AND FBCPRED FOR ZIKA
FIG. 2: EPITOPE PREDICTION BY ABCPRED FOR BCPRED, AAP METHODS AND FBCPRED FOR DENGUE
Predictions of Instability Index Aliphatic Index and GRAVY Analysis: For ZIKV, 66 stable epitopes were utilised, with 16 epitopes being removed. In addition, 73 stable epitopes were utilized, with 33 epitopes for DENV removed. The thermal stability of ZIKV and DENV will be improved by all super Alphatic index values safeguarded inside aspect by examination. GRAVY research revealed 58 and 89 B cell epitopes for ZIKV and DENV, respectively, with a greater terrible value and stability score 45, 57 B cell epitopes finalized for ZIKV and DENV.
TABLE 1: PREDICTIONS OF GRAVY, ALIPHATIC INDEX AND INSTABILITY INDEX VALUE FOR ZIKA VIRUS
Start position | Sequence | Score | Gravy | Aliphatic index | instability index | Result | Name of tool |
327 | TVEVQYAGTDGPCKVP | 0.94 | -0.263 | 60.62 | 16.18 | Stable | ABC 16 mer |
165 | AKVEVTPNSPRAEATL | 0.94 | -0.419 | 79.38 | 21.51 | Stable | ABC 16 mer |
156 | TGHETDENRAKVEVTP | 0.93 | -1.438 | 42.5 | -6.54 | Stable | ABC pred 16 mer |
183 | FGSLGLDCEPRTGLDF | 0.91 | 0.013 | 73.12 | 6.68 | Stable | ABC 16 mer |
98 | DRGWGNGCGLFG | 0.999 | -0.442 | 32.5 | -22.15 | Stable | BC Pred 12 mer |
332 | YAGTDGPCKVPA | 0.995 | -0.258 | 40.83 | 40.57 | Unstable | BC Pred 12 mer |
177 | EATLGGFGSLGL | 0.984 | 0.783 | 105.83 | 19.45 | Stable | BC Pred 12 mer |
227 | AGADTGTPHWNN | 0.974 | -1.233 | 16.67 | -23.78 | Stable | BC Pred 12 mer |
74 | CPTQGEAYLDKQ | 0.968 | -1.15 | 40.83 | 25.31 | Stable | BC Pred 12 mer |
348 | DMQTLTPVGRLI | 0.948 | 0.275 | 121.67 | 11.86 | Stable | BC Pred 12 mer |
164 | RAKVEVTPNSPR | 0.944 | -1.2 | 56.67 | 25.35 | Stable | BC Pred 12 mer |
163 | NRAKVEVTPNSPRAEA | 0.998 | -1.113 | 55 | 21.51 | Stable | BC pred 16 mer |
328 | VEVQYAGTDGPCKVPA | 0.996 | -0.106 | 66.88 | 28.21 | Stable | BC pred 16 mer |
96 | LVDRGWGNGCGLFGKG | 0.991 | -0.1 | 66.88 | -34.12 | Stable | BC pred 16 mer |
227 | AGADTGTPHWNNKEAL | 0.99 | -1.038 | 43.12 | -0.53 | Stable | BC pred 16 mer |
72 | SRCPTQGEAYLDKQSD | 0.986 | -1.462 | 30.63 | 60.98 | Unstable | BC pred 16 mer |
390 | GVGDKKITHHWHRSGS | 0.97 | -1.319 | 42.5 | 33.92 | Stable | BC pred 16 mer |
425 | GDTAWDFGSVGGVFNS | 0.947 | 0.031 | 42.5 | -2.33 | Stable | BC pred 16 mer |
359 | ITANPVITESTENSKM | 0.922 | -0.394 | 73.12 | 76.1 | Unstable | BC pred 16 mer |
220 | DIPLPWHAGADTGTPHWNNK | 0.988 | -1.06 | 49 | 20.16 | Stable | BC pred 20 mer |
160 | TDENRAKVEVTPNSPRAEAT | 0.985 | -1.31 | 44 | 19.21 | Stable | BC pred 20 mer |
328 | VEVQYAGTDGPCKVPAQMAV | 0.98 | 0.135 | 73 | 30.74 | Stable | BC pred 20 mer |
378 | LDPPFGDSYIVIGVGDKKIT | 0.962 | 0.15 | 107 | 21.41 | Stable | BC pred 20 mer |
118 | VEVQYAGTDGPCKVPAQMAV | 0.962 | -1.02 | 39 | 34.19 | Stable | BC pred 20 mer |
66 | SDMASDSRCPTQGEAYLDKQ | 0.947 | -1.2 | 29.5 | 44.61 | Unstable | BC pred 20 mer |
30 | CVTVMAQDKPTV | 1 | 0.408 | 80.83 | 8.78 | Stable | AAP methoods 12 mer |
252 | RQTVVVLGSQEG | 1 | -0.075 | 105 | 57.32 | Unstable | AAP methoods 12 mer |
67 | DMASDSRCPTQG | 1 | -1.092 | 8.33 | 61.32 | Unstable | AAP methoods 12 mer |
164 | RAKVEVTPNSPR | 1 | -1.2 | 56.67 | 25.35 | Stable | AAP methoods 12 mer |
94 | RTLVDRGWGNGC | 1 | -0.692 | 56.67 | -34.68 | Stable | AAP methoods 12 mer |
378 | LDPPFGDSYIVI | 1 | 0.592 | 121.67 | 50.24 | Unstable | AAP methoods 12 mer |
336 | DGPCKVPAQMAV | 1 | 0.158 | 65 | 38.19 | Stable | AAP methoods 12 mer |
360 | TANPVITESTEN | 1 | -0.667 | 65 | 70.97 | Unstable | AAP methoods 12 mer |
13 | EGMSGGTWVDVV | 1 | 0.325 | 72.5 | 16.87 | Stable | AAP methoods 12 mer |
199 | SDLYYLTMNNKH | 1 | -1.017 | 65 | 39.18 | Stable | AAP methoods 12 mer |
46 | VTTTVSNMAEVR | 1 | 0.158 | 80.83 | 12.38 | Stable | AAP methoods 12 mer |
452 | AFKSLFGGMSWF | 1 | 0.725 | 40.83 | 43.54 | Unstable | AAP methoods 12 mer |
328 | VEVQYAGTDGPCKVPA | 1 | -0.106 | 66.88 | 28.21 | Stable | AAP methoods 16 mer |
353 | TPVGRLITANPVITES | 1 | 0.312 | 115.62 | 50.42 | Unstable | AAP methoods 16 mer |
433 | SVGGVFNSLGKGIHQI | 1 | 0.419 | 109.38 | 3.57 | Stable | AAP methoods 16 mer |
91 | VCKRTLVDRGWGNGCG | 1 | -0.369 | 60.62 | -3.13 | Stable | AAP methoods 16 mer |
392 | GDKKITHHWHRSGSTI | 1 | -1.319 | 48.75 | 39.23 | Stable | AAP methoods 16 mer |
70 | SDSRCPTQGEAYLDKQ | 1 | -1.462 | 30.63 | 45.56 | Unstable | AAP methoods 16 mer |
