Recent developments in particulate-based vaccines

Vaccines remain a key tool in the defence against major diseases. However, in the development of vaccines a trade off between safety and efficacy is required with newer vaccines, based on sub-unit proteins and peptides, displaying improved safety profiles yet suffering from low efficacy. Adjuvants can be employed to improve their potency, but currently there are only a limited number of adjuvant systems licensed for clinical use. Of the new adjuvants being investigated, particulate systems offer several advantages including: passive targeting to the antigen-presenting cells within the immune system, protection against adjuvant degradation, and ability for sustained antigen release. There has been a range of particulate vaccine delivery systems outlined in recent patents including polymer-based microspheres (which are generally more focused on the use of synthetic polymers, in particular the polyesters) and surfactant-based vesicles. Within these formulations, several patented systems are exploiting the use of cationic lipids which, despite their limitations in gene therapy, clearly offer strong potential as adjuvants. Within this review, the current range of particulate system technologies being investigated as potential adjuvants are discussed with regard to both their respective advantages and the potential hurdles which must be overcome for such systems to be converted into successful pharmaceutical products.

Accurate estimation of isoelectric point of protein and peptide based on amino acid sequences

Motivation: In any macromolecular polyprotic system - for example protein, DNA or RNA - the isoelectric point - commonly referred to as the pI - can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge - and thus the electrophoretic mobility - of the ampholyte sums to zero. Different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Protein separation by isoelectric point is a critical part of 2-D gel electrophoresis, a key precursor of proteomics, where discrete spots can be digested in-gel, and proteins subsequently identified by analytical mass spectrometry. Peptide fractionation according to their pI is also widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. Therefore accurate theoretical prediction of pI would expedite such analysis. While such pI calculation is widely used, it remains largely untested, motivating our efforts to benchmark pI prediction methods. Results: Using data from the database PIP-DB and one publically available dataset as our reference gold standard, we have undertaken the benchmarking of pI calculation methods. We find that methods vary in their accuracy and are highly sensitive to the choice of basis set. The machine-learning algorithms, especially the SVM-based algorithm, showed a superior performance when studying peptide mixtures. In general, learning-based pI prediction methods (such as Cofactor, SVM and Branca) require a large training dataset and their resulting performance will strongly depend of the quality of that data. In contrast with Iterative methods, machine-learning algorithms have the advantage of being able to add new features to improve the accuracy of prediction. Contact: yperez@ebi.ac.uk Availability and Implementation: The software and data are freely available at https://github.com/ypriverol/pIR. Supplementary information: Supplementary data are available at Bioinformatics online.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Toward the atomistic simulation of T cell epitopes automated construction of MHC:peptide structures for free energy calculations

Epitopes mediated by T cells lie at the heart of the adaptive immune response and form the essential nucleus of anti-tumour peptide or epitope-based vaccines. Antigenic T cell epitopes are mediated by major histocompatibility complex (MHC) molecules, which present them to T cell receptors. Calculating the affinity between a given MHC molecule and an antigenic peptide using experimental approaches is both difficult and time consuming, thus various computational methods have been developed for this purpose. A server has been developed to allow a structural approach to the problem by generating specific MHC:peptide complex structures and providing configuration files to run molecular modelling simulations upon them. A system has been produced which allows the automated construction of MHC:peptide structure files and the corresponding configuration files required to execute a molecular dynamics simulation using NAMD. The system has been made available through a web-based front end and stand-alone scripts. Previous attempts at structural prediction of MHC:peptide affinity have been limited due to the paucity of structures and the computational expense in running large scale molecular dynamics simulations. The MHCsim server (http://igrid-ext.cryst.bbk.ac.uk/MHCsim) allows the user to rapidly generate any desired MHC:peptide complex and will facilitate molecular modelling simulation of MHC complexes on an unprecedented scale.

MHC class II binding prediction:a little help from a friend

Vaccines are the greatest single instrument of prophylaxis against infectious diseases, with immeasurable benefits to human wellbeing. The accurate and reliable prediction of peptide-MHC binding is fundamental to the robust identification of T-cell epitopes and thus the successful design of peptide- and protein-based vaccines. The prediction of MHC class II peptide binding has hitherto proved recalcitrant and refractory. Here we illustrate the utility of existing computational tools for in silico prediction of peptides binding to class II MHCs. Most of the methods, tested in the present study, detect more than the half of the true binders in the top 5% of all possible nonamers generated from one protein. This number increases in the top 10% and 15% and then does not change significantly. For the top 15% the identified binders approach 86%. In terms of lab work this means 85% less expenditure on materials, labour and time. We show that while existing caveats are well founded, nonetheless use of computational models of class II binding can still offer viable help to the work of the immunologist and vaccinologist.

