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.

Mechanisms of action of microbicides

This chapter describes the sites and mechanisms of action of the major groups of microbicides, relating their physical and chemical properties to interactions with microbial structures. It considers the physical, cellular and molecular methods for studying the mechanisms of action of chemical microbicides. These range from the uptake, binding and penetration of microbial cells, to the interaction with microbial structures, including the cell wall, membrane, nucleic acids, cytoplasm and enzymes. Key features of the mechanisms of action of the major groups of microbicides are described covering oxidizing agents, alkylating agents, metal ion-binding agents, nucleic acid-binding agents, protein denaturants and agents that interact with lipids. © 2013 Blackwell Publishing Ltd.

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.

Solid-supported boronic acid conjugates for sugar and glycopeptide recognition

The Fmoc synthetic strategy was employed to synthesise two identical combinatorial peptide libraries on a hydrophilic PEG-PS resin. One library was appended with boronic acid moieties at two positionally-fixed locations. Successful inclusion of the boronic acid units was confirmed using a novel UV fluorescent colorimetric assay employing carminic acid as the dye compound. A study of the effect had by the resin-bound peptides bearing boronic acid groups on the binding characteristics of vancomycin, a medically relevant antibiotic glycoprotein, was conducted. In all, 132 library compounds were tested for their binding affinity with vancomycin, via immobilisation of the glycopeptide onto the solid support through hydrogen bonding or complexation with the boronic acid moieties. Subsequent cleavage via acidolysis afforded vancomycin containing solutions which were quantified by growth inhibition of methicillin susceptible Staphylococcus aureus. Comparison of the diameters of the resultant zones of inhibition and those produced by vancomycin of known concentrations afforded a means of calculating the vancomycin concentration of the cleavage solutions, and thereby determining the binding affinity of vancomycin to each peptide sequence. Five peptide sequences and twenty one of the peptidyl-boronic acid sequences showed zones of inhibition, demonstrating their reversible affinity for vancomycin. Three peptide sequences showed zones of inhibition in both libraries. The presence of boronic acid was therefore shown to impart, enhance, detract and remove the affinity of vancomycin to a range of resin-bound peptide sequences.

Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties

Subunit vaccine discovery is an accepted clinical priority. The empirical approach is time- and labor-consuming and can often end in failure. Rational information-driven approaches can overcome these limitations in a fast and efficient manner. However, informatics solutions require reliable algorithms for antigen identification. All known algorithms use sequence similarity to identify antigens. However, antigenicity may be encoded subtly in a sequence and may not be directly identifiable by sequence alignment. We propose a new alignment-independent method for antigen recognition based on the principal chemical properties of protein amino acid sequences. The method is tested by cross-validation on a training set of bacterial antigens and external validation on a test set of known antigens. The prediction accuracy is 83% for the cross-validation and 80% for the external test set. Our approach is accurate and robust, and provides a potent tool for the in silico discovery of medically relevant subunit vaccines.

Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach

DNA-binding proteins are crucial for various cellular processes and hence have become an important target for both basic research and drug development. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to establish an automated method for rapidly and accurately identifying DNA-binding proteins based on their sequence information alone. Owing to the fact that all biological species have developed beginning from a very limited number of ancestral species, it is important to take into account the evolutionary information in developing such a high-throughput tool. In view of this, a new predictor was proposed by incorporating the evolutionary information into the general form of pseudo amino acid composition via the top-n-gram approach. It was observed by comparing the new predictor with the existing methods via both jackknife test and independent data-set test that the new predictor outperformed its counterparts. It is anticipated that the new predictor may become a useful vehicle for identifying DNA-binding proteins. It has not escaped our notice that the novel approach to extract evolutionary information into the formulation of statistical samples can be used to identify many other protein attributes as well.