Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. 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 are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Benchmarking the knowledge competitiveness of the globe's high performing regions:a review of the World Knowledge Competitiveness Index

Purpose – The purpose of this paper is to analyze the way in which the knowledge competitiveness of regions is measured and further introduces the World Knowledge Competitiveness Index (WKCI) benchmarking tool. Design/methodology/approach – The methodology consists of an econometric analysis of key indicators relating to the concept of knowledge competitiveness for 125 regions from across the globe consisting of 55 representatives from North America, 45 from Europe and 25 from Asia and Oceania. Findings – The key to winning the super competitive race in the knowledge-based economy is investment in the future: research and development, and education and training. It is found that the majority of the high-performing regional economies in the USA have a knowledge competitive edge over their counterparts in Europe and Asia. Research limitations/implications – To an extent, the research is limited by the availability of comparable indicators and metrics at the regional level that extend across the globe. Whilst comparative data are often accessible at the national level, regional data sources remain underdeveloped. Practical implications – The WKCI has become internationally recognized as an important instrument for economic development policymakers and regional investment promotion agents as they create and refine their strategies and targets. In particular, it has provided a benchmark that allows regions to compare their knowledge competitiveness with other regions for around the world and not only their own nation or continent. Originality/value – The WKCI is the first composite and relative measure of the knowledge competitiveness of the globe's best performing regions.

Amino acid-modified spray-dried powders with enhanced aerosolisation properties for pulmonary drug delivery

In this study, the amino acids arginine, aspartic acid, leucine, phenylalanine and threonine were investigated as 'dispersibility enhancers' in spray-dried powders for inhalation. Parameters such as spray-dried yield, tapped density, and Carr's Index were not predictive of aerosolisation performance. In addition, whilst the majority of amino acid-modified powders displayed suitable particle size distribution for pulmonary administration and potentially favourable low moisture content, in vitro particle deposition was only enhanced for the leucine-modified powder. In summary, leucine can be used to enhance the dispersibility and aerosolisation properties of spray-dried powders for pulmonary drug delivery. © 2007 Elsevier B.V. All rights reserved.

Productivity change in the water industry in England and Wales:application of the meta-Malmquist Index

This paper uses a meta-Malmquist index for measuring productivity change of the water industry in England and Wales and compares this to the traditional Malmquist index. The meta-Malmquist index computes productivity change with reference to a meta-frontier, it is computationally simpler and it is circular. The analysis covers all 22 UK water companies in existence in 2007, using data over the period 1993–2007. We focus on operating expenditure in line with assessments in this field, which treat operating and capital expenditure as lacking substitutability. We find important improvements in productivity between 1993 and 2005, most of which were due to frontier shifts rather than catch up to the frontier by companies. After 2005, the productivity shows a declining trend. We further use the meta-Malmquist index to compare the productivities of companies at the same and at different points in time. This shows some interesting results relating to the productivity of each company relative to that of other companies over time, and also how the performance of each company relative to itself over 1993–2007 has evolved. The paper is grounded in the broad theory of methods for measuring productivity change, and more specifically on the use of circular Malmquist indices for that purpose. In this context, the contribution of the paper is methodological and applied. From the methodology perspective, the paper demonstrates the use of circular meta-Malmquist indices in a comparative context not only across companies but also within company across time. This type of within-company assessment using Malmquist indices has not been applied extensively and to the authors’ knowledge not to the UK water industry. From the application perspective, the paper throws light on the performance of UK water companies and assesses the potential impact of regulation on their performance. In this context, it updates the relevant literature using more recent data.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

Comparative study of dexamethasone and vancomycin release behavior from stimuli-sensitive microgel aqueous dispersions

Stimuli-sensitive microgels of poly(N-isopropylacrylamide-co-acrylic acid) (designated as P(NIPAAm-co-AA)) were prepared through precipitation polymerization. Their capacity to load and release different drugs under different conditions, including physiological, in a controlled manner was analyzed. Two drugs were assayed and compared: dexamethasone and vancomycin. The prepared microgel particles show good thermosensitivity. In addition, the amount of cross-linker used in the preparation of the microgels does not greatly influence the drug-release capability of P(NIPAAm-co-AA)), but the amount of drug used to load the microgels did result in bigger amounts of drug released afterwards. These results imply potential application of prepared stimuli-sensitive microgel dispersions as drug-delivery systems and tissue engineering materials.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

Comparative physical, mechanical and crystallographic properties of a series of gemfibrozil salts

Objectives Understanding the impact of the counterion on the properties of an acidic or basic drug may influence the choice of salt form, especially for less potent drugs with a high drug load per unit dose. The aim of this work was to determine the influence of the hydrogen bonding potential of the counterion on the crystal structure of salts of the poorly soluble, poorly compressible, acidic drug gemfibrozil and to correlate these with mechanical properties. Methods Compacts of the parent drug and the salts were used to determine Young's modulus of elasticity using beam bending tests. Crystal structures were determined previously from X-ray powder diffraction data. Key findings The free acid, tert-butylamine, 2-amino-2-methylpropan-1-ol and 2-amino-2-methylpropan-1, 3-diol salts had a common crystal packing motif of infinite hydrogen-bonded chains with cross-linking between pairs of adjacent chains. The tromethamine (trsi) salt, with different mechanical properties, had a two-dimensional sheet-like network of hydrogen bonds, with slip planes, forming a stiffer compact. Conclusions The type of counter ion is important in determining mechanical properties and could be selected to afford slip and plastic deformation. © 2010 Royal Pharmaceutical Society of Great Britain.