9 | RDFVEGMSGGTWVDVV | 1 | 0.181 | 72.5 | 10.44 | Stable | AAP methoods 16 mer |
147 | QHSGMIVNDTGHETDE | 1 | -1.238 | 42.5 | -10.63 | Stable | AAP methoods 16 mer |
371 | NSKMMLELDPPFGDSY | 1 | -0.637 | 48.75 | 64.06 | Unstable | AAP methoods 16 mer |
207 | NNKHWLVHKEWFHDIP | 1 | -1.219 | 66.88 | 33.69 | Stable | AAP methoods 16 mer |
255 | VVVLGSQEGAVHTALA | 0.999 | 1.081 | 140 | 23.43 | Stable | AAP methoods 16 mer |
162 | ENRAKVEVTPNSPRAEATLG | 1 | -0.93 | 63.5 | 19.21 | Stable | AAP methoods 20 mer |
346 | AVDMQTLTPVGRLITANPVI | 1 | 0.7 | 131.5 | 11.79 | Stable | AAP methoods 20 mer |
317 | VPAETLHGTVTVEVQYAGTD | 1 | 0.025 | 87.5 | 18.91 | Stable | AAP methoods 20 mer |
141 | LSVHGSQHSGMIVNDTGHET | 1 | -0.5 | 68 | -2.06 | Stable | AAP methoods 20 mer |
13 | EGMSGGTWVDVVLEHGGCVT | 1 | 0.31 | 77.5 | 3.32 | Stable | AAP methoods 20 mer |
92 | CKRTLVDRGWGNGCGLFGKG | 1 | -0.41 | 53.5 | -8.99 | Stable | AAP methoods 20 mer |
379 | DPPFGDSYIVIGVGDKKITH | 1 | -0.2 | 87.5 | 21.41 | Stable | AAP methoods 20 mer |
61 | YEASISDMASDSRCPTQGEA | 0.991 | -0.745 | 34.5 | 33.25 | Stable | AAP methoods 20 mer |
220 | DIPLPWHAGADTGTPHWNNK | 0.986 | -1.06 | 49 | 20.16 | Stable | AAP methoods 20 mer |
37 | DKPTVDIELVTTTVSNMAEV | 0.946 | 0.11 | 102 | 17.86 | Stable | AAP methoods 20 mer |
167 | VEVTPNSPRAEA | 1 | -0.642 | 65 | 32.42 | Stable | FBC Pred 12 mer |
332 | YAGTDGPCKVPA | 0.999 | -0.258 | 40.83 | 40.57 | Unstable | FBC Pred 12 mer |
376 | LELDPPFGDSYI | 0.986 | -0.108 | 97.5 | 57.32 | Unstable | FBC Pred 12 mer |
25 | LEHGGCVTVMAQ | 0.984 | 0.558 | 89.17 | 1.45 | Stable | FBC Pred 12 mer |
228 | GADTGTPHWNNK | 0.981 | -1.708 | 8.33 | -4.04 | Stable | FBC Pred 12 mer |
79 | EAYLDKQSDTQY | 0.979 | -1.658 | 40.83 | 33.35 | Stable | FBC Pred 12 mer |
186 | LGLDCEPRTGLD | 0.954 | -0.35 | 97.5 | 11.86 | Stable | FBC Pred 12 mer |
98 | DRGWGNGCGLFG | 0.944 | -0.442 | 32.5 | -22.15 | Stable | FBC Pred 12 mer |
152 | IVNDTGHETDEN | 0.924 | -1.442 | 56.67 | -17.51 | Stable | FBC Pred 12 mer |
165 | AKVEVTPNSPRAEATL | 1 | -0.419 | 79.38 | 21.51 | Stable | FBC Pred 16 mer |
331 | QYAGTDGPCKVPAQMA | 1 | -0.4 | 36.88 | 35.93 | Stable | FBC Pred 16 mer |
24 | VLEHGGCVTVMAQDKP | 0.997 | 0.119 | 85 | 5.61 | Stable | FBC Pred 16 mer |
224 | PWHAGADTGTPHWNNK | 0.996 | -1.525 | 12.5 | 12.47 | Stable | FBC Pred 16 mer |
374 | MMLELDPPFGDSYIVI | 0.993 | 0.7 | 115.62 | 38.38 | Stable | FBC Pred 16 mer |
74 | CPTQGEAYLDKQSDTQ | 0.988 | -1.394 | 30.63 | 34.84 | Stable | FBC Pred 16 mer |
182 | GFGSLGLDCEPRTGLD | 0.949 | -0.188 | 73.12 | 11.39 | Stable | FBC Pred 16 mer |
144 | HGSQHSGMIVNDTGHE | 0.937 | -1.031 | 42.5 | -5.07 | Stable | FBC Pred 16 mer |
159 | ETDENRAKVEVTPNSPRAEA | 1 | -1.45 | 44 | 19.21 | Stable | FBC Pred 20 mer |
327 | TVEVQYAGTDGPCKVPAQMA | 0.999 | -0.11 | 58.5 | 30.74 | Stable | FBC Pred 20 mer |
222 | PLPWHAGADTGTPHWNNKEA | 0.999 | -1.195 | 34.5 | 21.6 | Stable | FBC Pred 20 mer |
24 | VLEHGGCVTVMAQDKPTVDI | 0.996 | 0.32 | 102 | -1.03 | Stable | FBC Pred 20 mer |
66 | SDMASDSRCPTQGEAYLDKQ | 0.993 | -1.2 | 29.5 | 44.61 | Unstable | FBC Pred 20 mer |
181 | GGFGSLGLDCEPRTGLDFSD | 0.991 | -0.245 | 58.5 | 13.52 | Stable | FBC Pred 20 mer |
370 | ENSKMMLELDPPFGDSYIVI | 0.991 | -0.025 | 92.5 | 49.01 | Unstable | FBC Pred 20 mer |
TABLE 2: PREDICTIONS OF GRAVY, ALIPHATIC INDEX AND INSTABILITY INDEX VALUE FOR DENGUE VIRUS
Start
position |
Sequence | Score | Gravy | Aliphatic index | instability index | Result | Name of tool |
317 | HGTIVIRVQYEGDGSP | 0.94 | -0.400 | 85.00 | 10.32 | Stable | ABC Pred 16 mer |
178 | YGTVTMECSPRTGLDF | 0.94 | -0.181 | 42.50 | 33.65 | Stable | ABC Pred 16 mer |
58 | KYCIEAKLTNTTTASR | 0.9 | -0.613 | 61.25 | 28.87 | Stable | ABC Pred 16 mer |
219 | PWLPGADTQGSNWIQK | 0.9 | -0.944 | 55.00 | -3.88 | Stable | ABC Pred 16 mer |
98 | DRGWGNGCGLFG | 0.999 | -0.442 | 32.50 | -22.15 | Stable | BC Pred 12 mer |
386 | QLKLSWFKKGSS | 0.999 | -0.708 | 65.00 | -8.53 | Stable | BC Pred 12 mer |
64 | KLTNTTTASRCP | 0.988 | -0.750 | 40.83 | 14.59 | Stable | BC Pred 12 mer |
367 | IEAEPPFGDSYI | 0.986 | -0.217 | 73.33 | 109.98 | Unstable | BC Pred 12 mer |
354 | VNPIVTEKDSPV | 0.903 | -0.167 | 105.00 | 77.38 | Unstable | BC Pred 12 mer |
64 | KLTNTTTASRCPTQGE | 1 | -1.069 | 30.63 | 4.02 | Stable | BC Pred 16 mer |
216 | LPLPWLPGADTQGSNW | 0.998 | -0.388 | 79.38 | 20.20 | Stable | BC Pred 16 mer |
