Carnosine:can understanding its actions on energy metabolism and protein homeostasis inform its therapeutic potential?

The dipeptide carnosine (β-alanyl-L-histidine) has contrasting but beneficial effects on cellular activity. It delays cellular senescence and rejuvenates cultured senescent mammalian cells. However, it also inhibits the growth of cultured tumour cells. Based on studies in several organisms, we speculate that carnosine exerts these apparently opposing actions by affecting energy metabolism and/or protein homeostasis (proteostasis). Specific effects on energy metabolism include the dipeptide's influence on cellular ATP concentrations. Carnosine's ability to reduce the formation of altered proteins (typically adducts of methylglyoxal) and enhance proteolysis of aberrant polypeptides is indicative of its influence on proteostasis. Furthermore these dual actions might provide a rationale for the use of carnosine in the treatment or prevention of diverse age-related conditions where energy metabolism or proteostasis are compromised. These include cancer, Alzheimer's disease, Parkinson's disease and the complications of type-2 diabetes (nephropathy, cataracts, stroke and pain), which might all benefit from knowledge of carnosine's mode of action on human cells. © 2013 Hipkiss et al.; licensee Chemistry Central Ltd.

Investigating polymer-peptide conjugates and electrospinning for the production of advanced materials

This thesis describes the production of advanced materials comprising a wide array of polymer-based building blocks. These materials include bio-hybrid polymer-peptide conjugates, based on phenylalanine and poly(ethylene oxide), and polymers with intrinsic microporosity (PIMs). Polymer-peptides conjugates were previously synthesised using click chemistry. Due to the inherent disadvantages of the reported synthesis, a new, simpler, inexpensive protocol was sought. Three synthetic methods based on amidation chemistry were investigated for both oligopeptide and polymerpeptide coupling. The resulting conjugates produced were then assessed by various analytical techniques, and the new synthesis was compared with the established protocol. An investigation was also carried out focussing on polymer-peptide coupling via ester chemistry, involving deprotection of the carboxyl terminus of the peptide. Polymer-peptide conjugates were also assessed for their propensity to self-assemble into thixotropic gels in an array of solvent mixtures. Determination of the rules governing this particular self-assembly (gelation) was required. Initial work suggested that at least four phenylalanine peptide units were necessary for self-assembly, due to favourable hydrogen bond interactions. Quantitative analysis was carried out using three analytical techniques (namely rheology, FTIR, and confocal microscopy) to probe the microstructure of the material and provided further information on the conditions for self-assembly. Several polymers were electrospun in order to produce nanofibres. These included novel materials such as PIMs and the aforementioned bio-hybrid conjugates. An investigation of the parameters governing successful fibre production was carried out for PIMs, polymer-peptide conjugates, and for nanoparticle cages coupled to a polymer scaffold. SEM analysis was carried out on all material produced during these electrospinning experiments.

Identification and relative quantification of tyrosine nitration in a model peptide using two-dimensional infrared spectroscopy

Nitration of tyrosine in proteins and peptides is a post-translational modification that occurs under conditions of oxidative stress. It is implicated in a variety of medical conditions, including neurodegenerative and cardiovascular diseases. However, monitoring tyrosine nitration and understanding its role in modifying biological function remains a major challenge. In this work, we investigate the use of electron-vibration-vibration (EVV) two-dimensional infrared (2DIR) spectroscopy for the study of tyrosine nitration in model peptides. We demonstrate the ability of EVV 2DIR spectroscopy to differentiate between the neutral and deprotonated states of 3-nitrotyrosine, and we characterize their spectral signatures using information obtained from quantum chemistry calculations and simulated EVV 2DIR spectra. To test the sensitivity of the technique, we use mixed-peptide samples containing various levels of tyrosine nitration, and we use mass spectrometry to independently verify the level of nitration. We conclude that EVV 2DIR spectroscopy is able to provide detailed spectroscopic information on peptide side-chain modifications and to detect nitration levels down to 1%. We further propose that lower nitration levels could be detected by introducing a resonant Raman probe step to increase the detection sensitivity of EVV 2DIR spectroscopy. (Graph Presented).

