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At least 145 records · Page 8Linked to original sources
PubMed2001

The computational prediction of toxicity.

Recent developments in the prediction of toxicity from chemical structure have been reviewed. Attention has been drawn to some of the problems that can be encountered in the area of predictive toxicology, including the need for a multi-disciplinary approach and the need to address mechanisms of action. Progress has been hampered by the sparseness of good quality toxicological data. Perhaps too much effort has been devoted to exploring new statistical methods rather than to the creation of data sets for hitherto uninvestigated toxicological endpoints and/or classes of chemicals.

Carcinogens↗
PubMed2006

Computational prediction of novel components of lung transcriptional networks.

MOTIVATION: Little is known regarding the transcriptional mechanisms involved in forming and maintaining epithelial cell lineages of the mammalian respiratory tract. RESULTS: Herein, a motif discovery approach was used to identify novel transcriptional regulators in the lung using genes previously found to be regulated by Foxa2 or Wnt signaling pathways. A human-mouse comparison of both novel and known motifs was also performed. Some of the factors and families identified here were previously shown to be involved epithelial cell differentiation (ETS family, HES-1 and MEIS-1), and ciliogenesis (RFX family), but have never been characterized in lung epithelia. Other unidentified over-represented motifs suggest the existence of novel mammalian lung transcription factors. Of the fraction of motifs examined we describe 25 transcription factor family predictions for lung. Fifteen novel factors were shown here to be expressed in mouse lung, and/or human bronchial or distal lung epithelial tissues or lung epithelial cell lineages. AVAILABILITY: DME: http://rulai.cshl.edu/dme. MATCOMPARE: http://rulai.cshl.edu/MatCompare. MOTIFCLASS is available from the authors.

Algorithms↗
PubMed2005

Computational prediction and experimental verification of novel IdeR binding sites in the upstream sequences of Mycobacterium tuberculosis open reading frames.

IdeR (iron-dependent regulator) is a key regulator of virulence factors and iron acquisition systems in Mycobacterium tuberculosis. Despite the wealth of information available on IdeR-regulated genes of M.tuberculosis, there is still an underlying possibility that there are novel genes/pathways that have gone undetected, the identification of which could give new insights into understanding the pathogenesis of M.tuberculosis. We describe an in silico approach employing the positional relative entropy method to identify potential IdeR binding sites in the upstream sequences of all the 3919 ORFs of M.tuberculosis. While many of the predictions made by this approach overlapped with the ones already identified by microarray experiments and binding assays, pointing to the accuracy of our method, a few genes for which there has been no evidence for IdeR regulation were additionally identified. Our results have implications on the iron-dependent regulatory mechanism of M.tuberculosis vis-a-vis the activity of urease operon and novel transcription regulators and transporters.

Bacterial Proteins↗
PubMed1990

Computer prediction of the exon-intron structure of mammalian pre-mRNAs.

A novel approach to the problem of prediction of protein-coding regions is suggested. This approach combines the site prediction methods to predict splicing sites and the global coding region prediction methods to choose the best variant of spliced mRNA. One of the advantages of the suggested algorithm is that the resulting mRNA or protein sequence may then be immediately analyzed further. The true mRNA either coincides with the predicted one or ranks high in the list of variants. In the latter situation the predicted mRNA usually differs from the true one in only one or two of several exons. The combined approach allows the use of a priori information (e.g. the putative protein length or the number of exons). It is possible to use additional parameters not considered here, such as the preferred lengths of exons and introns, and particularly the preferred position of introns in the reading frame and the preferred codon position of exon termini.

Actins↗
PubMed2000

Trypsin-specific acyl-4-guanidinophenyl esters for alpha-chymotrypsin-catalysed reactions computational predictions, hydrolyses, and peptide bond formation.

The function of acyl-4-guanidinophenyl esters as substrate mimetics for the serine protease alpha-chymotrypsin was investigated by protein-ligand docking, hydrolysis, and acyl transfer experiments. On the basis of protein-ligand docking studies, the binding and hydrolysis properties of these artificial substrates were estimated. The predictions of the rational approach were confirmed by steady-state hydrolysis studies on 4-guanidinophenyl esters derived from coded amino acids (which alpha-chymotrypsin is not specific for), noncoded amino acids, and even simple carboxylic acid moieties. Enzymatic peptide syntheses qualify these esters as suitable acyl donors for the coupling of acyl components far from the natural enzyme specificity, thus considerably expanding the synthetic utility of alpha-chymotrypsin.

Amino Acids↗
PubMed2006

Computational prediction of microRNA genes in silkworm genome.

MicroRNAs (miRNAs) constitute a novel, extensive class of small RNAs (approximately 21 nucleotides), and play important gene-regulation roles during growth and development in various organisms. Here we conducted a homology search to identify homologs of previously validated miRNAs from silkworm genome. We identified 24 potential miRNA genes, and gave each of them a name according to the common criteria. Interestingly, we found that a great number of newly identified miRNAs were conserved in silkworm and Drosophila, and family alignment revealed that miRNA families might possess single nucleotide polymorphisms. miRNA gene clusters and possible functions of complement miRNA pairs are discussed.

