The Eukaryotic Promoter Database EPD: the impact of in silico primer extension.

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, experimentally defined by a transcription start site (TSS). There may be multiple promoter entries for a single gene. The underlying experimental evidence comes from journal articles and, starting from release 73, from 5' ESTs of full-length cDNA clones used for so-called in silico primer extension. Access to promoter sequences is provided by pointers to TSS positions in nucleotide sequence entries. The annotation part of an EPD entry includes a description of the type and source of the initiation site mapping data, links to other biological databases and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Web-based interfaces have been developed that enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria and to navigate to related databases exploiting different cross-references. Tools for analysing sequence motifs around TSSs defined in EPD are provided by the signal search analysis server. EPD can be accessed at http://www.epd. isb-sib.ch.

A new approach for potential drug target discovery through in silico metabolic pathway analysis using Trypanosoma cruzi genome information

The current drug options for the treatment of chronic Chagas disease have not been sufficient and high hopes have been placed on the use of genomic data from the human parasite Trypanosoma cruzi to identify new drug targets and develop appropriate treatments for both acute and chronic Chagas disease. However, the lack of a complete assembly of the genomic sequence and the presence of many predicted proteins with unknown or unsure functions has hampered our complete view of the parasite's metabolic pathways. Moreover, pinpointing new drug targets has proven to be more complex than anticipated and has revealed large holes in our understanding of metabolic pathways and their integrated regulation, not only for this parasite, but for many other similar pathogens. Using an in silicocomparative study on pathway annotation and searching for analogous and specific enzymes, we have been able to predict a considerable number of additional enzymatic functions in T. cruzi. Here we focus on the energetic pathways, such as glycolysis, the pentose phosphate shunt, the Krebs cycle and lipid metabolism. We point out many enzymes that are analogous to those of the human host, which could be potential new therapeutic targets.

Megazol and its bioisostere 4H-1,2,4-triazole: comparing the trypanocidal, cytotoxic and genotoxic activities and their in vitro and in silico interactions with the Trypanosoma brucei nitroreductase enzyme

Megazol (7) is a 5-nitroimidazole that is highly active against Trypanosoma cruzi and Trypanosoma brucei, as well as drug-resistant forms of trypanosomiasis. Compound 7 is not used clinically due to its mutagenic and genotoxic properties, but has been largely used as a lead compound. Here, we compared the activity of 7 with its 4H-1,2,4-triazole bioisostere (8) in bloodstream forms of T. brucei and T. cruzi and evaluated their activation by T. brucei type I nitroreductase (TbNTR) enzyme. We also analysed the cytotoxic and genotoxic effects of these compounds in whole human blood using Comet and fluorescein diacetate/ethidium bromide assays. Although the only difference between 7 and 8 is the substitution of sulphur (in the thiadiazole in 7) for nitrogen (in the triazole in 8), the results indicated that 8 had poorer antiparasitic activity than 7 and was not genotoxic, whereas 7 presented this effect. The determination of Vmax indicated that although 8 was metabolised more rapidly than 7, it bounds to the TbNTR with better affinity, resulting in equivalent kcat/KM values. Docking assays of 7 and 8 performed within the active site of a homology model of the TbNTR indicating that 8 had greater affinity than 7.

In silico meets in vivo

A report of the 6th Georgia Tech-Oak Ridge National Lab International Conference on Bioinformatics 'In silico Biology: Gene Discovery and Systems Genomics', Atlanta, USA, 15-17 November, 2007.

Unfolding nature "in silico" : overcoming practical and metodological limitations of species distribution models

Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

Solving ambiguities in contig assembly of Idiomarina loihiensis L2TR chromosome by in silico analyses.

Nucleotide composition analyses of bacterial genomes such as cumulative GC skew highlight the atypical, strongly asymmetric architecture of the recently published chromosome of Idiomarina loihiensis L2TR, suggesting that an inversion of a 600-kb chromosomal segment occurred. The presence of 3.4-kb inverted repeated sequences at the borders of the putative rearrangement supports this hypothesis. Reverting in silico this segment restores (1) a symmetric chromosome architecture; (2) the co-orientation of transcription of all rRNA operons with DNA replication; and (3) a better conservation of gene order between this chromosome and other gamma-proteobacterial ones. Finally, long-range PCRs encompassing the ends of the 600-kb segment reveal the existence of the reverted configuration but not of the published one. This demonstrates how cumulative nucleotide-skew analyses can validate genome assemblies.

TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

Identification of human IKK-2 inhibitors of natural origin (Part II): in Silico prediction of IKK-2 inhibitors in natural extracts with known anti-inflammatory activity.