363 | SPVNIEAEPPFGDSYI | 0.995 | -0.269 | 73.12 | 151.95 | Unstable | BC Pred 16 mer |
321 | VIRVQYEGDGSPCKIP | 0.995 | -0.319 | 85.00 | 15.59 | Stable | BC Pred 16 mer |
97 | VDRGWGNGCGLFGKGG | 0.993 | -0.362 | 42.50 | -26.41 | Stable | BC Pred 16 mer |
386 | QLKLSWFKKGSSIGQM | 0.991 | -0.375 | 73.12 | -3.90 | Stable | BC Pred 16 mer |
160 | KEVKVTPQSSITEAEL | 0.971 | -0.494 | 91.25 | 60.54 | Unstable | BC Pred 16 mer |
177 | GYGTVTMECSPRTGLD | 0.958 | -0.381 | 42.50 | 33.06 | Stable | BC Pred 16 mer |
141 | ITPHSGEENAVGNDTG | 0.94 | -0.950 | 48.75 | -0.28 | Stable | BC Pred 16 mer |
25 | LEHGSCVTTMAKNKPT | 0.93 | -0.544 | 48.75 | 26.34 | Stable | BC Pred 16 mer |
382 | VEPGQLKLSWFKKGSSIGQM | 0.999 | -0.365 | 73.00 | 8.51 | Stable | BC Pred 20 mer |
64 | KLTNTTTASRCPTQGEPSLN | 0.999 | -0.960 | 44.00 | 24.48 | Sable | BC Pred 20 mer |
217 | PLPWLPGADTQGSNWIQKET | 0.994 | -0.855 | 63.50 | 8.53 | Stable | BC Pred 20 mer |
353 | TVNPIVTEKDSPVNIEAEPP | 0.987 | -0.505 | 87.50 | 113.63 | Unstable | BC Pred 20 mer |
317 | HGTIVIRVQYEGDGSPCKIP | 0.978 | -0.245 | 87.50 | 0.80 | Stable | BC Pred 20 mer |
96 | MVDRGWGNGCGLFGKGGIVT | 0.914 | 0.205 | 68.00 | -31.86 | Stable | BC Pred 20 mer |
478 | SLVLVGVVTLYL | 1 | 2.400 | 226.67 | -4.98 | Stable | AAP Methods 12 mer |
106 | GLFGKGGIVTCA | 1 | 1.117 | 97.50 | -15.92 | Stable | AAP Methods 12 mer |
79 | EPSLNEEQDKRF | 1 | -2.100 | 32.50 | 120.63 | Unstable | AAP Methods 12 mer |
389 | LSWFKKGSSIGQ | 1 | -0.358 | 65.00 | 5.62 | Stable | AAP Methods 12 mer |
150 | AVGNDTGKHGKE | 1 | -1.450 | 32.50 | -47.38 | Stable | AAP Methods 12 mer |
121 | CKKNMEGKIVQP | 1 | -0.925 | 56.67 | 3.99 | Stable | AAP Methods 12 mer |
32 | TTMAKNKPTLDF | 1 | -0.683 | 40.83 | 26.62 | Stable | AAP Methods 12 mer |
165 | TPQSSITEAELT | 1 | -0.475 | 73.33 | 93.93 | Unstable | AAP Methods 12 mer |
65 | LTNTTTASRCPT | 1 | -0.483 | 40.83 | 21.67 | Stable | AAP Methods 12 mer |
288 | RMDKLQLKGMSY | 1 | -0.86 | 65.00 | 44.65 | Unstable | AAP Methods 12 mer |
324 | VQYEGDGSPCKI | 1 | -0.642 | 56.67 | 19.86 | Stable | AAP Methods 12 mer |
369 | AEPPFGDSYIII | 1 | 0.450 | 105.83 | 73.37 | Unstable | AAP Methods 12 mer |
355 | NPIVTEKDSPVN | 1 | -0.808 | 80.83 | 77.38 | Unstable | AAP Methods 12 mer |
93 | KHSMVDRGWGNG | 1 | -1.283 | 24.17 | -34.68 | Stable | AAP Methods 12 mer |
13 | EGVSGGSWVDIV | 1 | 0.533 | 105.00 | -7.23 | Stable | AAP Methods 12 mer |
249 | DVVVLGSQEGAM | 1 | 0.667 | 113.33 | 34.19 | Stable | AAP Methods 12 mer |
221 | LPGADTQGSNWI | 1 | -0.433 | 73.33 | -16.38 | Stable | AAP Methods 12 mer |
47 | KTEAKQPATLRK | 1 | -1.567 | 49.17 | 93.10 | Unstable | AAP Methods 12 mer |
100 | GWGNGCGLFGKGGIVT | 1 | 0.375 | 66.88 | -22.91 | Stable | AAP methods 16 mer |
384 | PGQLKLSWFKKGSSIG | 1 | -0.400 | 73.12 | -3.90 | Stable | AAP methods 16 mer |
67 | NTTTASRCPTQGEPSL | 1 | -0.931 | 30.63 | 42.79 | Unstable | AAP methods 16 mer |
357 | IVTEKDSPVNIEAEPP | 1 | -0.531 | 91.25 | 141.34 | Unstable | AAP methods 16 mer |
321 | VIRVQYEGDGSPCKIP | 1 | -0.319 | 85.00 | 15.59 | Stable | AAP methods 16 mer |
245 | AKKQDVVVLGSQEGAM | 1 | -0.094 | 91.25 | 54.98 | Unstable | AAP methods 16 mer |
47 | KTEAKQPATLRKYCIE | 1 | -1.038 | 61.25 | 99.79 | Unstable | AAP methods 16 mer |
19 | SWVDIVLEHGSCVTTM | 1 | 0.675 | 103.12 | -11.47 | Stable | AAP methoods 16 mer |
216 | LPLPWLPGADTQGSNW | 1 | -0.388 | 79.38 | 20.20 | Stable | AAP methods 16 mer |
144 | HSGEENAVGNDTGKHG | 1 | -1.556 | 24.38 | -12.06 | Stable | AAP methods 16 mer |
177 | GYGTVTMECSPRTGLD | 1 | -0.381 | 42.50 | 33.06 | Stable | AAP methods 16 mer |
119 | FTCKKNMEGKIVQPEN | 1 | -1.000 | 42.50 | 16.36 | Stable | AAP methods 16 mer |
437 | HQVFGAIYGAAFSGVS | 0.999 | 0.819 | 79.38 | -11.26 | Stable | AAP methods 16 mer |
385 | GQLKLSWFKKGSSIGQMFET | 1 | -0.390 | 58.50 | -1.12 | Stable | AAP methods 20 mer |
314 | ETQHGTIVIRVQYEGDGSPC | 1 | -0.580 | 68.00 | 2.71 | Stable | AAP methods 20 mer |
349 | GRLITVNPIVTEKDSPVNIE | 1 | -0.090 | 121.50 | 94.37 | Unstable | AAP methoods 20 mer |
37 | NKPTLDFELIKTEAKQPATL | 1 | -0.610 | 88.00 | 50.29 | Unstable | AAP methods 20 mer |
255 | SQEGAMHTALTGATEIQMSS | 1 | -0.250 | 54.00 | 91.75 | Unstable | AAP methods 20 mer |
61 | IEAKLTNTTTASRCPTQGEP | 1 | -0.795 | 49.00 | 36.82 | Stable | AAP methods 20 mer |
