key: cord-0036180-to54sbmp
authors: Kangueane, Pandjassarame; Sowmya, Gopichandran; Anupriya, Sadhasivam; Dangeti, Sandeep Raja; Mathura, Venkatrajan S.; Sakharkar, Meena K.
title: Short Peptide Vaccine Design and Development: Promises and Challenges
date: 2015-05-12
journal: Global Virology I - Identifying and Investigating Viral Diseases
DOI: 10.1007/978-1-4939-2410-3_1
sha: d727c328f28787cdf5baeccc04fe00062c17869d
doc_id: 36180
cord_uid: to54sbmp

Vaccine development for viral diseases is a challenge where subunit vaccines are often ineffective. Therefore, the need for alternative solutions is crucial. Thus, short peptide vaccine candidates promise effective answers under such circumstances. Short peptide vaccine candidates are linear T-cell epitopes (antigenic determinants that are recognized by the immune system) that specifically function by binding human leukocyte antigen (HLA) alleles of different ethnicities (including Black, Caucasian, Oriental, Hispanic, Pacific Islander, American Indian, Australian aboriginal, and mixed ethnicities). The population-specific allele-level HLA sequence data in the public IMGT/HLA database contains approximately 12542 nomenclature defined class I (9437) and class II (3105) HLA alleles as of March 2015 present in several ethnic populations. The bottleneck in short peptide vaccine design and development is HLA polymorphism on the one hand and viral diversity on the other hand. Hence, a crucial step in its design and development is HLA allele-specific binding of short antigen peptides. This is usually combinatorial and computationally labor intensive. Mathematical models utilizing structure-defined pockets are currently available for class I and class II HLA-peptide-binding peptides. Frameworks have been developed to design protocols to identify the most feasible short peptide cocktails as vaccine candidates with superantigen properties among known HLA supertypes. This approach is a promising solution to develop new viral vaccines given the current advancement in T-cell immuno-informatics, yet challenging in terms of prediction efficiency and protocol development.

The types of approved viral vaccines include live attenuated viruses, killed/inactivated viruses, and conjugate/subunits. However, these types of vaccine technologies may prove unsuitable against some viruses. In some cases, there is interest in the development of short peptide vaccines to fi ll the gaps. For example, the use of live attenuated HIV-1/AIDS vaccines is not as yet approved due to safety concerns [ 1 ] . There are several subunit vaccines under consideration and evaluation. However, one of these, the NIAID and Merck Co.-sponsored 2004 STEP (HVTN 502 or Merck V520-023) trial using three recombinant adenovirus-5 (rAD5) vectors containing HIV-1 genes Ad5-gag, Ad5-pol, and Ad5-Nef, did not show promising results [ 2 ] . This has led to the development of a multifaceted strategy for HIV-1/AIDS vaccine development. However, encouraging results were observed with four priming injections of a recombinant canary pox vector (ALVAC-HIV) and two booster injections of gp120 subunit (AIDSVAX-B/E) in a community-based, randomized, multicenter, double-blind, placebo-controlled effi cacy trial (NCT00223080) in Thailand [ 3 ] . The main concern following this study was that this vaccine did not affect the degree of viremia or the CD4 T-cell count in patients who later seroconverted. Further studies indicated that the challenges with the development of an HIV-1/AIDS vaccine are viral diversity and host-virus molecular mimicry [ 4 -6 ] . Nonetheless, there is considerable amount of interest to develop gp160 (gp120-gp41 complex) TRIMER envelope (ENV) protein as a potential vaccine candidate [ 4 ] .

The production of an HIV-1 ENV spike protein trimer complex is nontrivial due to protein size, protein type, sequence composition, and residue charge polarity. Therefore, the need for the consideration of alternative approaches for vaccine development such as T-cell-based HLA-specifi c short peptide vaccines is promising [ 6 , 7 ] . The LANL HIV molecular immunology database provides comprehensive information on all known T-cell epitopes in the literature [ 8 ] . Thus, these resources in combination with other predictive advancements described in this chapter are collectively useful for the design, development, evaluation, and validation of short peptide vaccine candidates.

A structural dataset of complexes for class I HLA-peptide ( 

The peptide-binding grooves of both class I HLA ( Fig. 1.1a ) and class II HLA ( Fig. 1.1c ) molecules were superimposed using the molecular overlay option in the Discovery Studio software from Accelrys ® [ 10 ].

