Computational characterization of Plasmodium falciparum proteomic data for screening of potential vaccine candidates

Revisiting the dimensions of universal vaccine with special focus on COVID-19: Efficacy versus methods of designing

Even though the use of SARS-CoV-2 vaccines during the COVID-19 pandemic showed unprecedented success in a short time, it also exposed a flaw in the current vaccine design strategy to offer broad protection against emerging variants of concern. However, developing broad-spectrum vaccines is still a challenge for immunologists. The development of universal vaccines against emerging pathogens and their variants appears to be a practical solution to mitigate the economic and physical effects of the pandemic on society. Very few reports are available to explain the basic concept of universal vaccine design and development. This review provides an overview of the innate and adaptive immune responses generated against vaccination and essential insight into immune mechanisms helpful in designing universal vaccines targeting influenza viruses and coronaviruses. In addition, the characteristics, safety, and factors affecting the efficacy of universal vaccines have been discussed. Furthermore, several advancements in methods worthy of designing universal vaccines are described, including chimeric immunogens, heterologous prime-boost vaccines, reverse vaccinology, structure-based antigen design, pan-reactive antibody vaccines, conserved neutralizing epitope-based vaccines, mosaic nanoparticle-based vaccines, etc. In addition to the several advantages, significant potential constraints, such as defocusing the immune response and subdominance, are also discussed.

A cutting-edge immunoinformatics approach for design of multi-epitope oral vaccine against dreadful human malaria

Human malaria is a pathogenic disease mainly caused by Plasmodium falciparum, which was responsible for about 405,000 deaths globally in the year 2018. To date, several vaccine candidates have been evaluated for prevention, which failed to produce optimal output at various preclinical/clinical stages. This study is based on designing of polypeptide vaccines (PVs) against human malaria that cover almost all stages of life-cycle of Plasmodium and for the same 5 genome derived predicted antigenic proteins (GDPAP) have been used. For the development of a multi-immune inducer, 15 PVs were initially designed using T-cell epitope ensemble, which covered >99% human population as well as linear B-cell epitopes with or without adjuvants. The immune simulation of PVs showed higher levels of T-cell and B-cell activities compared to positive and negative vaccine controls. Furthermore, in silico cloning of PVs and codon optimization followed by enhanced expression within Lactococcus lactis host system was also explored. Although, the study has sound theoretical and in silico findings, the in vitro/in vivo evaluation seems imperative to warrant the immunogenicity and safety of PVs towards management of P. falciparum infection in the future.

Designing of precise vaccine construct against visceral leishmaniasis through predicted epitope ensemble: A contemporary approach

Visceral leishmaniasis (VL) caused by Leishmania donovani is a fatal parasitic disease affecting primarily the poor population in endemic countries. Increasing number of deaths as well as resistant to existing drugs necessitates the development of an effective vaccine for successful treatment of VL. The present study employed a combinatorial approach for designing monomer vaccine construct against L. donovani by applying forecasted B- and T- cell epitopes from 4 genome derived antigenic proteins having secretory signal peptides and glycophosphatidylinositol (GPI) anchors with ≤ 1 transmembrane helix. The forecasted population coverage of chosen T cell epitope ensemble (combined HLA class I and II) cover 99.14 % of world-wide human population. The predicted 3D structure of vaccine constructs (VC1/VC2) were modeled using homology modeling approach and docked to innate immune receptors TLR-2 and TLR-4 with respective docking energies -1231.4/-910.3 and -1119.4/-1476 kcal/mol. Overall, the aforementioned designed vaccine constructs were found appropriate for including in self-assembly protein nanoparticles (SAPN) for further study in developing cutting-edge precision vaccine against VL in short duration with cost-effective manner.

