Structure-function analysis of amino acid 74 of human RAMP1 and RAMP3 and its role in peptide interactions with adrenomedullin and calcitonin gene-related peptide receptors

The receptors for calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) are complexes of the calcitonin receptor-like receptor (CLR) and receptor activity-modifying proteins (RAMP). The CGRP receptor is a CLR/RAMP1 pairing whereas CLR/RAMP2 and CLR/RAMP3 constitute two subtypes of AM receptor: AM(1) and AM(2), respectively. Previous studies identified Glu74 in RAMP3 to be important for AM binding and potency. To further understand the importance of this residue and its equivalent in RAMP1 (Trp74) we substituted the native amino acids with several others. In RAMP3, these were Trp, Phe, Tyr, Ala, Ser, Thr, Arg and Asn; in RAMP1, Glu, Phe, Tyr, Ala and Asn substitutions were made. The mutant RAMPs were co-expressed with CLR in Cos7 cells; receptor function in response to AM, AM(2)/intermedin and CGRP was measured in a cAMP assay and cell surface expression was determined by ELISA. Phe reduced AM potency in RAMP3 but had no effect in RAMP1. In contrast, Tyr had no effect in RAMP3 but enhanced AM potency in RAMP1. Most other substitutions had a small effect on AM potency in both receptors whereas there was little impact on CGRP or AM(2) potency. Overall, these data suggest that the geometry and charge of the residue at position 74 contribute to how AM interacts with the AM(2) and CGRP receptors and confirms the role of this position in dictating differential AM pharmacology at the AM(2) and CGRP receptors.

On the utility of alternative amino acid scripts

In this work we propose the hypothesis that replacing the current system of representing the chemical entities known as amino acids using Latin letters with one of several possible alternative symbolic representations will bring significant benefits to the human construction, modification, and analysis of multiple protein sequence alignments. We propose ways in which this might be done without prescribing the choice of actual scripts used. Specifically we propose and explore three ways to encode amino acid texts using novel symbolic alphabets free from precedents. Primary orthographic encoding is the direct substitution of a new alphabet for the standard, Latin-based amino acid code. Secondary encoding imposes static residue groupings onto the orthography of the alphabet by manipulating the shape and/or orientation of amino acid symbols. Tertiary encoding renders each residue as a composite symbol; each such symbol thus representing several alternative amino acid groupings simultaneously. We also propose that the use of a new group-focussed alphabet will free the colouring of amino acid residues often used as a tool to facilitate the representation or construction of multiple alignments for other purposes, possibly to indicate dynamic properties of an alignment such as position-wise residue conservation.

Investigation of formulation and process of lyophilised orally disintegrating tablet (ODT) using novel amino acid combination

Lyophilised orally disintegrating tablets (ODTs) have achieved a great success in overcoming dysphagia associated with conventional solid dosage forms. However, the extensive use of saccharides within the formulation limits their use in treatment of chronic illnesses. The current study demonstrates the feasibility of using combination of proline and serine to formulate zero sacharide ODTs and investigates the effect of freezing protocol on sublimation rate and tablets characteristics. The results showed that inclusion of proline and serine improved ODT properties when compared to individual counterparts. Additionally, annealing the ODTs facilitated the sublimation process and shortened the disintegration time. © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.

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.

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.

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.

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.