HLA-bound peptides in the groove of both class I HLA ( Fig. 1.1b ) and class II HLA ( Fig. 1 .1d ) molecules were overlaid using the molecular overlay option in the Discovery Studio software from Accelrys ® [ 10 ].

Accessible surface area (ASA) was calculated using the WINDOWS software Surface Racer [ 12 ] with Lee and Richard implementation [ 13 ] . A probe radius of 1.4 Å was used for ASA calculation.

Relative binding measure (RBM) is defi ned as the percentage ASA Å 2 of residues in the peptide at the corresponding positions buried as a result of binding with the HLA groove. This is the percentage change in ASA (ΔASA) of the position-specifi c peptide residues upon complex formation with the HLA groove ( Fig. 1.2 ). 

The rate-limiting step in T-cell epitope design is allele-specifi c HLA-peptide binding prediction. The number of known HLA alleles is over 12542 in number as of March 2015 at the IMGT/HLA database [ 11 ] . Hence, a number of methods have been formulated so far and optimized for HLA-peptide binding prediction during the last two decades. Structural information on HLA-peptide complexes has increased our understanding of their binding patterns (Tables 1.1 and 1.2 ) . The HLA-binding groove is structurally similar among class I (Fig. 1.1a ) and class II ( Fig. 1.1b ) alleles. The class I (Fig. 1.1c ) and class II (Fig. 1.1d ) bound peptides do not show an identical binding pattern at the groove. A detailed illustration of peptide binding patterns (Fig. 1.2 ) at the groove of class I and class II alleles provides valuable insights using mean and deviation profi les ( Fig. 1.3 ) . Tables 1.1 and 1 .2 ). The peptide lengthwise distribution of the binding pattern is shown as relative binding measure using change in solvent-accessible surface area upon complex formation with the HLA groove A comprehensive description of HLA-peptide binding prediction is documented [ 14 , 15 ] . Lee and McConnell [ 16 ] proposed a general model of invariant chain association with class II HLA using the side-chain packing technique on a known structural template complex with self-consistent ensemble optimization (SCEO) [ 17 , 18 ] using the program CARA in the molecular visualization/modeling software LOOK (Molecular Application Group (1995), Palo Alto, CA) [ 16 , 19 ] . This was an important development in the fi eld and the approach was extended to a large dataset of known HLA-binding peptides. Kangueane et al. [ 20 ] collected over 126 class I peptides with known IC 50 values from literature with defi ned HLA allele specifi city. These peptides were modeled using available templates for a large-scale assessment of peptide binding to defi ned HLA alleles. Thus, a structural framework was estab- Fig. 1.3 The mean peptide binding pattern with standard deviation (SD) at the groove is illustrated as function of residue position for class I and class II alleles using a dataset (Tables 1.1 and 1.2 ) of HLA-peptide complexes (67 class I and 16 class II) retrieved from protein databank (PDB). This provides insight into the understanding of the nature of peptide binding at the groove towards the design of an effective T-cell epitope candidate lished for discriminating allele-specifi c binders from non-binders using rules derived from a dataset of HLA-peptide complexes. This procedure was promising.

An extended dataset of class 1 and class 2 complexes were manually created, curated, and analyzed for insights into HLA-peptide binding patterns at the groove [ 21 ] . These studies lead to a detailed analysis of the HLA-peptide interface at the groove and the importance of peptide side chain and backbone atomic interactions were realized [ 22 ] . Meanwhile, the amount of structural data on HLA-peptide complexes was increasing in size leading to the development of an online database [ 23 ] . Thus, information gleaned from HLA-peptide structural complexes helped to identify common pockets among alleles in the binding groove and provided insights into functional overlap among them [ 24 ] . The need for a simple, robust, generic HLA-peptide binding prediction was evident. Therefore, a model was formulated by defi ning virtual pockets at the peptide-binding groove using information gleaned from a structural dataset of HLA-peptide complexes [ 25 ] . The model (average accuracy of 60 %) was superior because of its application to any given class I allele whose sequence is clearly defi ned. The model (53 % accuracy) was then extended for class II prediction using a class II-specifi c HLA-peptide structural dataset [ 26 ] .

The techniques thus far established are highly promising towards short peptide vaccine design and development [ 27 , 28 ] . Nonetheless, it was observed that alleles are covered within few HLA supertypes, where different members of a supertype bind similar peptides, yet exhibiting distinct repertoires [ 29 ] . These principles led to the development of frameworks to group alleles into HLA supertypes [ 30 , 31 ] , understand their structural basis [ 32 ] , and cluster alleles based on electrostatic potential at the groove [ 33 ] . These observations should aid in the design of peptide vaccine candidates for viruses including HIV/AIDS [ 5 , 6 ] . Further, for example, the importance of protein modifi cations to enhance HIV-1 ENV trimer spike protein vaccine across multiple clades, blood, and brain is discussed [ 4 ] . 

