SVRMHC prediction server for MHC-binding peptides

The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort. Recently, we demonstrated the appealing performance of SVRMHC, an SVR-based quantitative modeling method for peptide-MHC interactions, when applied to three mouse class I MHC molecules. Subsequently, we have greatly extended the construction of SVRMHC models and have established such models for more than 40 class I and class II MHC molecules. Here we present the SVRMHC web server for predicting peptide-MHC binding affinities using these models. Benchmarked percentile scores are provided for all predictions. The larger number of SVRMHC models available allowed for an updated evaluation of the performance of the SVRMHC method compared to other well- known linear modeling methods. SVRMHC is an accurate and easy-to-use prediction server for epitope-MHC binding with significant coverage of MHC molecules. We believe it will prove to be a valuable resource for T cell epitope researchers.

Cholecystokinin (CCK) receptor and CCK gene expression in human pituitary adenomas and in vitro effects of CCK peptides on GH and gonadotrophin secretion

There is growing evidence that cholecystokinin (CCK) affects growth and differentiation of anterior pituitary cells, via the CCK-B receptor. The possibility of an autocrine / paracrine role for CCK to modulate hormone secretion in human pituitary tumour cells is demonstrated here by RT-PCR and direct sequencing. In support of this conclusion, a neutralising antibody against the CCK peptide exhibited a dose dependent inhibition of hormone secretion by functionless pituitary adenomas. Total RNA was extracted from human pituitary adenomas, reverse transcribed into cDNA and subjected to PCR using primers specific for the gene for CCK, CCK-A and CCK-B receptors. PCR bands of the predicted length were observed in all tumours using human CCK gene and CCK-B receptor primers. Restriction digestion and direct sequence analysis provided further evidence that they represented both the human CCK peptide along with the CCK-A and/B receptor mRNA. CCK-33 and CCK octapeptide sulphate (CCK-8s) both powerfully stimulated phosphatidylinositol hydrolysis, providing evidence for functional activity of the CCK-A and/B receptors. A direct stimulatory effect of CCK peptides on both LH and FSH secretion is reported for the first time, whereas stimulatory effects on GH were blocked by antagonists to CCK. These results may indicate an autocrine role for CCK in the functioning and perhaps development of human pituitary tumours. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart.

On the hydrophobicity of peptides:comparing empirical predictions of peptide log P values

Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient logP, is useful for the development of predictive Quantitative Structure-Activity Relationships (QSARs). We have investigated the accuracy of available programs for the prediction of logP values for peptides with known experimental values obtained from the literature. Eight prediction programs were tested, of which seven programs were fragment-based methods: XLogP, LogKow, PLogP, ACDLogP, AlogP, Interactive Analysis's LogP and MlogP; and one program used a whole molecule approach: QikProp. The predictive accuracy of the programs was assessed using r(2) values, with ALogP being the most effective (r( 2) = 0.822) and MLogP the least (r(2) = 0.090). We also examined three distinct types of peptide structure: blocked, unblocked, and cyclic. For each study (all peptides, blocked, unblocked and cyclic peptides) the performance of programs rated from best to worse is as follows: all peptides - ALogP, QikProp, PLogP, XLogP, IALogP, LogKow, ACDLogP, and MlogP; blocked peptides - PLogP, XLogP, ACDLogP, IALogP, LogKow, QikProp, ALogP, and MLogP; unblocked peptides - QikProp, IALogP, ALogP, ACDLogP, MLogP, XLogP, LogKow and PLogP; cyclic peptides - LogKow, ALogP, XLogP, MLogP, QikProp, ACDLogP, IALogP. In summary, all programs gave better predictions for blocked peptides, while, in general, logP values for cyclic peptides were under-predicted and those of unblocked peptides were over-predicted.

Transporter associated with antigen processing preselection of peptides binding to the MHC:a bioinformatic evaluation

TAP is responsible for the transit of peptides from the cytosol to the lumen of the endoplasmic reticulum. In an immunological context, this event is followed by the binding of peptides to MHC molecules before export to the cell surface and recognition by T cells. Because TAP transport precedes MHC binding, TAP preferences may make a significant contribution to epitope selection. To assess the impact of this preselection, we have developed a scoring function for TAP affinity prediction using the additive method, have used it to analyze and extend the TAP binding motif, and have evaluated how well this model acts as a preselection step in predicting MHC binding peptides. To distinguish between MHC alleles that are exclusively dependent on TAP and those exhibiting only a partial dependence on TAP, two sets of MHC binding peptides were examined: HLA-A*0201 was selected as a representative of partially TAP-dependent HLA alleles, and HLA-A*0301 represented fully TAP-dependent HLA alleles. TAP preselection has a greater impact on TAP-dependent alleles than on TAP-independent alleles. The reduction in the number of nonbinders varied from 10% (TAP-independent) to 33% (TAP-dependent), suggesting that TAP preselection is an important component in the successful in silico prediction of T cell epitopes.

Coupling in silico and in vitro analysis of peptide-MHC binding:a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes

The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.