Human inhibitor NF-κB kinase 2 (hIKK-2) is the primary component responsible for activating NF-κB in response to various inflammatory stimuli. Thus, synthetic ATP-competitive inhibitors for hIKK-2 have been developed as anti-inflammatory compounds. We recently reported a virtual screening protocol (doi:10.1371/journal.pone.0016903) that is able to identify hIKK-2 inhibitors that are not structurally related to any known molecule that inhibits hIKK-2 and that have never been reported to have anti-inflammatory activity. In this study, a stricter version of this protocol was applied to an in-house database of 29,779 natural products annotated with their natural source. The search identified 274 molecules (isolated from 453 different natural extracts) predicted to inhibit hIKK-2. An exhaustive bibliographic search revealed that anti-inflammatory activity has been previously described for: (a) 36 out of these 453 extracts; and (b) 17 out of 30 virtual screening hits present in these 36 extracts. Only one of the remaining 13 hit molecules in these extracts shows chemical similarity with known synthetic hIKK-2 inhibitors. Therefore, it is plausible that a significant portion of the remaining 12 hit molecules are lead-hopping candidates for the development of new hIKK-2 inhibitors.

In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae

Background: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). Results: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. Conclusion: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.

ESTIRIL-LACTONAS DE Cryptocarya aschersoniana Mez. (Lauraceae Juss.) COM ATIVIDADE CONTRA Meloidogyne spp. E INTERAÇÃO IN SILICO COM PROVÁVEL FUMARASE DEMeloidogyne hapla

In a previous study, substances with nematicidal properties were detected in the bark of Cryptocarya aschersoniana. Continuing such study, the methanol extract from this plant underwent fractionation guided by in vitro assays with the plant-parasitic nematode Meloidogyne exigua. Two active compounds were isolated and identified by spectroscopic methods as (E)-6-styrylpyran-2-one and (R)-goniothalamin. The latter compound was also active againstMeloidogyne incognita. In silico studies carried out with (R)-goniothalamin and the enzyme fumarate hydratase, which was extracted from the genome of Meloidogyne hapla and modeled using computational methods, suggested that this substance acts against nematodes by binding to a cavity close to the active site of the enzyme.

In silico phylogenetic and virulence gene profile analyses of avian pathogenic Escherichia coli genome sequences

Avian pathogenic Escherichia coli (APEC) infections are responsible for significant losses in the poultry industry worldwide. A zoonotic risk has been attributed to APEC strains because they present similarities to extraintestinal pathogenic E. coli (ExPEC) associated with illness in humans, mainly urinary tract infections and neonatal meningitis. Here, we present in silico analyses with pathogenic E. coli genome sequences, including recently available APEC genomes. The phylogenetic tree, based on multi-locus sequence typing (MLST) of seven housekeeping genes, revealed high diversity in the allelic composition. Nevertheless, despite this diversity, the phylogenetic tree was able to cluster the different pathotypes together. An in silico virulence gene profile was also determined for each of these strains, through the presence or absence of 83 well-known virulence genes/traits described in pathogenic E. coli strains. The MLST phylogeny and the virulence gene profiles demonstrated a certain genetic similarity between Brazilian APEC strains, APEC isolated in the United States, UPEC (uropathogenic E. coli) and diarrheagenic strains isolated from humans. This correlation corroborates and reinforces the zoonotic potential hypothesis proposed to APEC.

Biomolecular screening for inhibitors of butyrylcholinesterase : identification and characterization using in vitro and in silico tools

Drug discovery is a continuous process where researchers are constantly trying to find new and better drugs for the treatment of various conditions. Alzheimer’s disease, a neurodegenerative disease mostly affecting the elderly, has a complex etiology with several possible drug targets. Some of these targets have been known for years while other new targets and theories have emerged more recently. Cholinesterase inhibitors are the major class of drugs currently used for the symptomatic treatment of Alzheimer’s disease. In the Alzheimer’s disease brain there is a deficit of acetylcholine and an impairment in signal transmission. Acetylcholinesterase has therefore been the main target as this is the main enzyme hydrolysing acetylcholine and ending neurotransmission. It is believed that by inhibiting acetylcholinesterase the cholinergic signalling can be enhanced and the cognitive symptoms that arise in Alzheimer’s disease can be improved. Butyrylcholinesterase, the second enzyme of the cholinesterase family, has more recently attracted interest among researchers. Its function is still not fully known, but it is believed to play a role in several diseases, one of them being Alzheimer’s disease. In this contribution the aim has primarily been to identify butyrylcholinesterase inhibitors to be used as drug molecules or molecular probes in the future. Both synthetic and natural compounds in diverse and targeted screening libraries have been used for this purpose. The active compounds have been further characterized regarding their potencies, cytotoxicity, and furthermore, in two of the publications, the inhibitors ability to also inhibit Aβ aggregation in an attempt to discover bifunctional compounds. Further, in silico methods were used to evaluate the binding position of the active compounds with the enzyme targets. Mostly to differentiate between the selectivity towards acetylcholinesterase and butyrylcholinesterase, but also to assess the structural features required for enzyme inhibition. We also evaluated the compounds, active and non-active, in chemical space using the web-based tool ChemGPS-NP to try and determine the relevant chemical space occupied by cholinesterase inhibitors. In this study, we have succeeded in finding potent butyrylcholinesterase inhibitors with a diverse set of structures, nine chemical classes in total. In addition, some of the compounds are bifunctional as they also inhibit Aβ aggregation. The data gathered from all publications regarding the chemical space occupied by butyrylcholinesterase inhibitors we believe will give an insight into the chemically active space occupied by this type of inhibitors and will hopefully facilitate future screening and result in an even deeper knowledge of butyrylcholinesterase inhibitors.

