Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

Measuring the influence of similarity on category-specific effects

There is evidence for both advantages and disadvantages in normal recognition of living over nonliving things. This paradox has been attributed to high levels of perceptual similarity within living categories having a different effect on performance in different contexts. However, since living things are intrinsically more similar to each other, previous studies could not determine whether the various category effects were due to perceptual similarity, or to other characteristics of living things. We used novel animal and vehicle stimuli that were matched for similarity to measure the influence of perceptual similarity in different contexts. We found that displaying highly similar objects in blocked sets reduced their perceived similarity, eliminating the detrimental effect on naming performance. Experiment 1 demonstrated a disadvantage for highly similar objects in name learning and name verification using mixed groups of similar and dissimilar animals and vehicles. Experiment 2 demonstrated no disadvantage for the same highly similar objects when they were blocked, e.g., similar animals presented alone. Thus, perceptual similarity, rather than other characteristics particular to living things, is affected by context, and could create apparent category effects under certain testing conditions.

Present perspectives on the automated classification of the G-protein coupled receptors (GPCRs) at the protein sequence level

The G-protein coupled receptors--or GPCRs--comprise simultaneously one of the largest and one of the most multi-functional protein families known to modern-day molecular bioscience. From a drug discovery and pharmaceutical industry perspective, the GPCRs constitute one of the most commercially and economically important groups of proteins known. The GPCRs undertake numerous vital metabolic functions and interact with a hugely diverse range of small and large ligands. Many different methodologies have been developed to efficiently and accurately classify the GPCRs. These range from motif-based techniques to machine learning as well as a variety of alignment-free techniques based on the physiochemical properties of sequences. We review here the available methodologies for the classification of GPCRs. Part of this work focuses on how we have tried to build the intrinsically hierarchical nature of sequence relations, implicit within the family, into an adaptive approach to classification. Importantly, we also allude to some of the key innate problems in developing an effective approach to classifying the GPCRs: the lack of sequence similarity between the six classes that comprise the GPCR family and the low sequence similarity to other family members evinced by many newly revealed members of the family.

VaxiJen:a server for prediction of protective antigens, tumour antigens and subunit vaccines

Background - Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties. Results - Bacterial, viral and tumour protein datasets were used to derive models for prediction of whole protein antigenicity. Every set consisted of 100 known antigens and 100 non-antigens. The derived models were tested by internal leave-one-out cross-validation and external validation using test sets. An additional five training sets for each class of antigens were used to test the stability of the discrimination between antigens and non-antigens. The models performed well in both validations showing prediction accuracy of 70% to 89%. The models were implemented in a server, which we call VaxiJen. Conclusion - VaxiJen is the first server for alignment-independent prediction of protective antigens. It was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. The server can be used on its own or in combination with alignment-based prediction methods.

Some historical extracts relevant to the discovery and application of the diffraction of X-rays by crystals to contribute to the centennial celebration and the International Year of Crystallography

Illustrative extracts from the writings of Paul P. Ewald and of Max von Laue are presented. The latter in turn contains extensive text contributions from William Lawrence Bragg. These selections we have chosen so as to indicate the nature of the discovery of X-ray diffraction from crystals (experiments undertaken by Friedrich, Knipping and von Laue) and its early and prompt application in crystal structure analyses (by William Henry Bragg and William Lawrence Bragg). The platform for these discoveries was provided by a macroscopic physics problem dealt with by Ewald in his doctoral thesis with Arnold Sommerfeld in the Munich Physics Department, which is also where von Laue was based. W.L. Bragg was a student in Cambridge who used Trinity College Cambridge as his address on his early papers; experimental work was done by him in the Cavendish Laboratory, Cambridge, and also with his father, W.H. Bragg, in the Leeds University Physics Department. Of further historical interest is the award of an Honorary DSc (Doctor of Science) degree in 1936 to Max von Laue by the University of Manchester, UK, while William Lawrence Bragg was Langworthy Professor of Physics there. © 2012 Copyright Taylor and Francis Group, LLC.