Designing immunogenic peptides

Peptides fulfill many roles in immunology, yet none are more important than their role as immunogenic epitopes driving the adaptive immune response, our ultimate bulwark against infectious disease. Peptide epitopes are mediated primarily by their interaction with major histocompatibility complexes (T-cell epitopes) and antibodies (B-cell epitopes). As pathogen genomes continue to be revealed, both experimental and computational epitope mapping are becoming crucial tools in vaccine discovery1,2. Immunoinformatics offers many tools, techniques and approaches for in silico epitope characterization, which is capable of greatly accelerating epitope design. © 2013 Nature America, Inc. All rights reserved.

Anticancer effects of Curcuma C20-dialdehyde against colon and cervical cancer cell lines

Background: Recent attention on chemotherapeutic intervention against cancer has been focused on discovering and developing phytochemicals as anticancer agents with improved efficacy, low drug resistance and toxicity, low cost and limited adverse side effects. In this study, we investigated the effects of Curcuma C20-dialdehyde on growth, apoptosis and cell cycle arrest in colon and cervical cancer cell lines. Materials and Methods: Antiproliferative, apoptosis induction, and cell cycle arrest activities of Curcuma C20-dialdehyde were determined by WST cell proliferation assay, flow cytometric Alexa fluor 488-annexin V/propidium iodide (PI) staining and PI staining, respectively. Results: Curcuma C20 dialdehyde suppressed the proliferation of HCT116, HT29 and HeLa cells, with IC50 values of 65.4±1.74 μg/ml, 58.4±5.20 μg/ml and 72.0±0.03 μg/ml, respectively, with 72 h exposure. Flow cytometric analysis revealed that percentages of early apoptotic cells increased in a dose-dependent manner upon exposure to Curcuma C20-dialdehyde. Furthermore, exposure to lower concentrations of this compound significantly induced cell cycle arrest at G1 phase for both HCT116 and HT29 cells, while higher concentrations increased sub-G1 populations. However, the concentrations used in this study could not induce cell cycle arrest but rather induced apoptotic cell death in HeLa cells. Conclusions: Our findings suggest that the phytochemical Curcuma C20-dialdehyde may be a potential antineoplastic agent for colon and cervical cancer chemotherapy and/or chemoprevention. Further studies are needed to characterize the drug target or mode of action of the Curcuma C20-dialdehyde as an anticancer agent.

Cholecystokinin-1 receptor antagonists:5-hydroxy-5-aryl-pyrrol-2-ones as anticancer agents

A new class of 5-arylated 5-hydroxypyrrolones was derived from mucochloric acid in 2 synthetic steps and the chemical structure was confirmed additionally by X-ray analysis. Using a radiolabelled binding assay, potent CCK1 selective ligands were identified (CCK1: 12 nM) and the antagonism was confirmed by using isolated tissue preparations. A series of isobutyl derivatives displayed unsurmountable CCK antagonistic properties and in vitro excellent inhibition of proliferation was obtained in cholecystokinin related cancer cell lines in the nanomolar range. Finally, using xenograft studies in nude mice, two selected pyrrolone derivatives, X = H and X = F a fluorinated analogue (PNB-028), showed a strong inhibition of tumour growth in a chemo-resistant colon cancer-(MAC 16) and a human pancreatic cell line (MIAPACA) at 50 mg kg-1 by oral administration.

The integration of ProxiMAX randomisation with CIS display for the production of novel peptides

Saturation mutagenesis is a powerful tool in modern protein engineering, which permits key residues within a protein to be targeted in order to potentially enhance specific functionalities. However, the creation of large libraries using conventional saturation mutagenesis with degenerate codons (NNN or NNK/S) has inherent redundancy and consequent disparities in codon representation. Therefore, both chemical (trinucleotide phosphoramidites) and biological methods (sequential, enzymatic single codon additions) of non-degenerate saturation mutagenesis have been developed in order to combat these issues and so improve library quality. Large libraries with multiple saturated positions can be limited by the method used to screen them. Although the traditional screening method of choice, cell-dependent methods, such as phage display, are limited by the need for transformation. A number of cell-free screening methods, such as CIS display, which link the screened phenotype with the encoded genotype, have the capability of screening libraries with up to 1014 members. This thesis describes the further development of ProxiMAX technology to reduce library codon bias and its integration with CIS display to screen the resulting library. Synthetic MAX oligonucleotides are ligated to an acceptor base sequence, amplified, and digested, subsequently adding a randomised codon to the acceptor, which forms an iterative cycle using the digested product of the previous cycle as the base sequence for the next. Initial use of ProxiMAX highlighted areas of the process where changes could be implemented in order to improve the codon representation in the final library. The refined process was used to construct a monomeric anti-NGF peptide library, based on two proprietary dimeric peptides (Isogenica) that bind NGF. The resulting library showed greatly improved codon representation that equated to a theoretical diversity of ~69%. The library was subsequently screened using CIS display and the discovered peptides assessed for NGF-TrkA inhibition by ELISA. Despite binding to TrkA, these peptides showed lower levels of inhibition of the NGF-TrkA interaction than the parental dimeric peptides, highlighting the importance of dimerization for inhibition of NGF-TrkA binding.