A novel concentration dependent amino acid ion pair strategy to mediate drug permeation using indomethacin as a model insoluble drug

Assessment of oral drug bioavailability is an important parameter for new chemical entities (NCEs) in drug development cycle. After evaluating the pharmacological response of these new molecules, the following critical stage is to investigate their in vitro permeability. Despite the great success achieved by prodrugs, covalent linking the drug molecule with a hydrophobic moiety might result in a new entity that might be toxic or ineffective. Therefore, an alternative that would improve the drug uptake without affecting the efficacy of the drug molecule would be advantageous. The aim of the current study is to investigate the effect of ion-pairing on the permeability profile of a model drug: indomethacin (IND) to understand the mechanism behind the permeability improvement across Caco-2 monolayers. Arginine and lysine formed ion-pairs with IND at various molar ratios 1:1, 1:2, 1:4 and 1:8 as reflected by the double reciprocal graphs. The partitioning capacities of the IND were evaluated using octanol/water partitioning studies and the apparent permeabilities (P app) were measured across Caco-2 monolayers for the different formulations. Partitioning studies reflected the high hydrophobicity of IND (Log P = 3) which dropped upon increasing the concentrations of arginine/lysine in the ion pairs. Nevertheless, the prepared ion pairs improved IND permeability especially after 60 min of the start of the experiment. Coupling partitioning and permeability results suggest a decrease in the passive transcellular uptake due to the drop in IND portioning capacities and a possible involvement of active carriers. Future work will investigate which transport gene might be involved in the absorption of the ion paired formulations using molecular biology technologies. © 2014 Elsevier B.V. All rights reserved.

Optimizing amino acid groupings for GPCR classification

MOTIVATION: There is much interest in reducing the complexity inherent in the representation of the 20 standard amino acids within bioinformatics algorithms by developing a so-called reduced alphabet. Although there is no universally applicable residue grouping, there are numerous physiochemical criteria upon which one can base groupings. Local descriptors are a form of alignment-free analysis, the efficiency of which is dependent upon the correct selection of amino acid groupings. RESULTS: Within the context of G-protein coupled receptor (GPCR) classification, an optimization algorithm was developed, which was able to identify the most efficient grouping when used to generate local descriptors. The algorithm was inspired by the relatively new computational intelligence paradigm of artificial immune systems. A number of amino acid groupings produced by this algorithm were evaluated with respect to their ability to generate local descriptors capable of providing an accurate classification algorithm for GPCRs.

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.

Differential impact of amino acid substitutions on critical residues of the human glucagon-like peptide-1 receptor involved in peptide activity and small-molecule allosterys

The glucagon-like peptide-1 receptor (GLP-1R) is a class B G protein-coupled receptor that has a critical role in the regulation of glucose homeostasis, principally through the regulation of insulin secretion. The receptor systemis highly complex, able to be activated by both endogenous [GLP-1(1-36)NH2, GLP-1(1-37), GLP-1(7-36)NH2, GLP-1(7-37), oxyntomodulin], and exogenous (exendin-4) peptides in addition to small-molecule allosteric agonists (compound 2 [6,7-dichloro-2-methylsulfonyl-3-tertbutylaminoquinoxaline], BETP [4-(3-benzyloxy)phenyl)-2-ethylsulfinyl-6-(trifluoromethyl)pyrimidine]). Furthermore, the GLP-1R is subject to single-nucleotide polymorphic variance, resulting in amino acid changes in the receptor protein. In this study, we investigated two polymorphic variants previously reported to impact peptidemediated receptor activity (M149) and small-molecule allostery (C333). These residues were mutated to a series of alternate amino acids, and their functionality was monitored across physiologically significant signaling pathways, including cAMP, extracellular signal-regulated kinase 1 and 2 phosphorylation, and intracellular Ca2+ mobilization, in addition to peptide binding and cell-surface expression. We observed that residue 149 is highly sensitive to mutation, with almost all peptide responses significantly attenuated at mutated receptors. However, most reductions in activity were able to be restored by the small-molecule allosteric agonist compound 2. Conversely, mutation of residue 333 had little impact on peptide-mediated receptor activation, but this activity could not be modulated by compound 2 to the same extent as that observed at the wild-type receptor. These results provide insight into the importance of residues 149 and 333 in peptide function and highlight the complexities of allosteric modulation within this receptor system.

