Prediction of promiscuous multiepitope-based peptide vaccine against RdRp of rotavirus using immunoinformatics studies

ABSTRACT Rotavirus, a dsRNA virus in the Reoviridae family, shows a segmented genome. The VP1 gene encodes the RNA-dependent RNA polymerase (RdRp). This study aims to develop a multiepitope-based vaccine targeting RdRp using immunoinformatic approaches. In this study, 100 available nucleotide sequences of VP1-Rotavirus belonging to different strains across the world were retrieved from NCBI database. The selected sequences were aligned, and a global consensus sequence was developed by using CLC work bench. The study involved immunoinformatic approaches and molecular docking studies to reveal the promiscuous epitopes that can be eventually used as active vaccine candidates for Rotavirus. In total, 27 highly immunogenic, antigenic, and non-allergenic T-cell and B-cell epitopes were predicted for the Multiepitope vaccine (MEV) against rotavirus. It was also observed that MEV can prove to be effective worldwide due to its high population coverage, demonstrating the consistency of this vaccine. Moreover, there is a high docking interaction and immunological response with a binding score of −50.2 kcal/mol, suggesting the vaccine's efficacy. Toll-like receptors (TLRs) also suggest that the vaccine is physiologically and immunologically effective. Collectively, our data point to an effective MEV against rotavirus that can effectively reduce viral infections and improve the health status worldwide.

Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design

@#Malaria caused by Plasmodium knowlesi species has become a public health concern, especially in Malaysia. Plasmodium knowlesi parasite which originates from the macaque species, infects human through the bite of the Anopheles mosquitoes. Research on malaria vaccine has been a continuous effort to eradicate the malaria infection, yet there is no vaccine against P. knowlesi malaria to date. Apical membrane antigen 1 (AMA1) is a unique surface protein of all apicomplexan parasites that plays a crucial role in parasite-host cell invasion and thus has been a long-standing malaria vaccine candidate. The selection of protective epitopes in silico has led to significant advances in the design of the vaccine. The present study aimed to employ bioinformatics tools to predict the potential immunogenic B- and T-cell epitopes in designing malaria vaccine targeting P. knowlesi AMA1 (PkAMA1). B-cell epitopes were predicted using four bioinformatics tools, i.e., BepiPred, ABCpred, BcePred, and IEDB servers whereas T-cell epitopes were predicted using two bioinformatics servers, i.e., NetMHCpan4.1 and NetMHCIIpan-4.0 targeting human major histocompatibility complex (MHC) class I and class II molecules, respectively. The antigenicity of the selected epitopes computed by both B- and T-cell predictors were further analyzed using the VaxiJen server. The results demonstrated that PkAMA1 protein encompasses multi antigenic regions that have the potential for the development of multi-epitope vaccine. Two B- and T-cell epitopes consensus regions, i.e., NSGIRIDLGEDAEVGNSKYRIPAGKCP (codons 28-54) and KTHAASFVIAEDQNTSY RHPAVYDEKNKT (codons 122-150) at domain I (DI) of PkAMA1 were reported. Advancement of bioinformatics in characterization of the target protein may facilitate vaccine development especially in vaccine design which is costly and cumbersome process. Thus, comprehensive B-cell and T-cell epitope prediction of PkAMA1 offers a promising pipeline for the development and design of multi-epitope vaccine against P. knowlesi.

Prediction of T cell and B cell epitopes of the 22-, 47-, 56-, and 58-kDa proteins of Orientia tsutsugamushi

Objective: To predict B cell and T cell epitopes of 22-kDa, 47-kDa, 56-kDa and 58-kDa proteins. Methods: The sequences of 22-kDa, 47-kDa, 56-kDa and 58-kDa proteins which were derived from Orientia tsutsugamushi were analyzed by SOPMA, DNAstar, Bcepred, ABCpred, NetMHC, NetMHCⅡ and IEDB. The 58-kDa tertiary structure model was built by MODELLER9.17. Results: The 22-kDa B-cell epitopes were located at positions 194-200, 20-26 and 143-154, whereas the T-cell epitopes were located at positions 154-174, 95-107, 17-25 and 57-65. The 47-kDa protein B-cell epitopes were at positions 413-434, 150-161 and 283-322, whereas the T-cell epitopes were located at positions 129-147, 259-267, 412-420 and 80-88. The 56-kDa protein B-cell epitopes were at positions 167-173, 410-419 and 101-108, whereas the T-cell epitopes were located at positions 88-104, 429-439, 232-240 and 194-202. The 58-kDa protein B-cell epitopes were at positions 312-317, 540-548 and 35-55, whereas the T-cell epitopes were located at positions 415-434, 66-84 and 214-230. Conclusions: We identified candidate epitopes of 22-kDa, 47-kDa, 56-kDa and 58-kDa proteins from Orientia tsutsugamushi. In the case of 58-kDa, the dominant antigen is displayed on tertiary structure by homology modeling. Our findings will help target additional recombinant antigens with strong specificity, high sensitivity, and stable expression and will aid in their isolation and purification.