Systematic review of Late Jurassic sauropods from the Museu Geológico collections (Lisboa, Portugal)

The Museu Geológico collections house some of the first sauropod references of the Lusitanian Basin Upper Jurassic record, including the Lourinhasaurus alenquerensis and Lusotitan atalaiensis lectotypes, previously considered as new species of the Apatosaurus and Brachiosaurus genera, respectively. Several fragmentary specimens have been classical referred to those taxa, but the most part of these systematic attributions are not supported herein, excluding a caudal vertebra from Maceira (MG 8804) considered as cf. Lusotitan atalaiensis. From the material housed in the Museu Geológico were identified basal eusauropods (indeterminate eusauropods and turiasaurs) and neosauropods (indeterminate neosauropods, diplodods and camarasaurids and basal titanosauriforms). Middle caudal vertebrae with lateral fossae, ventral hollow border by pronounced ventrolateral crests and quadrangular cross-section suggest for the presence of diplodocine diplodocids in north area of the Lusitanian Basin Central Sector during the Late Jurassic. A humerus collected from Praia dos Frades (MG 4976) is attributed to cf. Duriatitan humerocristatus suggesting the presence of shared sauropod forms between the Portugal and United Kingdom during the Late Jurassic. Duriatitan is an indeterminate member of Eusauropoda and the discovery of new material in both territories is necessary to confirm this systematic approach. The studied material is in according with the previous recorded paleobiodiversity for the sauropod clade during the Portuguese Late Jurassic, which includes basal eusauropods (including turiasaurs), diplodocids and macronarians (including camarasaurids and basal titanosauriforms).

Discovery and settlement of Alaska coaster

Tsar Peter the Great ruled Russia between 1689 and 1725. Its domains, stretching from the Baltic Sea in the west to the Pacific Ocean in the east. From north to south, its empire stretching from the Arctic Ocean to the borders with China and India. Tsar Peter I tried to extend the geographical knowledge of his government and the rest of the world. He was also interested in the expansion of trade in Russia and in the control of trade routes. Feodor Luzhin and Ivan Yeverinov explored the eastern border of the Russian Empire, the trip between 1719 and 1721 and reported to the Tsar. They had crossed the peninsula of Kamchatka, from west to east and had traveled from the west coast of Kamchatka to the Kuril Islands. The information collected led to the first map of Kamchatka and the Kuril Islands. Tsar Peter ordered Bering surf the Russian Pacific coast, build ships and sail the seas north along the coast to regions of America. The second expedition found equal to those of the previous explorers difficulties. Two ships were eventually thrown away in Okhotsk in 1740. The explorers spent the winter of 1740-1741 stockpiling supplies and then navigate to Petropavlovsk. The two ships sailed eastward and did together until June 20, then separated by fog. After searching Chirikov and his boat for several days, Bering ordered the San Pedro continue to the northeast. There the Russian sailors first sighted Alaska. According to the log, "At 12:30 (pm July 17) in sight of snow-capped mountains and between them a high volcano." This finding came the day of St. Elijah and so named the mountain.

On the effect of word frequency on distributional similarity

The dependency of word similarity in vector space models on the frequency of words has been noted in a few studies, but has received very little attention. We study the influence of word frequency in a set of 10 000 randomly selected word pairs for a number of different combinations of feature weighting schemes and similarity measures. We find that the similarity of word pairs for all methods, except for the one using singular value decomposition to reduce the dimensionality of the feature space, is determined to a large extent by the frequency of the words. In a binary classification task of pairs of synonyms and unrelated words we find that for all similarity measures the results can be improved when we correct for the frequency bias.