In silico analysis identifies a C3HC4-RING finger domain of a putative E3 ubiquitin-protein ligase located at the C-terminus of a polyglutamine-containing protein

Almost identical polyglutamine-containing proteins with unknown structures have been found in human, mouse and rat genomes (GenBank AJ277365, AF525300, AY879229). We infer that an identical new gene (RING) finger domain of real interest is located in each C-terminal segment. A three-dimensional (3-D) model was generated by remote homology modeling and the functional implications are discussed. The model consists of 65 residues from terminal position 707 to 772 of the human protein with a total length of 796 residues. The 3-D model predicts a ubiquitin-protein ligase (E3) as a binding site for ubiquitin-conjugating enzyme (E2). Both enzymes are part of the ubiquitin pathway to label unwanted proteins for subsequent enzymatic degradation. The molecular contact specificities are suggested for both the substrate recognition and the residues at the possible E2-binding surface. The predicted structure, of a ubiquitin-protein ligase (E3, enzyme class number 6.3.2.19, CATH code 3.30.40.10.4) may contribute to explain the process of ubiquitination. The 3-D model supports the idea of a C3HC4-RING finger with a partially new pattern. The putative E2-binding site is formed by a shallow hydrophobic groove on the surface adjacent to the helix and one zinc finger (L722, C739, P740, P741, R744). Solvent-exposed hydrophobic amino acids lie around both zinc fingers (I717, L722, F738, or P765, L766, V767, V733, P734). The 3-D structure was deposited in the protein databank theoretical model repository (2B9G, RCSB Protein Data Bank, NJ).

Predição in silico de marcadores microssatélites relacionados ao tegumento de sementes de soja

O sucesso na obtenção de altas produtividades de soja depende da utilização de sementes de qualidade. Muitos problemas que comprometem a qualidade fisiológica das sementes podem ser relacionados às características do tegumento. Inúmeros trabalhos afirmam que sementes de soja com tegumento semipermeável à água apresentam maior tolerância a patógenos e pragas, menor susceptibilidade aos danos mecânicos, às adversidades climáticas e à deterioração por umidade. A inclusão das características de tegumento semipermeável nas cultivares atuais pode minimizar problemas relacionados à qualidade de sementes. Neste contexto, aliar as técnicas da biologia molecular com a bioinformática é uma importante estratégia para identificação dos genes envolvidos com o tegumento e com a fisiologia de sementes. O objetivo desse trabalho foi descrever e avaliar uma estratégia de utilização de ferramentas da bioinformática, para a integração in silico de informações de experimentos in vitro de marcadores moleculares, contra dados armazenados em bancos de dados genômicos e prever pela descrição funcional se estes marcadores podem estar associados a diferentes características do tegumento da soja. Foram utilizados 24 conjuntos de primers microssatélites, avaliados anteriormente e que amplificaram fragmentos polimórficos entre os genótipos de soja CD-202 (tegumento amarelo, permeável e susceptível à deterioração) e uma linhagem TP (tegumento preto, semipermeável e resistente a deterioração). Os resultados desta análise indicam como promissor o uso destes marcadores para estudos relacionados ao tegumento e à qualidade de sementes de soja. A estratégia da mineração de marcadores moleculares a partir da integração in silico de sequências de marcadores moleculares ainda anônimos, bancos de dados genômicos e bancos contendo seqüências com descrições funcionais dos genes demonstra ser promissora, pois, possibilita prever as funções para estes genes e verificar a associação destes com rotas bioquímicas e metabólicas responsáveis pelas características que se deseja analisar em rotinas in vitro.