Prediction of T cell and B cell epitopes of the 22-, 47-, 56-, and 58-kDa proteins of Orientia tsutsugamushi

Objective: To predict B cell and T cell epitopes of 22-kDa, 47-kDa, 56-kDa and 58-kDa proteins. Methods: The sequences of 22-kDa, 47-kDa, 56-kDa and 58-kDa proteins which were derived from Orientia tsutsugamushi were analyzed by SOPMA, DNAstar, Bcepred, ABCpred, NetMHC, NetMHC II and IEDB. The 58-kDa tertiary structure model was built by MODELLER9.17. Results: The 22-kDa B-cell epitopes were located at positions 194-200, 20-26 and 143-154, whereas the T-cell epitopes were located at positions 154-174, 95-107, 17-25 and 57-65. The 47-kDa protein B-cell epitopes were at positions 413-434, 150-161 and 283-322, whereas the T-cell epitopes were located at positions 129-147, 259-267, 412-420 and 80-88. The 56-kDa protein B-cell epitopes were at positions 167-173, 410-419 and 101-108, whereas the T-cell epitopes were located at positions 88-104, 429-439, 232-240 and 194-202. The 58-kDa protein B-cell epitopes were at positions 312-317, 540-548 and 35-55, whereas the T-cell epitopes were located at positions 415-434, 66-84 and 214-230. Conclusions: We identified candidate epitopes of 22-kDa, 47-kDa, 56-kDa and 58-kDa proteins from Orientia tsutsugamushi. In the case of 58-kDa, the dominant antigen is displayed on tertiary structure by homology modeling. Our findings will help target additional recombinant antigens with strong specificity, high sensitivity, and stable expression and will aid in their isolation and purification.

Q fever vaccines / 中国人兽共患病学报

Q fever is a worldwide zoonosis and vaccination is the best measure to against its prevalence.Coxiella burnetii (Cb) is an obligate intracellular pathogen responsible for Q fever.Inactivated phase I Cb (Whole cell vaccine,WCV) can provide 100％ protection against Q fever,but its side effect of vaccination is strong.Phase I Cb is treated with chloroform-methanol or trichloroacetic acid and the chloroform-methanol residual (CMR) or the trichloroacetic acid extract (TCA) is used to substitute for WCV.Both CMR and TCA vaccine retain the protective efficient of WCV and significantly reduce the side effects.However,both CMR and TCA vaccine are required to isolate and purify Cb from chick embryos where Cb grows in a biosafety laboratory with the complex procedures.In recent 10 years,the scientists have investigated from protective antigens to CD4+ and CD8+ T cell epitopes of Cb,expecting that the genes encoding the T cell epitopes express highly and induce an efficient protection against Q fever in bodies.

Prediction of promiscuous T cell epitopes in RNA dependent RNA polymerase of Chikungunya virus

Objective To explore RNA dependent RNA polymerase of Chikungunya virus (CHIKV) and develop T cell based epitopes with high antigenicity and good binding affinity for the human leukocyte antigen (HLA) classes as targets for epitopes based CHIKV vaccine. Methods In this study we downloaded 371 non-structural protein 4 protein sequences of CHIKV belonging to different regions of the world from the US National Institute of Allergy and Infectious Diseases (NIAID) virus pathogen resource database. All the sequences were aligned by using CLUSTALW software and a consensus sequence was developed by using Uni Pro U Gene Software version 1.2.1. Propred I and Propred software were used to predict HLA I and HLA II binding promiscuous epitopes from the consensus sequence of non-structural protein 4 protein. The predicted epitopes were analyzed to determine their antigenicity through Vaxijen server version 2.0. All the HLA I binding epitopes were scanned to determine their immunogenic potential through the Immune Epitope Database (IEDB). All the predicted epitopes of our study were fed to IEDB database to determine whether they had been tested earlier. Results Twenty two HLA class II epitopes and eight HLA class I epitopes were predicted. The promiscuous epitopes WMNMEVKII at position 486–494 and VRRLNAVLL at 331–339 were found to bind with 37 and 36 of the 51 HLA class II alleles respectively. Epitope MANRSRYQS at position 58–66 and epitopes YQSRKVENM at positions 64–72 were predicted to bind with 12 and 9 HLA II alleles with antigenicity scores of 0.754 9 and 1.013 0 respectively. Epitope YSPPINVRL was predicted to bind 18 HLA I alleles and its antigenicity score was 1.425 9 and immunogenicity score was 0.173 83. This epitope is very useful in the preparation of a universal vaccine against CHIKV infection. Conclusions Epitopes reported in this study showed promiscuity, antigenicity as well as good binding affinity for the HLA classes. These epitopes will provide the baseline for development of efficacious vaccine for CHIKV.