Comparison of the modes of action of Apremilast and Roflumilast

The phosphodiesterase 4 (PDE4) family are cAMP specific phosphodiesterases that play an important role in the inflammatory response and is the major PDE type found in inflammatory cells. A significant number of PDE4 specific inhibitors have been developed and are currently being investigated for use as therapeutic agents. Apremilast, a small molecule inhibitor of PDE 4 is in development for chronic inflammatory disorders and has shown promise for the treatment of psoriasis, psoriatic arthritis as well as other inflammatory diseases. It has been found to be safe and well tolerated in humans and in March 2014 it was approved by the US food and drug administration for the treatment of adult patients with active psoriatic arthritis. The only other PDE4 inhibitor on the market is Roflumilast and it is used for treatment of respiratory disease. Roflumilast is approved in the EU for the treatment of COPD and was recently approved in the US for treatment to reduce the risk of COPD exacerbations. Roflumilast is also a selective PDE4 inhibitor, administered as an oral tablet once daily, and is thought to act by increasing cAMP within lung cells. As both (Apremilast and Roflumilast) compounds selectively inhibit PDE4 but are targeted at different diseases, there is a need for a clear understanding of their mechanism of action (MOA). Differences and similarity of MOA should be defined for the purposes of labelling, for communication to the scientific community, physicians, and patients, and for an extension of utility to other diseases and therapeutic areas. In order to obtain a complete comparative picture of the MOA of both inhibitors, additional molecular and cellular biology studies are required to more fully elucidate the signalling mediators downstream of PDE4 inhibition which result in alterations in pro- and anti-inflammatory gene expression. My studies were conducted to directly compare Apremilast with Roflumilast, in order to substantiate the differences observed in the molecular and cellular effects of these compounds, and to search for other possible differentiating effects. Therefore the main aim of this thesis was to utilise cutting-edge biochemical techniques to discover whether Apremilast and Roflumilast work with different modes of action. In the first part of my thesis I used novel genetically encoded FRET based cAMP sensors targeted to different intracellular compartments, in order to monitor cAMP levels within specific microdomains of cells as a consequence of challenge with Apremilast and Roflumilast, which revealed that Apremilast and Roflumilast do regulate different pools of cAMP in cells. In the second part of my thesis I focussed on assessing whether Apremilast and Roflumilast cause differential effects on the PKA phosphorylation state of proteins in cells. I used various biochemical techniques (Western blotting, Substrate kinase arrays and Reverse Phase Protein array and found that Apremilast and Roflumilast do lead to differential PKA substrate phosphorylation. For example I found that Apremilast increases the phosphorylation of Ribosomal Protein S6 at Ser240/244 and Fyn Y530 in the S6 Ribosomal pathway of Rheumatoid Arthritis Synovial fibroblast and HEK293 cells, whereas Roflumilast does not. This data suggests that Apremilast has distinct biological effects from that of Roflumilast and could represent a new therapeutic role for Apremilast in other diseases. In the final part of my thesis, Phage display technology was employed in order to identify any novel binding motifs that associate with PDE4 and to identify sequences that were differentially regulated by the inhibitors in an attempt to find binding motifs that may exist in previously characterised signalling proteins. Petide array technology was then used to confirm binding of specific peptide sequences or motifs. Results showed that Apremilast and Roflumilast can either enhance or decrease the binding of PDE4A4 to specific peptide sequences or motifs that are found in a variety of proteins in the human proteome, most interestingly Ubiquitin-related proteins. The data from this chapter is preliminary but may be used in the discovery of novel binding partners for PDE4 or to provide a new role for PDE inhibition in disease. Therefore the work in this thesis provides a unique snapshot of the complexity of the cAMP signalling system and is the first to directly compare action of the two approved PDE4 inhibitors in a detailed way.