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.

Facile synthesis of polymer-peptide conjugates via direct amino acid coupling chemistry

Polymer-peptide conjugates (also known as biohy-brids) are attracting considerable attention as injectable materials owing to the self-assembling behavior of the peptide and the ability to control the material properties using the polymer component. To this end, a simple method for preparing poly(ethylene oxide)-oligophenylalanine polymer-peptide conjugates (mPEOm-F n-OEt) using isobutylchloroformate as the activating reagent has been identified and developed. The synthetic approach reported employs an industrially viable route to produce conjugates with high yield and purity. Moreover, the approach allows judicious selection of the precursor building blocks to produce libraries of polymer-peptide conjugates with complete control over the molecular composition. Control over the molecular make-up of the conjugates allows fine control of the physicochemical properties, which will be exploited in future studies into the prominent self-assembling behavior of such materials. © 2013 Wiley Periodicals, Inc.

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.

An assessment of the microbial contribution to aquatic dissolved organic nitrogen using amino acid enantiomeric ratios

There is increasing evidence that certain microbially-derived compounds may account for part of the aquatic dissolved organic nitrogen (DON) pool. Enantiomeric ratios of amino acids were used to assess the microbial input to the DON pool in the Florida Everglades, USA. Elevated levels of d-alanine, d-aspartic acid, d-glutamic acid and d-serine indicated the presence of peptidoglycan in the samples. The estimated peptidoglycan contribution to amino acid nitrogen ranged from 2.8 ± 0.1% to 6.4 ± 0.9%, increasing with salinity from freshwater to coastal waters. The distribution of individual d-amino acids in the samples suggests additional inputs to DON, possibly from archaea or from abiotic racemization of l-amino acids.

Benthic organic carbon flux and oxygen penetration depth in the Southern Ocean

For the investigation of organic carbon fluxes reaching the seafloor, oxygen microprofiles were measured at 145 sites in different sub-regions of the Southern Ocean. At eleven sites, an in situ oxygen microprofiler was deployed for the measurement of oxygen profiles and the calculation of organic carbon fluxes. At four sites, both in situ and ex situ data were determined for high latitudes. Based on this dataset as well as on previous published data, a relationship was established for the estimation of fluxes derived by ex situ measured O2 profiles. The fluxes of labile organic matter range from 0.5 to 37.1 mgC m**2/day. The high values determined by in situ measurements were observed in the Polar Front region (water depth of more than 4290 m) and are comparable to organic matter fluxes observed for high-productivity, upwelling areas like off West Africa. The oxygen penetration depth, which reflects the long-term organic matter flux to the sediment, was correlated with assemblages of key diatom species. In the Scotia Sea (~3000 m water depth), oxygen penetration depths of less than 15 cm were observed, indicating high benthic organic carbon fluxes. In contrast, the oxic zone extends down to several decimeters in abyssal sediments of the Weddell Sea and the southeastern South Atlantic. The regional pattern of organic carbon fluxes derived from micro-sensor data suggest that episodic and seasonal sedimentation pulses are important for the carbon supply to the seafloor of the deep Southern Ocean.

Community control in cellular protein production : consequences for amino acid starvation

The authors thank M. C. Romano, I. Stansfield, L. Ciandrini, A. Kort, and M. Rehberg for helpful discussions. This work was funded by BBSRC grants BB/F00513/X1 and BB/G010722, and the Scottish Universities Life Science Alliance (SULSA).

Community control in cellular protein production : consequences for amino acid starvation

The authors thank M. C. Romano, I. Stansfield, L. Ciandrini, A. Kort, and M. Rehberg for helpful discussions. This work was funded by BBSRC grants BB/F00513/X1 and BB/G010722, and the Scottish Universities Life Science Alliance (SULSA).