Peptide binding to the HLA-DRB1 supertype:a proteochemometrics analysis

A proteochemometrics approach was applied to a set of 2666 peptides binding to 12 HLA-DRB1 proteins. Sequences of both peptide and protein were described using three z-descriptors. Cross terms accounting for adjacent positions and for every second position in the peptides were included in the models, as well as cross terms for peptide/protein interactions. Models were derived based on combinations of different blocks of variables. These models had moderate goodness of fit, as expressed by r2, which ranged from 0.685 to 0.732; and good cross-validated predictive ability, as expressed by q2, which varied from 0.678 to 0.719. The external predictive ability was tested using a set of 356 HLA-DRB1 binders, which showed an r2(pred) in the range 0.364-0.530. Peptide and protein positions involved in the interactions were analyzed in terms of hydrophobicity, steric bulk and polarity.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique

A set of 38 epitopes and 183 non-epitopes, which bind to alleles of the HLA-A3 supertype, was subjected to a combination of comparative molecular similarity indices analysis (CoMSIA) and soft independent modeling of class analogy (SIMCA). During the process of T cell recognition, T cell receptors (TCR) interact with the central section of the bound nonamer peptide; thus only positions 4−8 were considered in the study. The derived model distinguished 82% of the epitopes and 73% of the non-epitopes after cross-validation in five groups. The overall preference from the model is for polar amino acids with high electron density and the ability to form hydrogen bonds. These so-called “aggressive” amino acids are flanked by small-sized residues, which enable such residues to protrude from the binding cleft and take an active role in TCR-mediated T cell recognition. Combinations of “aggressive” and “passive” amino acids in the middle part of epitopes constitute a putative TCR binding motif

Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide:can the α3 and β2m domains be neglected?

Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histo-compatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVY-DGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide–MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the α1–α2 domain, the α3 and β2m domains cannot be neglected. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1803–1813, 2004

New horizons in mouse immunoinformatics:reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity

Quantitative structure–activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide–protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2–Db, H2–Kb and H2–Kk. As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online (http://www.jenner.ac.uk/MHCPred).

Lys9 for Glu9 substitution in glucagon-like peptide-1(7-36)amide confers dipeptidylpeptidase IV resistance with cellular and metabolic actions similar to those of established antagonists glucagon-like peptide-1(9-36)amide and exendin (9-39)

The incretin hormone glucagon-like peptide-1(7-36)amide (GLP-1) has been deemed of considerable importance in the regulation of blood glucose. Its effects, mediated through the regulation of insulin, glucagon, and somatostatin, are glucose-dependent and contribute to the tight control of glucose levels. Much enthusiasm has been assigned to a possible role of GLP-1 in the treatment of type 2 diabetes. GLIP-l's action unfortunately is limited through enzymatic inactivation caused by dipeptidylpeptidase IV (DPP IV). It is now well established that modifying GLP-1 at the N-terminal amino acids, His7 and Ala8, can greatly improve resistance to this enzyme. Little research has assessed what effect Glu9-substitution has on GLP-1 activity and its degradation by DPP IV. Here, we report that the replacement of Glu9 of GLP-1 with Lys dramatically increased resistance to DPP IV. This analogue (Lys9)GLP-1, exhibited a preserved GLP-1 receptor affinity, but the usual stimulatory effects of GLP-1 were completely eliminated, a trait duplicated by the other established GLP-1-antagonists, exendin (9-39) and GLP-1 (9-36)amide. We investigated the in vivo antagonistic actions of (Lys9)GLP-1 in comparison with GLP-1(9-36)amide and exendin (9-39) and revealed that this novel analogue may serve as a functional antagonist of the GLP-1 receptor.

A comparative molecular similarity indices (CoMSIA) study of peptide binding to the HLA-A3 superfamily

Epitope identification is the basis of modern vaccine design. The present paper studied the supermotif of the HLA-A3 superfamily, using comparative molecular similarity indices analysis (CoMSIA). Four alleles with high phenotype frequencies were used: A*1101, A*0301, A*3101 and A*6801. Five physicochemical properties—steric bulk, electrostatic potential, local hydro-phobicity, hydrogen-bond donor and acceptor abilities—were considered and ‘all fields’ models were produced for each of the alleles. The models have a moderate level of predictivity and there is a good correlation between the data. A revised HLA-A3 supermotif was defined based on the comparison of favoured and disfavoured properties for each position of the MHC bound peptide. The present study demonstrated that CoMSIA is an effective tool for studying peptide–MHC interactions.