The design and development of short peptide cocktail vaccines is a possibility in the near future. This function on the principle of short epitopes developed through the binding of CD8+/CD4+-specifi c HLA alleles. HLA molecules are specifi c within ethnic populations and are polymorphic with more than 12542 known alleles as of March 2015. Thus, the binding of short peptide antigens to HLA alleles is rate limiting yet specifi c, with high sensitivity, while producing T-cell-mediated immune responses. Our understanding of this specifi c peptide binding to HLA alleles has improved using known HLA-peptide complexes. There is a search for superantigen peptides covering major HLA supertypes. Thus, peptide-binding predictions with large coverage, accuracy, sensitivity, and specifi city are essential for vaccine candidate design and development. It should be noted that available HLA-peptide binding prediction methods are highly promising in these directions.

Live attenuated HIV vaccines: predicting the tradeoff between effi cacy and safety

Vaccination with ALVAC and AIDSVAX to prevent HIV-1 infection in Thailand

HIV-1 envelope accessible surface and polarity: clade, blood, and brain

The spectrum of neuro-aids disorders: pathophysiology, diagnosis, and treatment

T cell responses to viral infections-opportunities for peptide vaccination

Novel computer program for fast exact calculation of accessible and molecular surface areas and average surface curvature

The interpretation of protein structures: estimation of static accessibility

MHC-peptide binding prediction for epitope based vaccine design

Structure modeling based computer aided T-cell epitope design

A general model of invariant chain association with class II major histocompatibility complex proteins

Accurate prediction of the stability and activity effects of site-directed mutagenesis on a protein core

Predicting protein mutant energetics by self-consistent ensemble optimization

Knowledge-based grouping of modeled HLA peptide complexes

Towards the MHC-peptide combinatorics

Types of inter-atomic interactions at the MHC-peptide interface-identifying commonality from accumulated data

MPID: MHC-peptide interaction database for sequence-structure-function information on peptides binding to MHC molecules

Compression of functional space in HLA-A sequence diversity

A novel MHCp binding prediction model

Class II HLA-peptide binding prediction using structural principles

T-epitope designer: a HLA-peptide binding prediction server

HLA-peptide binding prediction using structural and modeling principles

HLA supertypes and supermotifs-a functional perspective on HLA polymorphism

A framework to sub-type HLA supertypes

A HLA-DRB supertype chart with potential overlapping peptide binding function

Structural basis for HLA-A2 supertypes

Grouping of class I HLA alleles using electrostatic distribution maps of the peptide binding grooves

Respiratory syncytial virus: current progress in vaccine development

The resurgence of measles in the United States, 1989-1990

Hepatitis B virus vaccine failure resulting in chronic hepatitis B infection

West Nile Virus: is a vaccine needed

An overview on severe acute respiratory syndrome (SARS)

A doubleinactivated severe acute respiratory syndrome coronavirus vaccine provides incomplete protection in mice and induces increased eosinophilic proinfl ammatory pulmonary response upon challenge

Other viral pneumonias: coronavirus, respiratory syncytial virus, adenovirus, hantavirus

HBV and HCV) viruses and possible agents of bioterrorism (variola) by enveloped virus neutralizing compounds (EVNCs)

A compendium of 40 years of epidemiological, clinical, and laboratory studies

Evaluation of perceived threat differences posed by fi lovirus variants

Induction of ebolavirus crossspecies immunity using retrovirus-like particles bearing the Ebola virus glycoprotein lacking the mucin-like domain

Acknowledgements We wish to express our sincere appreciation to all members of Biomedical Informatics (India) for many discussions on the subject of this chapter. We also thank all scientists, research associates, "then" students, and collaborators of the project over a period of two decades since 1993. Pandjassarame Kangueane thanks all associated members and institutions, namely Bioinformatics Centre and Department of Microbiology @ NUS (Singapore), Supercomputer Centre @ NTU (Singapore), Biomedical Informatics (India), VIT University (India), AIMST University (Malaysia), Roskamp Institute (USA), RCSB, X-ray crystallographers for immune biological molecules, reviewers, editors, readers with critical feedback, open-access movement, and publishers for all their support on the subject of this chapter towards its specifi c advancement.