Polymer-peptide conjugate hydrogels:towards controlled drug delivery

Peptide-based materials exhibit remarkable supramolecular self-assembling behavior, owing to their overwhelming propensity to from hierarchical structures from a-helices and ß-sheets. Coupling a peptide sequence to a synthetic polymer chain allows greater control over the final physical properties of the supermolecular material. So-called ‘polymer-peptide conjugates’ can be used to create biocompatible hydrogels which are held together by reversible physical interactions. Potentially, the hydrogels can be loaded with aqueous-based drug molecules, which can be injected into targeted sites in the body if they can exhibit a gel-sol-gel transition under application and removal of a shear force. In this review, we introduce this topic to readers new to the field of polymer-peptide conjugates, discussing common synthetic strategies and their self-assembling behavior. The lack of examples of actual drug delivery applications from polymer-peptide conjugates is highlighted in an attempt to incite progress in this area.

Particulate delivery systems for vaccines

This review focuses on the use of particulate delivery systems for the purposes of immunization. This includes poly(lactide-co-glycolide) (PLGA), ISCOMs, liposomes, niosomes, virosomes, chitosan, and other biodegradable polymers. These systems are evaluated in terms of their use as carriers for protein subunit and DNA vaccines. There is an extensive focus on recent literature, the understanding of biological interactions, and relation of this to our present understanding of immunological mechanisms of action. In addition, there is consideration of formulation techniques including emulsification, solvent diffusion, DNA complexation, and entrapment. The diversity of formulation strategies presented is a testament to the exponential growth and interest in the area of vaccine delivery systems. A case study for the application of particulate vaccine carriers is assessed in terms of vaccine development and recent insights into the possible design and application of vaccines against two of the most important pathogens that threaten mankind and for which there is a significant need: Mycobacterium tuberculosis and human immunodeficiency virus. This review addresses the rationale for the use of particulate delivery systems in vaccine design in the context of the diversity of carriers for DNA- and protein-based vaccines and their potential for application in terms of the critical need for effective vaccines. © 2005 by Begell House, Inc.

Identifiying human MHC supertypes using bioinformatic methods

Classification of MHC molecules into supertypes in terms of peptide-binding specificities is an important issue, with direct implications for the development of epitope-based vaccines with wide population coverage. In view of extremely high MHC polymorphism (948 class I and 633 class II HLA alleles) the experimental solution of this task is presently impossible. In this study, we describe a bioinformatics strategy for classifying MHC molecules into supertypes using information drawn solely from three-dimensional protein structure. Two chemometric techniques–hierarchical clustering and principal component analysis–were used independently on a set of 783 HLA class I molecules to identify supertypes based on structural similarities and molecular interaction fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed “supertype fingerprints” to be identified. Thus, the A2 supertype fingerprint is Tyr9/Phe9, Arg97, and His114 or Tyr116; the A3-Tyr9/Phe9/Ser9, Ile97/Met97 and Glu114 or Asp116; the A24-Ser9 and Met97; the B7-Asn63 and Leu81; the B27-Glu63 and Leu81; for B44-Ala81; the C1-Ser77; and the C4-Asn77. action fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed “supertype fingerprints” to be identified. Thus, the A2 supertype fingerprint is Tyr9/Phe9, Arg97, and His114 or Tyr116; the A3-Tyr9/Phe9/Ser9, Ile97/Met97 and Glu114 or Asp116; the A24-Ser9 and Met97; the B7-Asn63 and Leu81; the B27-Glu63 and Leu81; for B44-Ala81; the C1-Ser77; and the C4-Asn77.

Designing liposomal adjuvants for the next generation of vaccines

Liposomes not only offer the ability to enhance drug delivery, but can effectively act as vaccine delivery systems and adjuvants. Their flexibility in size, charge, bilayer rigidity and composition allow for targeted antigen delivery via a range of administration routes. In the development of liposomal adjuvants, the type of immune response promoted has been linked to their physico-chemical characteristics, with the size and charge of the liposomal particles impacting on liposome biodistribution, exposure in the lymph nodes and recruitment of the innate immune system. The addition of immunostimulatory agents can further potentiate their immunogenic properties. Here, we outline the attributes that should be considered in the design and manufacture of liposomal adjuvants for the delivery of sub-unit and nucleic acid based vaccines.