Genome based screening of epitope ensemble vaccine candidates against dreadful visceral leishmaniasis using immunoinformatics approach

Visceral leishmaniasis (VL) is a dreadful protozoan disease caused by Leishmania donovani that severely affects huge populations in tropical and sub-tropical regions. The present study reports an unbiased genome based screening of 4 potent vaccine antigens against 8023 L. donovani proteins by following the criteria of presence of signal peptides, GPI-anchors and ≤1 transmembrane helix using advanced bioinformatics tools viz. SignalP4.0, PredGPI and TMHMM2.0, respectively. They are designated as genome based predicted signal peptide antigens (GBPSPA). The antigenicity/immunogenicity of chosen vaccine antigens (GBPSPA) with 4 randomly selected known leishmanial antigens (RSKLA) was compared by simulation study employing C-ImmSim software for human immune responses. This revealed better immunological responses. These antigens were further evaluated for the presence of B- and T-cell epitopes using immune epitope database (IEDB) based recommended consensus method of MHC class I and II tools. It was found to forecast CD4⁺ and CD8⁺ T-cell responses in genetically diverse human population worldwide as well as different endemic regions through IEDB based predicted population coverage (PPC) analysis tool. The worldwide percent PPC value of combined (HLA class I and II) epitope ensemble forecast was found to be 99.98, 99.96 and 50.04, respectively for GBPSPA, RSKLA and experimentally known epitopes (EKE) of L. donovani. Therefore, these potential antigens/epitope ensembles could favor the design of prospective and novel vaccine constructs like self-assembled epitopes as nano vaccine formulations against VL. Overall, the present study will serve as a model framework that might improve the effectiveness of designed vaccine against L. donovani and other related pathogens.

In silico rational design of a novel tetra-epitope tetanus vaccine with complete population coverage using developed immunoinformatics and surface epitope mapping approaches

Presentation of many unwanted epitopes within tetanus toxoid vaccine to lymphocyte clones may lead to production of many unwanted antibodies. Moreover an ideal vaccine must cover all individuals in a population that is dependent to the kinds of human leukocyte antigen alleles. Concerning these issues, our study was aimed to in silico design of a multi-epitope tetanus vaccine (METV) in order to improve population coverage and protectivity of tetanus vaccine as well as reduction of complications. Concerning these issues, a novel rational filtration was implemented to design a novel METV using immunoinformatics and surface epitope mapping approaches. Prediction of epitopes for tetanus toxin was performed in the candidate country in which the frequency had been gathered from almost all geographical distributions. The most strong binder epitopes for major histocompatibility complex class II were selected and among them the surface epitopes of native toxin were selected. The population coverage of the selected epitopes was estimated. The final candidate epitopes had highly population coverage. Molecular docking was performed to prediction of binding affinity of our candidate epitopes to the HLA-DRB1 alleles. At first, 680 strong binder epitopes were predicted. Among them 11 epitopes were selected. Finally, 4 epitopes had the most population coverage and suggested as a tetra-epitope tetanus vaccine. 99.41% of inessential strong binders were deleted using our tree steps filtration. HLA-DP had the most roles in epitope presentation. Molecular docking analysis proved the strong binding affinity of candidate epitopes to the HLA-DRB1 alleles. In conclusion, we theoretically reduced 99.41% of unwanted antibodies using our novel filtration strategies. Our tetra-epitope tetanus vaccine showed 100% population coverage in the candidate country. Furthermore, it was demonstrated that HLA-DP and HLA-DQ had more potential in epitope presentation in comparison to HLA-DRB1.

Exploitation of reverse vaccinology and immunoinformatics as promising platform for genome-wide screening of new effective vaccine candidates against Plasmodium falciparum

Background

In the current scenario, designing of world-wide effective malaria vaccine against Plasmodium falciparum remain challenging despite the significant progress has been made in last few decades. Conventional vaccinology (isolate, inactivate and inject) approaches are time consuming, laborious and expensive; therefore, the use of computational vaccinology tools are imperative, which can facilitate the design of new and promising vaccine candidates.