139 | IVITPHSGEENAVGNDTGKH | 1 | -0.680 | 73.00 | -6.71 | Stable | AAP methods 20 mer |
96 | MVDRGWGNGCGLFGKGGIVT | 1 | 0.205 | 68.00 | -31.86 | Stable | AAP methods 20 mer |
187 | PRTGLDFNEMVLLQMENKAW | 1 | -0.450 | 78.00 | 25.86 | Stable | AAP methods 20 mer |
5 | GISNRDFVEGVSGGSWVDIV | 0.997 | 0.260 | 97.00 | -8.35 | Stable | AAP methods 20 mer |
118 | MFTCKKNMEGKIVQPENLEY | 0.985 | -0.755 | 53.50 | 15.09 | Stable | AAP methods 20 mer |
478 | SLVLVGVVTLYL | 1 | 2.400 | 226.67 | -4.98 | Stable | FBC Pred 12 mer |
106 | GLFGKGGIVTCA | 1 | 1.117 | 97.50 | -15.92 | Stable | FBC Pred 12 mer |
79 | EPSLNEEQDKRF | 1 | -2.100 | 32.50 | 120.63 | Unstable | FBC Pred 12 mer |
63 | AKLTNTTTASRC | 1 | -0.467 | 49.17 | -1.46 | Stable | FBC Pred 12 mer |
388 | KLSWFKKGSSIG | 1 | -0.392 | 65.00 | -1.46 | Stable | FBC Pred 12 mer |
142 | TPHSGEENAVGN | 0.999 | -1.258 | 32.50 | 15.90 | Stable | FBC Pred 12 mer |
78 | GEPSLNEEQDKR | 0.999 | -2.367 | 32.50 | 114.34 | Unstable | FBC Pred 12 mer |
217 | PLPWLPGADTQG | 0.998 | -0.400 | 73.33 | 16.19 | Stable | FBC Pred 12 mer |
367 | IEAEPPFGDSYI | 0.993 | -0.217 | 73.33 | 109.98 | Unstable | FBC Pred 12 mer |
307 | KVVKEIAETQHG | 0.993 | -0.658 | 89.17 | 0.82 | Stable | FBC Pred 12 mer |
47 | KTEAKQPATLRK | 0.988 | -1.567 | 49.17 | 93.10 | Unstable | FBC Pred 12 mer |
265 | TGATEIQMSSGN | 0.982 | -0.508 | 40.83 | 72.71 | Unstable | FBC Pred 12 mer |
25 | LEHGSCVTTMAK | 0.981 | 0.083 | 65.00 | 18.33 | Stable | FBC Pred 12 mer |
181 | VTMECSPRTGLD | 0.98 | -0.275 | 56.67 | 61.97 | Unstable | FBC Pred 12 mer |
353 | TVNPIVTEKDSP | 0.965 | -0.575 | 80.83 | 61.33 | Unstable | FBC Pred 12 mer |
160 | KEVKVTPQSSIT | 0.959 | -0.542 | 80.83 | 61.33 | Unstable | FBC Pred 12 mer |
241 | KNPHAKKQDVVV | 0.951 | -1.050 | 80.83 | 42.55 | Unstable | FBC Pred 12 mer |
321 | VIRVQYEGDGSP | 0.948 | -0.550 | 80.83 | 33.22 | Stable | FBC Pred 12 mer |
98 | DRGWGNGCGLFG | 0.944 | -0.442 | 32.50 | -22.15 | Stable | FBC Pred 12 mer |
463 | ITWIGMNSRSTS | 0.855 | -0.183 | 65.00 | 49.31 | Unstable | FBC Pred 12 mer |
63 | AKLTNTTTASRCPTQG | 1 | -0.738 | 36.88 | 8.73 | Stable | FBC Pred 16 mer |
142 | TPHSGEENAVGNDTGK | 1 | -1.475 | 24.38 | -5.58 | Stable | FBC Pred 16 mer |
386 | QLKLSWFKKGSSIGQM | 1 | -0.375 | 73.12 | -3.90 | Stable | FBC Pred 16 mer |
307 | KVVKEIAETQHGTIVI | 0.999 | 0.287 | 133.75 | -7.50 | Stable | FBC Pred 16 mer |
216 | LPLPWLPGADTQGSNW | 0.999 | -0.388 | 79.38 | 20.20 | Stable | FBC Pred 16 mer |
365 | VNIEAEPPFGDSYIII | 0.996 | 0.444 | 121.88 | 112.45 | Unstable | FBC Pred 16 mer |
25 | LEHGSCVTTMAKNKPT | 0.995 | -0.544 | 48.75 | 26.34 | Stable | FBC Pred 16 mer |
261 | HTALTGATEIQMSSGN | 0.984 | -0.275 | 61.25 | 52.32 | Unstable | FBC Pred 16 mer |
237 | LVTFKNPHAKKQDVVV | 0.963 | -0.156 | 103.12 | 27.43 | Stable | FBC Pred 16 mer |
80 | PSLNEEQDKRFVCKHS | 0.957 | -1.431 | 42.50 | 80.93 | Unstable | FBC Pred 16 mer |
177 | GYGTVTMECSPRTGLD | 0.95 | -0.381 | 42.50 | 33.06 | Stable | FBC Pred 16 mer |
63 | AKLTNTTTASRCPTQGEPSL | 1 | -0.695 | 49.00 | 24.48 | Stable | FBC Pred 20 mer |
139 | IVITPHSGEENAVGNDTGKH | 1 | -0.680 | 73.00 | -6.71 | Stable | FBC Pred 20 mer |
307 | KVVKEIAETQHGTIVIRVQY | 1 | -0.025 | 121.50 | -7.77 | Stable | FBC Pred 20 mer |
380 | IGVEPGQLKLSWFKKGSSIG | 1 | -0.080 | 92.50 | 8.51 | Stable | FBC Pred 20 mer |
214 | LDLPLPWLPGADTQGSNWIQ | 0.999 | -0.245 | 102.50 | 18.16 | Stable | FBC Pred 20 mer |
353 | TVNPIVTEKDSPVNIEAEPP | 0.996 | -0.505 | 87.50 | 113.63 | Unstable | FBC Pred 20 mer |
23 | IVLEHGSCVTTMAKNKPTLD | 0.994 | 0.015 | 92.50 | 18.82 | Stable | FBC Pred 20 mer |
256 | QEGAMHTALTGATEIQMSSG | 0.982 | -0.230 | 54.00 | 82.12 | Unstable | FBC Pred 20 mer |
Consensus Epitope Prediction: BC pred predicted 1, 4, and 3 consensus epitopes (12mer, 16mer, 20mer) respectively. 1, 3 (16mer, 20mer) consensus epitopes were predicted by AAP method. FBC pred predicted Most of the 2, 5, 4 consensus epitopes (12mer, 16mer, 20mer) respectively. In an analysis of DENV protein, 2 (16mer) ABC predicted consensus epitopes pred whereas BC pred predicted 4, 4 consensus epitopes (16mer, 20mer) respectively.4, 5 (16mer, 20mer) consensus epitopes were predicted by AAP method. FBC pred predicted Most of the 1, 3 and 4 consensus epitopes (12mer, 16mer, 20mer). 24 (47%) consensus epitopes have a confirmed length of 16mer. There were 23 (45%) 20 mer and 4 (8%) 12 mer, respectively.