Vaccines

Vaccines continue to offer the key line of protection against a range of infectious diseases; however, the range of vaccines currently available is limited. One key consideration in the development of a vaccine is risk-versus-benefit, and in an environment of perceived low risk, the benefit of vaccination may not be recognised. To address this, there has been a move towards the use of subunit-based vaccines, which offer low side-effect profiles but are generally weakly immunogenic. This can be compensated for by the development of effective adjuvants. Nanotechnology offers key attributes in this field through the ability of nanoparticulates to incorporate and protect antigens from rapid degradation, combined with their potential to effectively deliver the antigens to appropriate cells within the immune system. These characteristics can be exploited in the development of new adjuvants. This chapter will outline the applications of nanosystems in vaccine formulations and consider the mechanisms of action behind a range of formulations.

Vaccine adjuvant systems: enhancing the efficacy of sub-unit protein antigens

Vaccination remains a key tool in the protection and eradication of diseases. However, the development of new safe and effective vaccines is not easy. Various live organism based vaccines currently licensed, exhibit high efficacy; however, this benefit is associated with risk, due to the adverse reactions found with these vaccines. Therefore, in the development of vaccines, the associated risk-benefit issues need to be addressed. Sub-unit proteins offer a much safer alternative; however, their efficacy is low. The use of adjuvanted systems have proven to enhance the immunogenicity of these sub-unit vaccines through protection (i.e. preventing degradation of the antigen in vivo) and enhanced targeting of these antigens to professional antigen-presenting cells. Understanding of the immunological implications of the related disease will enable validation for the design and development of potential adjuvant systems. Novel adjuvant research involves the combination of both pharmaceutical analysis accompanied by detailed immunological investigations, whereby, pharmaceutically designed adjuvants are driven by an increased understanding of mechanisms of adjuvant activity, largely facilitated by description of highly specific innate immune recognition of components usually associated with the presence of invading bacteria or virus. The majority of pharmaceutical based adjuvants currently being investigated are particulate based delivery systems, such as liposome formulations. As an adjuvant, liposomes have been shown to enhance immunity against the associated disease particularly when a cationic lipid is used within the formulation. In addition, the inclusion of components such as immunomodulators, further enhance immunity. Within this review, the use and application of effective adjuvants is investigated, with particular emphasis on liposomal-based systems. The mechanisms of adjuvant activity, analysis of complex immunological characteristics and formulation and delivery of these vaccines are considered.

The HLA-A2-supermotif:a QSAR definition

Identification of epitopes capable of binding multiple HLA types will significantly rationalise the development of epitope-based vaccines. A quantitative method assessing the contribution of each amino acid at each position was applied to over 500 nonamer peptides binding to 5 MHC alleles — A*0201, A*0202, A*0203, A*0206 and A*6802 — which together define the HLA-A2-like supertype. FXIGXI (L)IFV was identified as a supermotif for the A2-supertype based on the contributions of the common preferred amino acids at each of the nine positions. The results indicate that HLA-A*6802 is an intermediate allele standing between A2 and A3 supertypes: at anchor position 2 it is closer to A3 and at anchor position 9 it is nearer to A2. Models are available free on-line at http://www.jenner.ac.uk/MHCPred and can be used for binding affinity prediction.

Subunit vaccines distearoylphosphatidylcholine-based liposomes entrapping antigen offer a neutral alternative to dimethyldioctadecylammonium-based cationic liposomes as an adjuvant delivery system

The adjuvanticity of liposomes can be directed through formulation to develop a safe yet potent vaccine candidate. With the addition of the cationic lipid dimethyldioctadecylammonium bromide (DDA) to stable neutral distearoylphosphatidylcholine (DSPC):cholesterol (Chol) liposomes, vesicle size reduces while protein entrapment increases. The addition of the immunomodulator, trehalose 6,6-dibehenate (TDB) to either the neutral or cationic liposomes did not affect the physiochemical characteristics of these liposome vesicles. However, the protective immune response, as indicated by the amount of IFN-? production, increases considerably when TDB is present. High levels of IFN-? were observed for cationic liposomes; however, there was a marked reduction in IFN-? release over time. Conversely, for neutral liposomes containing TDB, although the initial amount of IFN-? was slightly lower than the cationic equivalent, the overall protective immune responses of these neutral liposomes were effectively maintained over time, generating good levels of protection. To that end, although the addition of DSPC and Chol reduced the protective immunity of DDA:TDB liposomes, relatively high protection was observed for the neutral counterpart, DSPC:Chol:TDB, which may offer an effective neutral alternative to the DDA:TDB cationic system, especially for the delivery of either zwitterionic (neutral) or cationic molecules or antigens.