Development of a novel platform for high-throughput gene design and artificial gene synthesis to produce large libraries of recombinant venom peptides for drug discovery

Tese de Doutoramento em Ciências Veterinárias na Especialidade de Ciências Biológicas e Biomédicas

Generation and screening of natural product-like compounds for antibiotic discovery

Avec l’apparition de plus en plus de souches de bactérie résistante aux antibiotiques, le développement de nouveaux antibiotiques est devenu une important problématique pour les agences de santé. C’est pour cela que la création de nouvelles plateformes pour accélérer la découverte de médicaments est devenu un besoin urgent. Dans les dernières décennies, la recherche était principalement orientée sur la modification de molécules préexistantes, la méta-analyse d’organismes produisant des molécules activent et l’analyse de librairies moléculaires pour trouver des molécules synthétiques activent, ce qui s’est avéré relativement inefficace. Notre but était donc de développer de nouvelles molécules avec des effets thérapeutiques de façon plus efficace à une fraction du prix et du temps comparé à ce qui se fait actuellement. Comme structure de base, nous avons utilisé des métabolites secondaires qui pouvaient altérer le fonctionnement des protéines ou l’interaction entre deux protéines. Pour générer ces molécules, j’ai concentré mes efforts sur les terpènes, une classe de métabolites secondaires qui possède un large éventail d’activités biologiques incluant des activités antibactériennes. Nous avons développé un système de chromosome artificiel de levure (YAC) qui permet à la fois l’assemblage directionnel et combinatoire de gènes qui permet la création de voies de biosynthèse artificielles. Comme preuve de concept, j’ai développé des YACs qui contiennent les gènes pour l’expression des enzymes impliquées dans la biosynthèse de la -carotène et de l’albaflavenone et produit ces molécules avec un haut rendement. Finalement, Des YACs produits à partir de librairies de gènes ont permis de créer une grande diversité de molécules.

Generation and screening of natural product-like compounds for antibiotic discovery

Avec l’apparition de plus en plus de souches de bactérie résistante aux antibiotiques, le développement de nouveaux antibiotiques est devenu une important problématique pour les agences de santé. C’est pour cela que la création de nouvelles plateformes pour accélérer la découverte de médicaments est devenu un besoin urgent. Dans les dernières décennies, la recherche était principalement orientée sur la modification de molécules préexistantes, la méta-analyse d’organismes produisant des molécules activent et l’analyse de librairies moléculaires pour trouver des molécules synthétiques activent, ce qui s’est avéré relativement inefficace. Notre but était donc de développer de nouvelles molécules avec des effets thérapeutiques de façon plus efficace à une fraction du prix et du temps comparé à ce qui se fait actuellement. Comme structure de base, nous avons utilisé des métabolites secondaires qui pouvaient altérer le fonctionnement des protéines ou l’interaction entre deux protéines. Pour générer ces molécules, j’ai concentré mes efforts sur les terpènes, une classe de métabolites secondaires qui possède un large éventail d’activités biologiques incluant des activités antibactériennes. Nous avons développé un système de chromosome artificiel de levure (YAC) qui permet à la fois l’assemblage directionnel et combinatoire de gènes qui permet la création de voies de biosynthèse artificielles. Comme preuve de concept, j’ai développé des YACs qui contiennent les gènes pour l’expression des enzymes impliquées dans la biosynthèse de la -carotène et de l’albaflavenone et produit ces molécules avec un haut rendement. Finalement, Des YACs produits à partir de librairies de gènes ont permis de créer une grande diversité de molécules.

SNP technologies for drug discovery : a current review

Single nucleotide polymorphisms (SNPs) are unique genetic differences between individuals that contribute in significant ways to the determination of human variation including physical characteristics like height and appearance as well as less obvious traits such as personality, behaviour and disease susceptibility. SNPs can also significantly influence responses to pharmacotherapy and whether drugs will produce adverse reactions. The development of new drugs can be made far cheaper and more rapid by selecting participants in drug trials based on their genetically determined response to drugs. Technology that can rapidly and inexpensively genotype thousands of samples for thousands of SNPs at a time is therefore in high demand. With the completion of the human genome project, about 12 million true SNPs have been identified to date. However, most have not yet been associated with disease susceptibility or drug response. Testing for the appropriate drug response SNPs in a patient requiring treatment would enable individualised therapy with the right drug and dose administered correctly the first time. Many pharmaceutical companies are also interested in identifying SNPs associated with polygenic traits so novel therapeutic targets can be discovered. This review focuses on technologies that can be used for genotyping known SNPs as well as for the discovery of novel SNPs associated with drug response.