Results

In current investigation, initially 5548 proteins of P. falciparum genome were carefully chosen for the incidence of signal peptide/ anchor using SignalP4.0 tool that resulted into 640 surface linked proteins (SLP). Out of these SLP, only 17 were predicted to contain GPI-anchors using PredGPI tool in which further 5 proteins were considered as malarial antigenic adhesins by MAAP and VaxiJen programs, respectively. In the subsequent step, T cell epitopes of 5 genome derived predicted antigenic adhesins (GDPAA) and 5 randomly selected known malarial adhesins (RSKMA) were analysed employing MHC class I and II tools of IEDB analysis resource. Finally, VaxiJen scored T cell epitopes from each antigen were considered for prediction of population coverage (PPC) analysis in the world-wide population including malaria endemic regions. The validation of the present in silico strategy was carried out by comparing the PPC of combined (MHC class I and II) predicted epitope ensemble among GDPAA (99.97%), RSKMA (99.90%) and experimentally known epitopes (EKE) of P. falciparum (97.72%) pertaining to world-wide human population.

Conclusions

The present study systematically screened 5 potential protective antigens from P. falciparum genome using bioinformatics tools. Interestingly, these GDPAA, RSKMA and EKE of P. falciparum epitope ensembles forecasted to contain highly promiscuous T cell epitopes, which are potentially effective for most of the world-wide human population with malaria endemic regions. Therefore, these epitope ensembles could be considered in near future for novel and significantly effective vaccine candidate against malaria.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2482-x) contains supplementary material, which is available to authorized users.

Conserved Binding Regions Provide the Clue for Peptide-Based Vaccine Development: A Chemical Perspective

Synthetic peptides have become invaluable biomedical research and medicinal chemistry tools for studying functional roles, i.e., binding or proteolytic activity, naturally-occurring regions’ immunogenicity in proteins and developing therapeutic agents and vaccines. Synthetic peptides can mimic protein sites; their structure and function can be easily modulated by specific amino acid replacement. They have major advantages, i.e., they are cheap, easily-produced and chemically stable, lack infectious and secondary adverse reactions and can induce immune responses via T- and B-cell epitopes. Our group has previously shown that using synthetic peptides and adopting a functional approach has led to identifying Plasmodium falciparumconserved regions binding to host cells. Conserved high activity binding peptides’ (cHABPs) physicochemical, structural and immunological characteristics have been taken into account for properly modifying and converting them into highly immunogenic, protection-inducing peptides (mHABPs) in the experimental Aotus monkey model. This article describes stereo–electron and topochemical characteristics regarding major histocompatibility complex (MHC)-mHABP-T-cell receptor (TCR) complex formation. Some mHABPs in this complex inducing long-lasting, protective immunity have been named immune protection-inducing protein structures (IMPIPS), forming the subunit components in chemically synthesized vaccines. This manuscript summarizes this particular field and adds our recent findings concerning intramolecular interactions (H-bonds or π-interactions) enabling proper IMPIPS structure as well as the peripheral flanking residues (PFR) to stabilize the MHCII-IMPIPS-TCR interaction, aimed at inducing long-lasting, protective immunological memory.

Genome-wide identification of novel vaccine candidates for Plasmodium falciparum malaria using integrative bioinformatics approaches

In spite of decades of malaria research and clinical trials, a fully effective and long-lasting preventive vaccine remains elusive. In the present study, 5370 proteins of Plasmodium falciparum genome were screened for the presence of signal peptide/anchor and GPI anchor motifs. Out of 45 screened surface-associated proteins, 22 were consensually predicted as antigens and had no orthologs in human and mouse except circumsporozoite protein (PF3D7_0304600). Among 22 proteins, 19 were identified as new antigens. In the next step, a total of 4944 peptides were predicted as CD8+ T cell epitopes from 22 probable antigens. Of these, the highest scoring 262 epitopes from each antigen were taken for optimization study in the malaria-endemic regions which covered a broad human population (~93.95%). The predicted epitope 13ILFYFFLWV21 of antigen 6-cysteine (PF3D7_1346800) was binding to the HLA-A*0201 allele with the highest fraction (26%) of immunogenicity in the target populations of North-East Asia, South-East Asia, and sub-Saharan Africa. Therefore, these epitopes are proposed to be favored in vaccine designs against malaria.