Whole body and splanchnic amino acid metabolism in sheep during an acute endotoxin challenge

Acknowledgements The expertise of A. Graham Calder and Susan Anderson for the various stable isotope analyses is gratefully recognised. Ngaire Dennison is also thanked for her surgical expertise with the trans-splanchnic tissue catheter preparations. This study was supported by funds provided to the Rowett Institute of Nutrition and Health, University of Aberdeen and Biomathematics and Statistics Scotland by the Rural and Environment Science and Analytical Services Division of the Scottish Government. S. O. H. was a recipient of a FoRST (NZ) award to study abroad.

Pre-formulation and systematic evaluation of amino acid assisted permeability of insulin across in vitro buccal cell layers

The aim of this work was to investigate alternative safe and effective permeation enhancers for buccal peptide delivery. Basic amino acids improved insulin solubility in water while 200 and 400 µg/mL lysine significantly increased insulin solubility in HBSS. Permeability data showed a significant improvement in insulin permeation especially for 10 µg/mL of lysine (p < 0.05) and 10 µg/mL histidine (p < 0.001), 100 µg/mL of glutamic acid (p < 0.05) and 200 µg/mL of glutamic acid and aspartic acid (p < 0.001) without affecting cell integrity; in contrast to sodium deoxycholate which enhanced insulin permeability but was toxic to the cells. It was hypothesized that both amino acids and insulin were ionised at buccal cavity pH and able to form stable ion pairs which penetrated the cells as one entity; while possibly triggering amino acid nutrient transporters on cell surfaces. Evidence of these transport mechanisms was seen with reduction of insulin transport at suboptimal temperatures as well as with basal-to-apical vectoral transport, and confocal imaging of transcellular insulin transport. These results obtained for insulin is the first indication of a possible amino acid mediated transport of insulin via formation of insulin-amino acid neutral complexes by the ion pairing mechanism.

Organic carbon flux and remineralization in surface sediments

Organic carbon fluxes through the sediment/water interface in the high-latitude North Atlantic were calculated from oxygen microprofiles. A wire-operated in situ oxygen bottom profiler was deployed, and oxygen profiles were also measured onboard (ex situ). Diffusive oxygen fluxes, obtained by fitting exponential functions to the oxygen profiles, were translated into organic carbon fluxes and organic carbon degradation rates. The mean Corg input to the abyssal plain sediments of the Norwegian and Greenland Seas was found to be 1.9 mg C/m**2/d. Typical values at the seasonally ice-covered East Greenland continental margin are between 1.3 and 10.9 mg C/m**2/d (mean 3.7 mg C/m**2/d), whereas fluxes on the East Greenland shelf are considerably higher, 9.1-22.5 mg C/m**2/d. On the Norwegian continental slope Corg fluxes of 3.3-13.9 mg C/m**2/d (mean 6.5 mg C/m**2/d) were found. Fluxes are considerably higher here compared to stations on the East Greenland slope at similar water depths. By repeated occupation of three sites off southern Norway in 1997 the temporal variability of diffusive O2 fluxes was found to be quite low. The seasonal signal of primary and export production from the upper water column appears to be strongly damped at the seafloor. Degradation rates of 0.004-1.1 mg C/cm**3/a at the sediment surface were calculated from the oxygen profiles. First-order degradation constants, obtained from Corg degradation rates and sediment organic carbon content, are in the range 0.03-0.6/a. Thus, the corresponding mean lifetime of organic carbon lies between 1.7 and 33.2 years, which also suggests that seasonal variations in Corg flux are small. The data presented here characterize the Norwegian and Greenland Seas as oligotrophic and relatively low organic carbon deep-sea environments.

Analytical results of 19 amino acid analyses from Unit 3.1 of sediment core CRP-1 (Table 1)

Amino acid-based geochronological analyses were carried out on fossil mollusc shell and foraminifera from Unit 3.1, Cape Roberts Project core CRP-1. Ratios of D-alloIsoleucine to L-Isoleucine (D/L) were measured from 19 fossil samples using cation exchange High Performance Liquid Chromatography (HPLC) methods. Preliminary interpretation of these results suggest that Unit 3.1 contains carbonate fossils having multiple ages. The interpreted ages have a bimodal distribution between ~220 Ka (Quaternary) and ~2.4 Ma (Pliocene). However, these results lack a comprehensive regional and taxonomic context for amino acid studies in Antarctica and therefore should be regarded as preliminary age estimates of fossil shell ages.