TABLE 3: PREDICTIONS OF CONSENSUS EPITOPES FOR ZIKA AND DENGUE
Zika | Dengue | ||||||
Sequence | Score | Epitope length | Tool | Sequence | Score | Epitope length | Tool |
AKVEVTPNSPRAEATL | 0.94 | 16 mer | ABC pred | HGTIVIRVQYEGDGSP | 0.94 | 16 mer | ABC pred |
RAKVEVTPNSPR | 0.944 | 12 mer | BC pred | PWLPGADTQGSNWIQK | 0.9 | 16 mer | ABC pred |
NRAKVEVTPNSPRAEA | 0.998 | 16 mer | BC pred | KLTNTTTASRCPTQGE | 1 | 16 mer | BC pred |
VEVQYAGTDGPCKVPA | 0.996 | 16 mer | BC pred | VIRVQYEGDGSPCKIP | 0.995 | 16 mer | BC pred |
LVDRGWGNGCGLFGKG | 0.991 | 16 mer | BC pred | VDRGWGNGCGLFGKGG | 0.993 | 16 mer | BC pred |
AGADTGTPHWNNKEAL | 0.99 | 16 mer | BC pred | QLKLSWFKKGSSIGQM | 0.991 | 16 mer | BC pred |
DIPLPWHAGADTGTPHWNNK | 0.988 | 20 mer | BC pred | VEPGQLKLSWFKKGSSIGQM | 0.999 | 20 mer | BC pred |
TDENRAKVEVTPNSPRAEAT | 0.985 | 20 mer | BC pred | KLTNTTTASRCPTQGEPSLN | 0.999 | 20 mer | BC pred |
VEVQYAGTDGPCKVPAQMAV | 0.962 | 20 mer | BC pred | PLPWLPGADTQGSNWIQKET | 0.994 | 20 mer | BC pred |
VCKRTLVDRGWGNGCG | 1 | 16 mer | AAP meth | HGTIVIRVQYEGDGSPCKIP | 0.987 | 20 mer | BC pred |
ENRAKVEVTPNSPRAEATLG | 1 | 20 mer | AAP meth | PGQLKLSWFKKGSSIG | 1 | 16 mer | AAP meth |
LSVHGSQHSGMIVNDTGHET | 1 | 20 mer | AAP meth | LPLPWLPGADTQGSNW | 1 | 16 mer | AAP meth |
CKRTLVDRGWGNGCGLFGKG | 1 | 20 mer | AAP meth | GYGTVTMECSPRTGLD | 1 | 16 mer | AAP meth |
VEVTPNSPRAEA | 1 | 12 mer | FBC Pred | FTCKKNMEGKIVQPEN | 1 | 16 mer | AAP meth |
DRGWGNGCGLFG | 0.944 | 12 mer | FBC Pred | GQLKLSWFKKGSSIGQMFET | 1 | 20mer | AAP meth |
QYAGTDGPCKVPAQMA | 1 | 16 mer | FBC Pred | ETQHGTIVIRVQYEGDGSPC | 1 | 20 mer | AAP meth |
PWHAGADTGTPHWNNK | 0.996 | 16 mer | FBC Pred | IEAKLTNTTTASRCPTQGEP | 1 | 20 mer | AAP meth |
CPTQGEAYLDKQSDTQ | 0.988 | 16 mer | FBC Pred | IVITPHSGEENAVGNDTGKH | 1 | 20 mer | AAP meth |
GFGSLGLDCEPRTGLD | 0.949 | 16 mer | FBC Pred | MFTCKKNMEGKIVQPENLEY | 0.985 | 20 mer | AAP meth |
HGSQHSGMIVNDTGHE | 0.937 | 16 mer | FBC Pred | DRGWGNGCGLFG | 0.944 | 12mer | FBC pred |
ETDENRAKVEVTPNSPRAEA | 1 | 20 mer | FBC Pred | AKLTNTTTASRCPTQG | 1 | 16 mer | FBC pred |
TVEVQYAGTDGPCKVPAQMA | 0.999 | 20 mer | FBC Pred | TPHSGEENAVGNDTGK | 1 | 16 mer | FBC pred |
PLPWHAGADTGTPHWNNKEA | 0.999 | 20 mer | FBC Pred | LEHGSCVTTMAKNKPT | 0.995 | 16 mer | FBC pred |
GGFGSLGLDCEPRTGLDFSD | 0.991 | 20 mer | FBC Pred | AKLTNTTTASRCPTQGEPSL | 1 | 20 mer | FBC pred |
KVVKEIAETQHGTIVIRVQY | 1 | 20 mer | FBC pred | ||||
IGVEPGQLKLSWFKKGSSIG | 1 | 20 mer | FBC pred | ||||
LDLPLPWLPGADTQGSNWIQ | 0.999 | 20 mer | FBC pred |
Predictions of Antigenicity and Allergenicity: Allergen FP predicts non-allergic effects of the final vaccination formulation. Antigenicity and allergenicity were evaluated on 24, 27 Zika and Dengue consensus epitopes. BC pred had the most antigenic and Non Allergenic 10 epitopes (35.71%), followed by FBC pred 9 epitopes (32.14%) and 7, 2 epitopes (25 %, 7.14%) from the AAP Methods and ABC pred.