High porosity chained aggregates from the topsoil of the lunar regolith dust

The unusual behaviour of fine lunar regolith like stickiness and low heat conductivity is dominated by the structural arrangement of its finest fraction. Here, we show the previously unknown phenomenon of a globular 3D superstructure within the dust fraction of regolith. A study using the recently developed Transmission X-ray Microscopy (TXM) with tomographic reconstruction reveals a highly porous network of cellular voids in the finest dust fraction aggregates in lunar soil. Such porous chained aggregates are composed of sub-micron particles that form a network of cellular voids a few micrometers in diameter. Discovery of such a superstructure within the finest fraction of lunar topsoil enables a model of heat transfer to be constructed.

A re-examination of the Ghrelin and Ghrelin receptor genes

The last few years have seen dramatic advances in genomics, including the discovery of a large number of non-coding and antisense transcripts. This has revolutionised our understanding of multifaceted transcript structures found within gene loci and their roles in the regulation of development, neurogenesis and other complex processes. The recent and continuing surge of knowledge has prompted researchers to reassess and further dissect gene loci. The ghrelin gene (GHRL) gives rise to preproghrelin, which in turn produces ghrelin, a 28 amino acid peptide hormone that acts via the ghrelin receptor (growth hormone secretagogue receptor/GHSR 1a). Ghrelin has many important physiological and pathophysiological roles, including the stimulation of growth hormone (GH) release, appetite regulation, and cancer development. A truncated receptor splice variant, GHSR 1b, does not bind ghrelin, but dimerises with GHSR 1a, and may act as a dominant negative receptor. The gene products of ghrelin and its receptor are frequently overexpressed in human cancer While it is well known that the ghrelin axis (ghrelin and its receptor) plays a range of important functional roles, little is known about the molecular structure and regulation of the ghrelin gene (GHRL) and ghrelin receptor gene (GHSR). This thesis reports the re-annotation of the ghrelin gene, discovery of alternative 5’ exons and transcription start sites, as well as the description of a number of novel splice variants, including isoforms with a putative signal peptide. We also describe the discovery and characterisation of a ghrelin antisense gene (GHRLOS), and the discovery and expression of a ghrelin receptor (growth hormone secretagogue receptor/GHSR) antisense gene (GHSR-OS). We have identified numerous ghrelin-derived transcripts, including variants with extended 5' untranslated regions and putative secreted obestatin and C-ghrelin transcripts. These transcripts initiate from novel first exons, exon -1, exon 0 and a 5' extended 1, with multiple transcription start sites. We used comparative genomics to identify, and RT-PCR to experimentally verify, that the proximal exon 0 and 5' extended exon 1 are transcribed in the mouse ghrelin gene, which suggests the mouse and human proximal first exon architecture is conserved. We have identified numerous novel antisense transcripts in the ghrelin locus. A candidate non-coding endogenous natural antisense gene (GHRLOS) was cloned and demonstrates very low expression levels in the stomach and high levels in the thymus, testis and brain - all major tissues of non-coding RNA expression. Next, we examined if transcription occurs in the antisense orientation to the ghrelin receptor gene, GHSR. A novel gene (GHSR-OS) on the opposite strand of intron 1 of the GHSR gene was identified and characterised using strand-specific RT-PCR and rapid amplification of cDNA ends (RACE). GHSR-OS is differentially expressed and a candidate non-coding RNA gene. In summary, this study has characterised the ghrelin and ghrelin receptor loci and demonstrated natural antisense transcripts to ghrelin and its receptor. Our preliminary work shows that the ghrelin axis generates a broad and complex transcriptional repertoire. This study provides the basis for detailed functional studies of the the ghrelin and GHSR loci and future studies will be needed to further unravel the function, diagnostic and therapeutic potential of the ghrelin axis.