Genome-Wide Prediction of Vaccine Candidates for Leishmania major: An Integrated Approach

Despite the wealth of information regarding genetics of the causative parasite and experimental immunology of the cutaneous leishmaniasis, there is currently no licensed vaccine against it. In the current study, a two-level data mining strategy was employed, to screen the Leishmania major genome for promising vaccine candidates. First, we screened a set of 25 potential antigens from 8312 protein coding sequences, based on presence of signal peptides, GPI anchors, and consensus antigenicity predictions. Second, we conducted a comprehensive immunogenic analysis of the 25 antigens based on epitopes predicted by NetCTL tool. Interestingly, results revealed that candidate antigen number 1 (LmjF.03.0550) had greater number of potential T cell epitopes, as compared to five well-characterized control antigens (CSP-Plasmodium falciparum, M1 and NP-Influenza A virus, core protein-Hepatitis B virus, and PSTA1-Mycobacterium tuberculosis). In order to determine an optimal set of epitopes among the highest scoring predicted epitopes, the OptiTope tool was employed for populations susceptible to cutaneous leishmaniasis. The epitope (127SLWSLLAGV) from antigen number 1, found to bind with the most prevalent allele HLA-A⁎0201 (25% frequency in Southwest Asia), was predicted as most immunogenic for all the target populations. Thus, our study reasserts the potential of genome-wide screening of pathogen antigens and epitopes, for identification of promising vaccine candidates.

Major histocompatibility complex linked databases and prediction tools for designing vaccines

Presently, the major histocompatibility complex (MHC) is receiving considerable interest owing to its remarkable role in antigen presentation and vaccine design. The specific databases and prediction approaches related to MHC sequences, structures and binding/nonbinding peptides have been aggressively developed in the past two decades with their own benchmarks and standards. Before using these databases and prediction tools, it is important to analyze why and how the tools are constructed along with their strengths and limitations. The current review presents insights into web-based immunological bioinformatics resources that include searchable databases of MHC sequences, epitopes and prediction tools that are linked to MHC based vaccine design, including population coverage analysis. In T cell epitope forecasts, MHC class I binding predictions are very accurate for most of the identified MHC alleles. However, these predictions could be further improved by integrating proteasome cleavage (in conjugation with transporter associated with antigen processing (TAP) binding) prediction, as well as T cell receptor binding prediction. On the other hand, MHC class II restricted epitope predictions display relatively low accuracy compared to MHC class I. To date, pan-specific tools have been developed, which not only deliver significantly improved predictions in terms of accuracy, but also in terms of the coverage of MHC alleles and supertypes. In addition, structural modeling and simulation systems for peptide-MHC complexes enable the molecular-level investigation of immune processes. Finally, epitope prediction tools, and their assessments and guidelines, have been presented to immunologist for the design of novel vaccine and diagnostics.

Computational screening and characterization of putative vaccine candidates of Plasmodium vivax

Plasmodium vivax is the most prevalent species of malaria affecting millions of people annually worldwide and demands effective interventions to develop a successful vaccine. In this milieu, we have dedicated noteworthy efforts to characterize the proteome of P. vivax to give a lead for the epitope-based vaccine development. Membrane proteins of P. vivax were collected from SWISS PROT database and 10 antigenic proteins were identified among them by in silico analysis using multiple servers. T-cell and B-cell epitopes were identified and their immunity was assessed. Their ability to trigger humoral and cell-mediated responses was determined. Three dimensional models were constructed for the antigenic proteins using Modeller, Phyre2, and Modloop tools and their quality was validated using PROCHECK and ProSA-web validation servers. Further, the binding affinity and molecular interactions of these antigenic proteins were characterized by performing protein-protein docking against transmission-blocking anti-malaria antibody Fab2A8 (PDB ID: 3S62) using Z-dock module of Discovery Studio 4.0. The presence of potential B & T-cell epitopes, major histocompatibility complex-binding sites, and their efficient interactions with Fab2A8 antibody suggests the use of predicted antigenic proteins for the construction of multi-epitope peptide vaccine against P. vivax.