TABLE 4: PREDICTIONS OF ANTIGENICITY AND ALLERGENICITY FOR ZIKA VIRUS
Epitope length | sequence
|
Vaxijen score | Antigenicity | Allergenicity | Result
|
Tool |
16 mer | AKVEVTPNSPRAEATL | 0.6917 | Antigen | 0.55 | Non Allergen | ABC pred |
12 mer | RAKVEVTPNSPR | 0.6219 | Antigen | 0.59 | Non Allergen | BC pred |
16 mer | NRAKVEVTPNSPRAEA | 0.5131 | Antigen | 0.55 | Non Allergen | BC pred |
16 mer | VEVQYAGTDGPCKVPA | 0.2715 | Non Antigen | 0.52 | Non Allergen | BC pred |
16 mer | LVDRGWGNGCGLFGKG | 0.4848 | Antigen | 0.58 | allergen | BC pred |
16 mer | AGADTGTPHWNNKEAL | 0.8268 | Antigen | 0.57 | Non Allergen | BC pred |
20 mer | DIPLPWHAGADTGTPHWNNK | 0.7757 | Antigen | 0.61 | allergen | BC pred |
20 mer | TDENRAKVEVTPNSPRAEAT | 0.5860 | Antigen | 0.63 | Non Allergen | BC pred |
20 mer | VEVQYAGTDGPCKVPAQMAV | 0.4222 | Antigen | 0.6 | Non Allergen | BC pred |
16 mer | VCKRTLVDRGWGNGCG | 0.4492 | Non Antigen | 0.53 | Non Allergen | AAP methods |
20 mer | ENRAKVEVTPNSPRAEATLG | 0.7850 | Antigen | 0.63 | Non Allergen | AAP methods |
20 mer | LSVHGSQHSGMIVNDTGHET | 0.1743 | Non Antigen | 0.67 | allergen | AAP methods |
20 mer | CKRTLVDRGWGNGCGLFGKG | 0.1147 | Non Antigen | 0.62 | Non Allergen | AAP methods |
12 mer | VEVTPNSPRAEA | 0.5990 | Antigen | 0.61 | Non Allergen | FBC Pred |
12 mer | DRGWGNGCGLFG | 0.1661 | Non Antigen | 0.65 | Non Allergen | FBC Pred |
16 mer | QYAGTDGPCKVPAQMA | 0.1466 | Non Antigen | 0.59 | allergen | FBC Pred |
16 mer | PWHAGADTGTPHWNNK | 0.8358 | Antigen | 0.58 | Non Allergen | FBC Pred |
16 mer | CPTQGEAYLDKQSDTQ | 0.3721 | Non Antigen | 0.61 | Non Allergen | FBC Pred |
16 mer | GFGSLGLDCEPRTGLD | 1.3220 | Antigen | 0.58 | Non Allergen | FBC Pred |
16 mer | HGSQHSGMIVNDTGHE | 0.0332 | Non Antigen | 0.65 | Non Allergen | FBC Pred |
20 mer | ETDENRAKVEVTPNSPRAEA | 0.4149 | Antigen | 0.62 | allergen | FBC Pred |
20 mer | TVEVQYAGTDGPCKVPAQMA | 0.1270 | Non Antigen | 0.69 | allergen | FBC Pred |
20 mer | PLPWHAGADTGTPHWNNKEA | 0.9325 | Antigen | 0.61 | Non Allergen | FBC Pred |
20 mer | GGFGSLGLDCEPRTGLDFSD | 1.5554 | Antigen | 0.64 | Non Allergen | FBC Pred |
TABLE 5: PREDICTIONS OF ANTIGENICITY AND ALLERGENICITY FOR DENGUE VIRUS
Epitope length | Sequence | Vaxi Jen score | Antigenicity | Allergenicity | Result | Tool |
16 mer | HGTIVIRVQYEGDGSP | 0.9363 | Antigen | 0.55 | Non Allergen | ABC pred |
16 mer | PWLPGADTQGSNWIQK | 0.2599 | Non Antigen | 0.57 | Non Allergen | ABC pred |
16 mer | KLTNTTTASRCPTQGE | 0.8589 | Antigen | 0.59 | Non Allergen | BC pred |
16 mer | VIRVQYEGDGSPCKIP | 0.2868 | Non Antigen | 0.5 | allergen | BC pred |
16 mer | VDRGWGNGCGLFGKGG | 0.6497 | Antigen | 0.6 | Non Allergen | BC pred |
16 mer | QLKLSWFKKGSSIGQM | 1.0680 | Antigen | 0.63 | Non Allergen | BC pred |
20 mer | VEPGQLKLSWFKKGSSIGQM | 1.0872 | Antigen | 0.67 | Non Allergen | BC pred |
20 mer | KLTNTTTASRCPTQGEPSLN | 0.8825 | Antigen | 0.66 | allergen | BC pred |
20 mer | PLPWLPGADTQGSNWIQKET | 0.5089 | Antigen | 0.65 | Non Allergen | BC pred |
20 mer | HGTIVIRVQYEGDGSPCKIP | 0.5904 | Antigen | 0.62 | allergen | BC pred |
16 mer | PGQLKLSWFKKGSSIG | 1.0629 | Antigen | 0.61 | Non Allergen | AAP methods |
16 mer | LPLPWLPGADTQGSNW | 0.5417 | Antigen | 0.54 | Non Allergen | AAP methods |
16 mer | GYGTVTMECSPRTGLD | 0.7913 | Antigen | 0.58 | Non Allergen | AAP methods |
16 mer | FTCKKNMEGKIVQPEN | 0.3722 | Non Antigen | 0.61 | Non Allergen | AAP methods |
20mer | GQLKLSWFKKGSSIGQMFET | 0.6671 | Antigen | 0.68 | Non Allergen | AAP methods |
20 mer | ETQHGTIVIRVQYEGDGSPC | 0.9347 | Antigen | 0.61 | Non Allergen | AAP methods |
20 mer | IEAKLTNTTTASRCPTQGEP | 1.0315 | Antigen | 0.65 | Non Allergen | AAP methods |
20 mer | IVITPHSGEENAVGNDTGKH | 0.1396 | Non Antigen | 0.65 | Non Allergen | AAP methods |
20 mer | MFTCKKNMEGKIVQPENLEY | 0.5536 | Antigen | 0.64 | allergen | AAP methods |
12mer | DRGWGNGCGLFG | 0.1661 | Non Antigen | 0.65 | Non Allergen | FBC pred |
16 mer | AKLTNTTTASRCPTQG | 0.8092 | Antigen | 0.6 | Non Allergen | FBC pred |
16 me | TPHSGEENAVGNDTGK | -0.1015 | Non Antigen | 0.59 | Non Allergen | FBC pred |
16 me | LEHGSCVTTMAKNKPT | 0.4300 | Antigen | 0.56 | Non Allergen | FBC pred |
20 mer | AKLTNTTTASRCPTQGEPSL | 0.9032 | Antigen | 0.65 | Non Allergen | FBC pred |
20 mer | KVVKEIAETQHGTIVIRVQY | 0.7464 | Antigen | 0.67 | allergen | FBC pred |
20 mer | IGVEPGQLKLSWFKKGSSIG | 1.3301 | Antigen | 0.65 | Non Allergen | FBC pred |
20 mer | LDLPLPWLPGADTQGSNWIQ | 0.3370 | Non Antigen | 0.65 | allergen | FBC pred |
Predictions of Toxicity, Hydrophobicity, Hydropathicity, Charge and Mol. Weight of Zika: All epitopes for ZV and DV in my study were non-toxic, hydrophobic and hydropathic with Charge and Molecular Weight.