Animals↗
PubMed2006

Computational prediction of RpoS and RpoD regulatory sites in Geobacter sulfurreducens using sequence and gene expression information.

RpoS, the sigma S subunit of RNA polymerase, is vital during the growth and survival of Geobacter sulfurreducens under conditions typically encountered in its native subsurface environments. We investigated the conservation of sites that may be important for RpoS function in G. sulfurreducens. We also employed sequence information and expression microarray data to predict G. sulfurreducens genome sites that may be related to RpoS regulation. Hierarchical clustering identified three clusters of significantly downregulated genes in the rpoS deletion mutant. The search for conserved overrepresented motifs in co-regulated operons identified likely -35 and -10 promoter elements upstream of a number of functionally important G. sulfurreducens operons that were downregulated in the rpoS deletion mutant. Putative -35/-10 promoter elements were also identified in the G. sulfurreducens genome using sequence similarity searches to matrices of -35/-10 promoter elements found in G. sulfurreducens and in Escherichia coli. Due to a sufficient degree of sequence similarity between -35/-10 promoter elements for RpoS, RpoD, and other sigma factors, both the sequence similarity searches and the search for conserved overrepresented motifs using microarray data may identify promoter elements for both RpoS and other sigma factors.

Amino Acid Sequence↗
PubMed2005

Artificial neural network computer prediction of ovarian malignancy in women with adnexal masses.

OBJECTIVE: Assessment of the usefulness of a neural model to predict which ovarian tumors are malignant. METHOD: Age, menopausal status, body mass index, grayscale and Doppler ultrasonographic features, as well as levels of specific markers (CA 125, tissue polypeptide specific antigen) were examined in 686 women with adnexal masses. The probability of malignancy was calculated using an artificial neural network software and the diagnostic efficiency of the received model was estimated using a receiver-operating characteristics (ROC) curve. RESULT: Of the 686 women, 431 (62.8%) had a benign and 255 (37.2%) had a malignant ovarian tumor. The significant malignancy predictors are age, menopausal status, maximum tumor diameter, internal wall structure of tumor, presence of septa and/or solid elements, tumor location, location of vessels, and blood flow indexes. The best network provided 96.0% sensitivity and 97.7% specificity. The area under the curve for the received model was 0.9716. CONCLUSIONS: An artificial neural network model based on clinical and ultrasonographic data allows to calculate the probability of tumor malignancy.

Adnexal Diseases↗
PubMed2001

Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions.

A mathematical model for predicting human thermal and regulatory responses in cold, cool, neutral, warm, and hot environments has been developed and validated. The multi-segmental passive system, which models the dynamic heat transport within the body and the heat exchange between body parts and the environment, is discussed elsewhere. This paper is concerned with the development of the active system, which simulates the regulatory responses of shivering, sweating, and peripheral vasomotion of unacclimatised subjects. Following a comprehensive literature review, 26 independent experiments were selected that were designed to provoke each of these responses in different circumstances. Regression analysis revealed that skin and head core temperature affect regulatory responses in a nonlinear fashion. A further signal, i.e. the rate of change of the mean skin temperature weighted by the skin temperature error signal, was identified as governing the dynamics of thermoregulatory processes in the cold. Verification and validation work was carried out using experimental data obtained from 90 exposures covering a range of steady and transient ambient temperatures between 5 degrees C and 50 degrees C and exercise intensities between 46 W/m2 and 600 W/m2. Good general agreement with measured data was obtained for regulatory responses, internal temperatures, and the mean and local skin temperatures of unacclimatised humans for the whole spectrum of climatic conditions and for different activity levels.

Acclimatization↗
PubMed2005

Computational prediction of SEG (single exon gene) function in humans.

Human genes are often interrupted by non-coding, intragenic sequences called introns. Hence, the gene sequence is divided into exons (coding segments) and introns (non-coding segments). Consequently, a majority of them are multi exon genes (MEG). However, a considerable amount of single exon genes (SEG) are present in the human genome (approximately 12%). This amount is sizeable and it is important to probe their molecular function and cellular role. Hence, we performed a genome wide functional assignment to 3750 SEG sequences using PFAM (protein family database), PROSITE (database of biologically meaningful signatures or motifs) and SUPERFAMILY (a library covering all proteins of known 3 dimensional structure). PFAM assigned 13% SEG to trans-membrane receptor genes of the G-protein coupled receptor (GPCR) family and showed that a majority of SEG proteins have DNA binding function. PROSITE identified 336 unique motif types in them and this accounts for 25% of all known patterns, with a majority having PHOSPHORYLATION and ACETYLATION signals. SUPERFAMILY assigned 33% SEG to the membrane all alpha (proteins containing alpha helix structural elements according to SCOP (structural classification of proteins) definition). Functional assignment of SEG proteins at multiple levels (sequence signals, sequence families, 3D structures) using PFAM, PROSITE and SUPERFAMILY is envisioned to suggest their selective and predominant molecular function in cellular systems. Their function as DNA binding, phosphorylating, acetylating and house-keeping agents is intriguing. The analysis also showed evidence of SEG expression and retro-transposition. However, this information is inadequate to draw concerted conclusion on the prevalent role played by these proteins in cellular biology. A complete understanding of SEG function will help to explore their role in cellular environment. The derived datasets from these analyses are available at http://sege.ntu.edu.sg/wester/intronless/human/.