Characterization of Plasmodium falciparum Proteome at Asexual Blood Stages for Screening of Effective Vaccine Candidates: An Immunoinformatics Approach

Malaria is a complex parasitic disease that is currently causing great concerns globally owing to the resistance to antimalarial drugs and lack of an effective vaccine. The present study involves the characterization of extracellular secretory proteins as vaccine candidates derived from proteome analysis of Plasmodium falciparum at asexual blood stages of malaria. Among the screened 32 proteins, 31 were predicted as antigens by the VaxiJen program, and 26 proteins had less than two transmembrane spanning regions predicted using the THMMM program. Moreover, 10 and 5 proteins were predicted to contain secretory signals by SignalP and TargetP, respectively. T-cell epitope prediction using MULTIPRED2 and NetCTL programs revealed that most of the predicted antigens are immunogenic and contain more than 10% supertype and 5% promiscuous epitopes of HLA-A, -B, or -DR. We anticipate that T-cell immune responses against asexual blood stages of Plasmodium are dispersed on a relatively large number of parasite antigens. This is the first report, to the best of our knowledge, offering new insights, at the proteome level, for the putative screening of effective vaccine candidates against the malaria pathogen. The findings also suggest new ways forward for the modern omics-guided vaccine target discovery using reverse vaccinology.

Imaging of the skeletal muscle metastases

Preclinical Research

Copyright 2011 Wiley-Liss, Inc., A Wiley CompanyThis article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

Omics technologies include genomics, transcriptomics, proteomics, metabolomics, and immunomics. These technologies have been used in vaccine research, which can be summarized using the term “vaccinomics.” These omics technologies combined with advanced bioinformatics analysis form the core of “systems vaccinology.” Omics technologies provide powerful methods in vaccine target identification. The genomics‐based reverse vaccinology starts with predicting vaccine protein candidates through in silico bioinformatics analysis of genome sequences. The VIOLIN Vaxign vaccine design program (http://www.violinet.org/vaxign) is the first web‐based vaccine target prediction software based on the reverse vaccinology strategy. Systematic transcriptomics and proteomics analyses facilitate rational vaccine target identification by detesting genome‐wide gene expression profiles. Immunomics is the study of the set of antigens recognized by host immune systems and has also been used for efficient vaccine target prediction. With the large amount of omics data available, it is necessary to integrate various vaccine data using ontologies, including the Gene Ontology (GO) and Vaccine Ontology (VO), for more efficient vaccine target prediction and assessment. All these omics technologies combined with advanced bioinformatics analysis methods for a systems biology‐based vaccine target prediction strategy. This article reviews the various omics technologies and how they can be used in vaccine target identification.

Designing the next generation of vaccines for global public health

Vaccine research and development are experiencing a renaissance of interest from the global scientific community. There are four major reasons for this: (1) the lack of efficacious treatment for many devastating infections; (2) the emergence of multidrug resistant bacteria; (3) the need for improving the safety of the more traditional licensed vaccines; and finally, (4) the great promise for innovative vaccine design and research with convergence of omics sciences, such as genomics, proteomics, immunomics, and vaccinology. Our first project based on omics was initiated in 2000 and was termed reverse vaccinology. At that time, antigen identification was mainly based on bioinformatic analysis of a singular genome. Since then, omics-guided approaches have been applied to its full potential in several proof-of-concept studies in the industry, with the first reverse vaccinology-derived vaccine now in late stage clinical trials and several vaccines developed by omics in preclinical studies. In the meantime, vaccine discovery and development has been further improved with the support of proteomics, functional genomics, comparative genomics, structural biology, and most recently vaccinomics. We illustrate in this review how omics biotechnologies and integrative biology are expected to accelerate the identification of vaccine candidates against difficult pathogens for which traditional vaccine development has thus far been failing, and how research will provide safer vaccines and improved formulations for immunocompromised patients in the near future. Finally, we present a discussion to situate omics-guided rational vaccine design in the broader context of global public health and how it can benefit citizens in both developed and developing countries.