MHCPred : a server for quantitative prediction of peptide-MHC binding

Accurate T-cell epitope prediction is a principal objective of computational vaccinology. As a service to the immunology and vaccinology communities at large, we have implemented, as a server on the World Wide Web, a partial least squares-base multivariate statistical approach to the quantitative prediction of peptide binding to major histocom-patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive,cellular immunity. MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203,HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401and HLA-DRB* 0701).

Speciation, metabolism, toxicity, and protein-binding of different arsenic species in human cells

Despite of its known toxicity and potential to cause cancer, arsenic has been proven to be a very important tool for the treatment of various refractory neoplasms. One of the promising arsenic-containing chemotherapeutic agents in clinical trials is Darinaparsin (dimethylarsinous glutathione, DMA III(GS)). In order to understand its toxicity and therapeutic efficacy, the metabolism of Darinaparsin in human cancer cells was evaluated. With the aim of detecting all potential intermediates and final products of the biotransformation of Darinaparsin and other arsenicals, an analytical method employing high performance liquid chromatography inductively coupled mass spectrometry (HPLC-ICP-MS) was developed. This method was shown to be capable of separating and detecting fourteen human arsenic metabolites in one chromatographic run. The developed analytical technique was used to evaluate the metabolism of Darinaparsin in human cancer cells. The major metabolites of Darinaparsin were identified as dimethylarsinic acid (DMAV), DMA III(GS), and dimethylarsinothioyl glutathione (DMMTAV(GS)). Moreover, the method was employed to study the conditions and mechanisms of formation of thiol-containing arsenic metabolites from DMAIII(GS) and DMAV as the mechanisms of formation of these important As species were unknown. The arsenic sulfur compounds studied included but were not limited to the newly discovered human arsenic metabolite DMMTA V(GS) and the unusually highly toxic dimethylmonothioarsinic acid (DMMTAV). It was found that these species may form from hydrogen sulfide produced in enzymatic reactions or by utilizing the sulfur present in protein persulfides. Possible pathways of thiolated arsenical formation were proposed and supporting data for their existence provided. In addition to known mechanism of arsenic toxicity such as protein-binding and reactive oxygen formation, it was proposed that the utilization of thiols from protein persulfides during the formation of thiolated arsenicals may be an additional mechanism of toxicity. The toxicities of DMAV(GS), DMMTA V, and DMMTAV(GS) were evaluated in cancer cells, and the ability of these cells to take the compounds up were compared. When assessing the toxicity by exposing multiple myeloma cells to arsenicals externally, DMMTAV(GS) was much less toxic than DMAIII(GS) and DMMTAV, probably as a result of its very limited uptake (less than 10% and 16% of DMAIII(GS) and DMMTAV respectively).^

Seawater carbonate chemistry and biological processes during experiments with four species of marine diatoms

The effect of pCO2 on carbon acquisition and intracellular assimilation was investigated in the three bloom-forming diatom species, Eucampia zodiacus (Ehrenberg), Skeletonema costatum (Greville) Cleve, Thalassionema nitzschioides (Grunow) Mereschkowsky and the non-bloom-forming Thalassiosira pseudonana (Hust.) Hasle and Heimdal. In vivo activities of carbonic anhydrase (CA), photosynthetic O2 evolution, CO2 and HCO3? uptake rates were measured by membrane-inlet mass spectrometry (MIMS) in cells acclimated to pCO2 levels of 370 and 800 ?atm. To investigate whether the cells operate a C4-like pathway, activities of ribulose-1,5-bisphosphate carboxylase (RubisCO) and phosphoenolpyruvate carboxylase (PEPC) were measured at the mentioned pCO2 levels and a lower pCO2 level of 50 ?atm. In the bloom-forming species, extracellular CA activities strongly increased with decreasing CO2 supply while constantly low activities were obtained for T. pseudonana. Half-saturation concentrations (K1/2) for photosynthetic O2 evolution decreased with decreasing CO2 supply in the two bloom-forming species S. costatum and T. nitzschioides, but not in T. pseudonana and E. zodiacus. With the exception of S. costatum, maximum rates (Vmax) of photosynthesis remained constant in all investigated diatom species. Independent of the pCO2 level, PEPC activities were significantly lower than those for RubisCO, averaging generally less than 3%. All examined diatom species operate highly efficient CCMs under ambient and high pCO2, but differ strongly in the degree of regulation of individual components of the CCM such as Ci uptake kinetics and extracellular CA activities. The present data do not suggest C4 metabolism in the investigated species.