TABLE 6: PREDICTIONS OF TOXICITY, HYDROPHOBICITY, HYDROPATHICITY, CHARGE, MOL. WT. OF ZIKA
Peptide Sequence | SVM Score | Prediction | Charge | Mol. Wt. | Hydrophobicity | Hydropathicity |
AKVEVTPNSPRAEATL | -1.05 | Non-Toxin | 0.00 | 1683.11 | -0.20 | -0.42 |
RAKVEVTPNSPR | -0.88 | Non-Toxin | 2.00 | 1353.70 | -0.43 | -1.20 |
NRAKVEVTPNSPRAEA | -0.86 | Non-Toxin | 1.00 | 1739.13 | -0.37 | -1.11 |
AGADTGTPHWNNKEAL | -0.59 | Non-Toxin | -0.50 | 1682.01 | -0.16 | -1.04 |
TDENRAKVEVTPNSPRAEAT | -0.84 | Non-Toxin | -1.00 | 2185.60 | -0.38 | -1.31 |
VEVQYAGTDGPCKVPAQMAV | -0.91 | Non-Toxin | -1.00 | 2063.66 | -0.03 | -0.14 |
ENRAKVEVTPNSPRAEATLG | -1.05 | Non-Toxin | 0.00 | 2139.63 | -0.30 | -0.93 |
VEVTPNSPRAEA | -1.12 | Non-Toxin | -1.00 | 1269.53 | -0.22 | -0.64 |
PWHAGADTGTPHWNNK | -0.58 | Non-Toxin | 1.00 | 1789.13 | -0.18 | -1.52 |
GFGSLGLDCEPRTGLD | -1.02 | Non-Toxin | -2.00 | 1637.03 | -0.09 | -0.19 |
PLPWHAGADTGTPHWNNKEA | -0.80 | Non-Toxin | 0.00 | 2199.66 | -0.14 | -1.20 |
GGFGSLGLDCEPRTGLDFSD | -1.16 | Non-Toxin | -3.00 | 2043.48 | -0.08 | -0.25 |
TABLE 7: PREDICTIONS OF TOXICITY, HYDROPHOBICITY, HYDROPATHICITY, CHARGE, MOL.WT. OF DENGUE
Peptide Sequence | SVM Score | Prediction | Charge | Mol.Wt. | Hydrophobicity | Hydropathicity |
HGTIVIRVQYEGDGSP | -0.60 | Non-Toxin | -0.50 | 1728.14 | -0.10 | -0.40 |
KLTNTTTASRCPTQGE | -0.98 | Non-Toxin | 1.00 | 1708.10 | -0.32 | -1.07 |
VDRGWGNGCGLFGKGG | -1.04 | Non-Toxin | 1.00 | 1580.00 | -0.06 | -0.36 |
QLKLSWFKKGSSIGQM | -1.14 | Non-Toxin | 3.00 | 1838.45 | -0.13 | -0.38 |
VEPGQLKLSWFKKGSSIGQM | -1.26 | Non-Toxin | 2.00 | 2220.93 | -0.10 | -0.37 |
PLPWLPGADTQGSNWIQKET | -0.87 | Non-Toxin | -1.00 | 2238.79 | -0.11 | -0.86 |
PGQLKLSWFKKGSSIG | -1.32 | Non-Toxin | 3.00 | 1733.29 | -0.10 | -0.40 |
LPLPWLPGADTQGSNW | -1.03 | Non-Toxin | -1.00 | 1752.20 | 0.01 | -0.39 |
GYGTVTMECSPRTGLD | -0.17 | Non-Toxin | -1.00 | 1687.10 | -0.13 | -0.38 |
GQLKLSWFKKGSSIGQMFET | -1.27 | Non-Toxin | 2.00 | 2272.96 | -0.11 | -0.39 |
ETQHGTIVIRVQYEGDGSPC | -0.80 | Non-Toxin | -1.50 | 2189.69 | -0.16 | -0.58 |
IEAKLTNTTTASRCPTQGEP | -0.94 | Non-Toxin | 0.00 | 2118.63 | -0.24 | -0.80 |
AKLTNTTTASRCPTQG | -0.79 | Non-Toxin | 2.00 | 1650.06 | -0.26 | -0.74 |
LEHGSCVTTMAKNKPT | -0.34 | Non-Toxin | 1.50 | 1717.22 | -0.18 | -0.54 |
AKLTNTTTASRCPTQGEPSL | -0.95 | Non-Toxin | 1.00 | 2076.59 | -0.23 | -0.70 |
IGVEPGQLKLSWFKKGSSIG | -1.50 | Non-Toxin | 2.00 | 2131.82 | -0.04 | -0.08 |
Predictions Epitope Cluster: All epitopes were organized into clusters. Alignment TDENRAKVEVTPNSPRAEATLG has the most Consensus epitopes 5, followed by Alignment PLPWHAGADTGTPHWNNKEAL with 3 Consensus epitopes and Alignment GGFGSLG-LDCEPRTGLDFSD with 2 Consensus epitopes for ZIKV. DENV works in a similar way.
Alignment IGVEPGQLKLSWFKKGSSIGQM, VEPGQLKLSWFKKGSSIGQMFET and IEAK-LTNTTTASRCPTQGEPSL, had the most consensus epitopes 4, while Alignment LPLPWLPGADTQGSNWIQKET and ETQHGTIVIRVQYEGDGSPC had 2 consensus epitopes.
TABLE 8: PREDICTIONS EPITOPE CLUSTER OF ZIKA
Clique No. | Peptide No. | Alignment | Position | Description | Peptide |
1 | Consensus | TDENRAKVEVTPNSPRAEATLG | - | - | - |
1 | 1 | TDENRAKVEVTPNSPRAEAT-- | 1 | seq9 | TDENRAKVEVTPNSPRAEAT |
1 | 2 | --ENRAKVEVTPNSPRAEATLG | 3 | seq13 | ENRAKVEVTPNSPRAEATLG |
1 | 3 | ---NRAKVEVTPNSPRAEA--- | 4 | seq5 | NRAKVEVTPNSPRAEA |
1 | 4 | ----RAKVEVTPNSPR------ | 5 | seq3 | RAKVEVTPNSPR |
1 | 5 | -----AKVEVTPNSPRAEATL- | 6 | seq1 | AKVEVTPNSPRAEATL |
3 | Consensus | PLPWHAGADTGTPHWNNKEAL | - | - | - |
3 | 1 | PLPWHAGADTGTPHWNNKEA- | 1 | seq21 | PLPWHAGADTGTPHWNNKEA |
3 | 2 | --PWHAGADTGTPHWNNK--- | 3 | seq17 | PWHAGADTGTPHWNNK |
3 | 3 | -----AGADTGTPHWNNKEAL | 6 | seq7 | AGADTGTPHWNNKEAL |
4 | Consensus | GGFGSLGLDCEPRTGLDFSD | - | - | - |
4 | 1 | GGFGSLGLDCEPRTGLDFSD | 1 | seq23 | GGFGSLGLDCEPRTGLDFSD |
4 | 2 | -GFGSLGLDCEPRTGLD--- | 2 | seq19 | GFGSLGLDCEPRTGLD |
5 | Singleton | VEVQYAGTDGPCKVPAQMAV | - | seq11 | VEVQYAGTDGPCKVPAQMAV |
TABLE 9: PREDICTIONS EPITOPE CLUSTER OF DENGUE
Clique NO. | Peptide No. | Alignment | Position | Description | Peptide |
1 | Consensus | IGVEPGQLKLSWFKKGSSIGQM | - | - | - |
1 | 1 | IGVEPGQLKLSWFKKGSSIG-- | 1 | seq33 | IGVEPGQLKLSWFKKGSSIG |
1 | 2 | --VEPGQLKLSWFKKGSSIGQM | 3 | seq7 | VEPGQLKLSWFKKGSSIGQM |
1 | 3 | ----PGQLKLSWFKKGSSIG-- | 5 | seq11 | PGQLKLSWFKKGSSIG |
1 | 4 | ------QLKLSWFKKGSSIGQM | 7 | seq26 | QLKLSWFKKGSSIGQM |
2 | Consensus | VEPGQLKLSWFKKGSSIGQMFET | - | - | - |
2 | 1 | VEPGQLKLSWFKKGSSIGQM--- | 1 | seq7 | VEPGQLKLSWFKKGSSIGQM |
2 | 2 | --PGQLKLSWFKKGSSIG----- | 3 | seq11 | PGQLKLSWFKKGSSIG |
2 | 3 | ---GQLKLSWFKKGSSIGQMFET | 4 | seq17 | GQLKLSWFKKGSSIGQMFET |
2 | 4 | ----QLKLSWFKKGSSIGQM--- | 5 | seq26 | QLKLSWFKKGSSIGQM |
3 | Consensus | IEAKLTNTTTASRCPTQGEPSL | - | - | - |
3 | 1 | IEAKLTNTTTASRCPTQGEP-- | 1 | seq21 | IEAKLTNTTTASRCPTQGEP |
3 | 2 | --AKLTNTTTASRCPTQGEPSL | 3 | seq30 | AKLTNTTTASRCPTQGEPSL |
3 | 3 | --AKLTNTTTASRCPTQG---- | 3 | seq23 | AKLTNTTTASRCPTQG |
3 | 4 | ---KLTNTTTASRCPTQGE--- | 4 | seq3 | KLTNTTTASRCPTQGE |
4 | Consensus | LPLPWLPGADTQGSNWIQKET | - | - | - |
4 | 1 | LPLPWLPGADTQGSNW----- | 1 | seq13 | LPLPWLPGADTQGSNW |
4 | 2 | -PLPWLPGADTQGSNWIQKET | 2 | seq9 | PLPWLPGADTQGSNWIQKET |
5 | Consensus | ETQHGTIVIRVQYEGDGSPC | - | - | - |