Computational Biology↗
PubMed2006

Computational prediction and experimental verification of HVA1-like abscisic acid responsive promoters in rice (Oryza sativa).

Abscisic acid (ABA) is one of the central plant hormones, responsible for controlling both maturation and germination in seeds, as well as mediating adaptive responses to desiccation, injury, and pathogen infection in vegetative tissues. Thorough analyses of two barley genes, HVA1 and HVA22, indicate that their response to ABA relies on the interaction of two cis-acting elements in their promoters, an ABA response element (ABRE) and a coupling element (CE). Together, they form an ABA response promoter complex (ABRC). Comparison of promoters of barley HVA1 and it rice orthologue indicates that the structures and sequences of their ABRCs are highly similar. Prediction of ABA responsive genes in the rice genome is then tractable to a bioinformatics approach based on the structures of the well-defined barley ABRCs. Here we describe a model developed based on the consensus, inter-element spacing and orientations of experimentally determined ABREs and CEs. Our search of the rice promoter database for promoters that fit the model has generated a partial list of genes in rice that have a high likelihood of being involved in the ABA signaling network. The ABA inducibility of some of the rice genes identified was validated with quantitative reverse transcription PCR (QPCR). By limiting our input data to known enhancer modules and experimentally derived rules, we have generated a high confidence subset of ABA-regulated genes. The results suggest that the pathways by which cereals respond to biotic and abiotic stresses overlap significantly, and that regulation is not confined to the level transcription. The large fraction of putative regulatory genes carrying HVA1-like enhancer modules in their promoters suggests the ABA signal enters at multiple points into a complex regulatory network that remains largely unmapped.

Abscisic Acid↗
PubMed2006

A computational prediction of isochores based on hidden Markov models.

Mammalian genomes are organised into a mosaic of regions (in general more than 300 kb in length), with differing, relatively homogeneous G+C contents. The G+C content is the basic characteristic of isochores, but they have also been associated with many other biological properties. For instance, the genes are more compact and their density is highest in G+C rich isochores. Various ways of locating isochores in the human genome have been developed, but such methods use only the base composition of the DNA sequences. The present paper proposes a new method, based on a hidden Markov model, which takes into account several of the biological properties associated with the isochore structure of a genome. This method leads to good segmentation of the human genome into isochores, and also permits a new analysis of the known heterogeneity of G+C rich isochores: most (60%) of the G+C poor genes embedded in G+C rich isochores have UTR sequences characteristic of G+C rich genes. This genomic feature is discussed in the context of both evolution and genome function.

5' Untranslated Regions↗
PubMed2005

Design of C2-chiral diamines that are computationally predicted to be a million-fold more basic than the original proton sponges.

A set of C2-chiral diamines 18-21 based on 1,6-diazacyclodecane have been identified whose conjugate acids are predicted by B3LYP/6-31G calculations to have pKa values of approximately 23-6 on the water scale (pKa = 30-33 in MeCN); they are also expected to be kinetically active, but essentially nonnucleophilic. Strain relief on protonation largely determines the basicity of these compounds, and the key to the design of stronger bases is limiting conformational freedom, especially by preventing nitrogen inversion, through the introduction of additional ring fusions. 15,16-Dimethyl-15,16-diazatricyclo[9.3.1.1(4,8)]hexadecane (20) is examined in detail and shown to exist in 10 diastereomeric forms as a result of in-/out-isomerism. The predicted pKa values for these diastereomers range over 14 log units.

Journal Article↗
PubMed2000

A refined 3-dimensional QSAR of cytochrome P450 2C9: computational predictions of drug interactions.

A ligand-based model is reported that predicts the Ki values for cytochrome P450 2C9 (CYP2C9) inhibitors. This CoMFA model was used to predict the affinity of 14 structurally diverse compounds not in the training set and appears to be robust. The mean error of the predictions is 6 microM. The experimentally measured Ki values of the 14 compounds range from 0.1 to 48 microM. Leave-one-out cross-validated partial least-squares gives a q2 value of between 0.6 and 0.8 for the various models which indicates internal consistency. Random assignment of biological data to structure leads to negative q2 values. These models are useful in that they establish a pharmacophore for binding to CYP2C9 that can be tested with site-directed mutagenesis. These models can also be used to screen for potential drug interactions and to design compounds that will not bind to this enzyme with high affinity.

Aryl Hydrocarbon Hydroxylases↗