Prediction of promiscuous T cell epitopes in RNA dependent RNA polymerase of Chikungunya virus

OBJECTIVE@#To explore RNA dependent RNA polymerase of Chikungunya virus (CHIKV) and develop T cell based epitopes with high antigenicity and good binding affinity for the human leukocyte antigen (HLA) classes as targets for epitopes based CHIKV vaccine.@*METHODS@#In this study we downloaded 371 non-structural protein 4 protein sequences of CHIKV belonging to different regions of the world from the US National Institute of Allergy and Infectious Diseases (NIAID) virus pathogen resource database. All the sequences were aligned by using CLUSTALW software and a consensus sequence was developed by using Uni Pro U Gene Software version 1.2.1. Propred I and Propred software were used to predict HLA I and HLA II binding promiscuous epitopes from the consensus sequence of non-structural protein 4 protein. The predicted epitopes were analyzed to determine their antigenicity through Vaxijen server version 2.0. All the HLA I binding epitopes were scanned to determine their immunogenic potential through the Immune Epitope Database (IEDB). All the predicted epitopes of our study were fed to IEDB database to determine whether they had been tested earlier.@*RESULTS@#Twenty two HLA class II epitopes and eight HLA class I epitopes were predicted. The promiscuous epitopes WMNMEVKII at position 486-494 and VRRLNAVLL at 331-339 were found to bind with 37 and 36 of the 51 HLA class II alleles respectively. Epitope MANRSRYQS at position 58-66 and epitopes YQSRKVENM at positions 64-72 were predicted to bind with 12 and 9 HLA II alleles with antigenicity scores of 0.754 9 and 1.013 0 respectively. Epitope YSPPINVRL was predicted to bind 18 HLA I alleles and its antigenicity score was 1.425 9 and immunogenicity score was 0.173 83. This epitope is very useful in the preparation of a universal vaccine against CHIKV infection.@*CONCLUSIONS@#Epitopes reported in this study showed promiscuity, antigenicity as well as good binding affinity for the HLA classes. These epitopes will provide the baseline for development of efficacious vaccine for CHIKV.

Prediction of promiscuous T-cell epitopes in the Zika virus polyprotein: An in silico approach

Objective To predict immunogenic promiscuous T cell epitopes from the polyprotein of the Zika virus using a range of bioinformatics tools. To date, no epitope data are available for the Zika virus in the IEDB database. Methods We retrieved nearly 54 full length polyprotein sequences of the Zika virus from the NCBI database belonging to different outbreaks. A consensus sequence was then used to predict the promiscuous T cell epitopes that bind MHC 1 and MHC II alleles using PorPred1 and ProPred immunoinformatic algorithms respectively. The antigenicity predicted score was also calculated for each predicted epitope using the VaxiJen 2.0 tool. Results By using ProPred1, 23 antigenic epitopes for HLA class I and 48 antigenic epitopes for HLA class II were predicted from the consensus polyprotein sequence of Zika virus. The greatest number of MHC class I binding epitopes were projected within the NS5 (21%), followed by Envelope (17%). For MHC class II, greatest number of predicted epitopes were in NS5 (19%) followed by the Envelope, NS1 and NS2 (17% each). A variety of epitopes with good binding affinity, promiscuity and antigenicity were predicted for both the HLA classes. Conclusion The predicted conserved promiscuous T-cell epitopes examined in this study were reported for the first time and will contribute to the imminent design of Zika virus vaccine candidates, which will be able to induce a broad range of immune responses in a heterogeneous HLA population. However, our results can be verified and employed in future efficacious vaccine formulations only after successful experimental studies.

Prediction of promiscuous T-cell epitopes in the Zika virus polyprotein: An in silico approach

OBJECTIVE@#To predict immunogenic promiscuous T cell epitopes from the polyprotein of the Zika virus using a range of bioinformatics tools. To date, no epitope data are available for the Zika virus in the IEDB database.@*METHODS@#We retrieved nearly 54 full length polyprotein sequences of the Zika virus from the NCBI database belonging to different outbreaks. A consensus sequence was then used to predict the promiscuous T cell epitopes that bind MHC 1 and MHC II alleles using PorPred1 and ProPred immunoinformatic algorithms respectively. The antigenicity predicted score was also calculated for each predicted epitope using the VaxiJen 2.0 tool.@*RESULTS@#By using ProPred1, 23 antigenic epitopes for HLA class I and 48 antigenic epitopes for HLA class II were predicted from the consensus polyprotein sequence of Zika virus. The greatest number of MHC class I binding epitopes were projected within the NS5 (21%), followed by Envelope (17%). For MHC class II, greatest number of predicted epitopes were in NS5 (19%) followed by the Envelope, NS1 and NS2 (17% each). A variety of epitopes with good binding affinity, promiscuity and antigenicity were predicted for both the HLA classes.@*CONCLUSION@#The predicted conserved promiscuous T-cell epitopes examined in this study were reported for the first time and will contribute to the imminent design of Zika virus vaccine candidates, which will be able to induce a broad range of immune responses in a heterogeneous HLA population. However, our results can be verified and employed in future efficacious vaccine formulations only after successful experimental studies.