5
5 |
1
2 |
ETQHGTIVIRVQYEGDGSPC
---HGTIVIRVQYEGDGSP- |
1
4 |
seq19
seq1 |
ETQHGTIVIRVQYEGDGSPC
HGTIVIRVQYEGDGSP |
6 | Singleton | GYGTVTMECSPRTGLD | - | seq15 | GYGTVTMECSPRTGLD |
7 | Singleton | LEHGSCVTTMAKNKPT | - | seq28 | LEHGSCVTTMAKNKPT |
8 | Singleton | VDRGWGNGCGLFGKGG | - | seq5 | VDRGWGNGCGLFGKGG |
Conservancy Analysis: IEDB tool with sequence identity criteria of 80% chooses homologous protein sets. In my research, we discovered that the epitopes PLPWHAGADTGTPHWNNKEA and GGFGSLGLDCEPRTGLDFSD length 20 mer had 100% Conservancy, but the epitope TDENRAKVEVTPNSPRAEAT length 20 mer has a low Conservancy of 40.74 percent and was eliminated from the vaccine selection procedure for ZIKV. The DENV epitopes LPLPWLPGADTQGSNW (16mer) and IGVEPGQLKLSWFKKGSSIG, VEPGQLKLSWFK-KGSSIGQM and IEAKLTNTTTASRCPTQGEP length 20 mer all have 100% conservation. Conservancy 97.30 percent for the remaining epitope ETQHGTIVIRVQYEGDGDGSPC with a length of 20 mer had been discarded.
TABLE 10: PREDICTIONS OF CONSERVANCY ANALYSIS
Sl. | Epitope legnth | Name of vectors | Epitope sequence | % of protein sequence matches | Maximum identity | Minimum identity |
1. | 20 | Zika | TDENRAKVEVTPNSPRAEAT | 40.74% (22/54) | 95.00% | 100.00% |
2. | 20 | Zika | PLPWHAGADTGTPHWNNKEA | 100.00% (54/54) | 100.00% | 100.00% |
3. | 20 | Zika | GGFGSLGLDCEPRTGLDFSD | 100.00% (54/54) | 100.00% | 100.00% |
4. | 20 | Dengue | IGVEPGQLKLSWFKKGSSIG | 100.00% (74/74 | 100.00% | 100.00% |
5. | 20 | Dengue | VEPGQLKLSWFKKGSSIGQM | 100.00% (74/74) | 100.00% | 100.00% |
6. | 20 | Dengue | IEAKLTNTTTASRCPTQGEP | 100.00% (74/74) | 100.00% | 100.00% |
7. | 16 | Dengue | LPLPWLPGADTQGSNW | 100.00% (74/74) | 100.00% | 100.00% |
8. | 20 | Dengue | ETQHGTIVIRVQYEGDGSPC | 97.30% (72/74 | 95.00% | 100.00% |
DISCUSSION: Defeat dengue viruses. The sudden outbreaks of Zika virus has brought additional difficulties to solve the dengue fever, the antibodies elicited by dengue vaccines also have the potential to augment ZIKV infection. However, like with any other scientific issue, the enormous worldwide outbreak of ZIKV has made it difficult to combat the infections.
Apart from forcing affected individuals to live with these neglected tropical illnesses, they also prevent children from attending school, jeopardise job security, raise the financial burden on nations owing to medical costs, and have a severe impact on developing countries' economies 37. When examining the whole ZIKV and DENV proteome, which contained B cell epitopes, we discovered consecutive amino acids 38. The adoption of the immunoinfomatic technique epitope cluster will open the door for more study into the creation of a precise ZIKV and DENV synthetic epitope vaccine. The epidemics of DV and ZV inspired much study into flavivirus virology, immunology and vaccinology. Epitope based vaccines provide specific immune responses without causing any adverse effects.
Research has very productive when B cells an emphasis on the E protein. Using different prediction method total 1529 B cell epitopes were predicted from all ZV and DV proteomes in this work. 27 and 24 consensus epitopes were separated for DV and ZV serotypes. The consensus epitopes identified in this work might be beneficial in developing a multipathogenic vaccine. Peptides with high antigenic and non-allergenic values were deemed to be strong B-cell epitopes using the VaxiJen server and the Allergen FP tool. 5 Alignment of DV and 3 Alignment of ZV had more Consensus epitopes.
Epitopes PLPWHAGADTGTPHWNNKEA and GGFGSLGL-DCEPRTGLDFSD had 100 percent conservation for ZIKV. Other DENV epitopes, including the 16-mer LPLPWLPGADTQGSNW and the 20-mer IGVEPGQLKLSWFKKGSSIG VEPGQLKLSWFKKGSSIGQM and IEAKLTNTTTASRCPTQGEP, all have 100% conservation.
CONCLUSION: Based on this knowledge, we provided possible ZIKV and DENV epitopes. In our research, the anticipated immunogenic epitopes PLPWHAGADTGTPHWNNKEA, GGFGSLGLDCEPRTGLDFSD of ZIKV and IGVEPGQLKLSWFKKGSSIG, VEPGQLKLSWFKKGSSIGQM and IEAKLTNTTTASRCPQGEP, LPLPWLPGADTQGSNW of DENV were the most Two-pronged methods combining human preventative vaccinations with vector blockade to stop transmission cycles are being used to combat mosquito-borne viruses.
ACKNOWLEDGEMENT: We would like to acknowledge Department of Biotechnology, Saroj Institute of Technology & Management, Lucknow, Uttar Pradesh, India, for the infrastructure support.
CONFLICT OF INTEREST: There are no conflicts of interest declared by the authors
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How to cite this article:
Dixit NK: Using an immunoinformatic approach, identification of B-cell envelope proteome for multipathogenic dengue and Zika viruses. Int J Pharm Sci & Res 2022; 13(8): 3208-23. doi: 10.13040/IJPSR.0975-8232.13(8).3208-23.
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Article Information
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3208-3223
1045 KB
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English
IJPSR
Neeraj Kumar Dixit
Department of Biotechnology, Saroj Institute of Technology & Management, Lucknow, Uttar Pradesh, India.
ndixitlip@gmail.com
14 December 2021
19 January 2022
28 April 2022
10.13040/IJPSR.0975-8232.13(8).3208-23
01 August 2022