SEARCH · PubMed Health

Results for “in silico analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2005

Deletion of an mmpL gene and multiple associated genes from the genome of the S strain of Mycobacterium avium subsp. paratuberculosis identified by representational difference analysis and in silico analysis.

Mycobacterium avium subsp. paratuberculosis (M. a. paratuberculosis) can be divided into two major strains, sheep (S) and cattle (C), based on cultural requirements, host specificity, degree of clumping of cells in suspension and minor genomic differences including copy number of insertion elements and point mutations. Representational difference analysis (RDA) with S strain as driver and C strain as tester was used to identify unique genomic regions. Three sequences (RDA1, RDA3 and RDA4) were identified. RDA1 (229bp) contained a single base difference between S and C strains. RDA4 (163bp) was an artefact. RDA3 (206bp) was similar to several sequences in the incomplete genome sequences of M. avium subsp. paratuberculosis K10 and M. avium subsp. avium 104. In silico analysis led to the identification of a deletion that may be as large as 17kb in the sheep strain of M. a. paratuberculosis. PCR analysis of this region confirmed the deletion of 11,584bp that included 10 genes (MAP1734 to MAP1743c) of the M. a. paratuberculosis K10 genome. This included the loss of mmpL5 and mmpS5 genes and homologues of the M. tuberculosis genes: Rv2002 (fabG3), Rv2017c (lipW), Rv3132c (devS), Rv2032 (acg) and the conserved hypothetical genes Rv2005c and Rv2026c. PCR reactions designed to detect the single nucleotide polymorphism in RDA1 and the deletion in the mmpL region can be used to distinguish these strains. MmpL genes, found in M. tuberculosis and other mycobacteria are part of the resistance-nodulation-division (RND) family but contain domains unique to mycobacteria thought to play a role in cell wall biogenesis, virulence and other phenotypic characteristics. Absence of mmpL5 in the S strain of M. a. paratuberculosis is unlikely to account for the difference in clumping in suspension but may explain the difference in cultural requirements and host specificity compared to the C strain but the impact of the remainder of the deletion is yet to be ascertained.

Base Sequence↗

PubMed2000

Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions.

BACKGROUND: Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA). FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information. RESULTS: Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system) essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains. CONCLUSIONS: We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation.

Computational Biology↗

PubMed2007

Plasma protein binding affinity and its relationship to molecular structure: an in-silico analysis.

In-silico plasma protein binding (PPB) models have been generated on human and rat in-house datasets, and on a human dataset sourced from the literature. From the results reported herein, it is apparent that models built on datasets relevant to the chemotypes under investigation in lead optimization programs will perform considerably better in this role than those generated on diverse compounds sourced from the literature. The in-house human and rat partial least-squares regression (PLS) models have cross-validated q2 values of 0.53 and 0.42 on the training sets, respectively. On the independent test and validation sets, they display similar predictive ability, with logK prediction errors of approximately 0.5 log units. This compares to approximately 0.25 log units variability expected for experiment. Given the considerable interspecies PPB differences, the prediction of PPB in one species using measurements in the other is no better than a prediction from an in-silico model generated on that species.

Analysis of Variance↗

PubMed2003

The Proteome Analysis database: a tool for the in silico analysis of whole proteomes.

The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Animals↗

PubMed2004

In silico analysis of complete bacterial genomes: PCR, AFLP-PCR and endonuclease restriction.

UNLABELLED: We have developed a website, www.in-silico.com, which runs a software program that performs three basic tasks in completely sequenced bacterial genomes by in silico analysis: PCR amplification, amplified fragment length polymorphism (AFLP-PCR) and endonuclease restriction. For PCR, after selection of the genome and introduction of primers, fragment size, DNA sequence and corresponding open reading frame (ORF) identity of the resulting PCR product is computed. Plasmids of sequenced species may be included in the analysis. Theoretical AFLP-PCR analyzes similar parameters, and includes a suggestion tool providing a list of commercial restriction enzyme pairs yielding up to 50 amplicons in the selected genome. Endonuclease restriction analysis of complete genomes and plasmids calculates the number of restriction sites for endonucleases in a given genome. If the number of fragments is 50 or fewer, pulsed field gel electrophoresis image and restriction maps are illustrated. Other tools that have been included in this site are ORF search by name and DNA to protein translation as well as restriction digestion of user-defined DNA sequences. AVAILABILITY: This is a new molecular biology resource freely available over the Internet at http://www.in-silico.com

Algorithms↗

PubMed2004

A quantitative in silico analysis calculates the angiotensin I converting enzyme (ACE) inhibitory activity in pea and whey protein digests.

Angiotensin I converting enzyme (ACE) inhibitory peptides can induce antihypertensive effects after oral administration. By means of an ACE inhibitory peptide database, containing about 500 reported sequences and their IC(50) values, the different proteins in pea and whey were quantitatively evaluated as precursors for ACE inhibitory peptides. This analysis was combined with experimental data from the evolution in ACE inhibitory activity and protein degradation during in vitro gastrointestinal digestion. Pea proteins produced similar in silico scores and were degraded early in the in vitro digestion. High ACE inhibitory activity was observed after the simulated stomach phase and augmented slightly in the simulated small intestine phase. The major whey protein beta-lactoglobulin obtained the highest in silico scores, which corresponded with the fact that degradation of this protein in vitro only occurred from the simulated small intestine phase on and resulted in a 10-fold increase in the ACE inhibitory activity. Whey protein obtained total in silico scores of about 124 ml/mg, compared to 46 ml/mg for pea protein, indicating that whey protein would be a richer source of ACE inhibitory peptides than pea protein. Although beta-lactoglobulin is only partially digested, a higher ACE inhibitory activity was indeed found in the whey (IC(50) = 0.048 mg/ml) compared to the pea digest (IC(50) = 0.076 mg/ml). In silico gastrointestinal digestion of the highest scoring proteins in pea and whey, vicilin and albumin PA2, and beta-lactoglobulin, respectively, directly released a number of potent ACE inhibitory peptides. Several other ACE inhibitory sequences resisted in silico digestion by gastrointestinal proteases. Briefly, the quantitative in silico analysis will facilitate the study of precursor proteins on a large scale and the specific release of bioactive peptides.

Amino Acid Sequence↗

PubMed2006

KCNE2, a down-regulated gene identified by in silico analysis, suppressed proliferation of gastric cancer cells.

It is important to identify the differentially expressed gene in gastric cancer for elucidating the molecular mechanisms of tumorigenesis of stomach. Here, 38 genes differentially expressed genes between gastric cancer and normal gastric mucosa by in silico approaches. A potassium channel protein KCNE2, identified as a down-regulated gene in gastric cancer, was chosen for further study. We investigated the expression of KCNE2 in gastric cancer tissues and cell lines and examined the effect of KCNE2 on proliferation of gastric cancer. The expression of KCNE2 was markedly down-regulated in gastric cancer tissues and cell lines. Forced overexpression of KCNE2 suppressed the growth of SGC7901 cells and cell cycle progression significantly, which might be related to the down-regulation of Cyclin D1. KCNE2 also inhibited SGC7901 cell growth in soft agar and its tumorigenicity in nude mice. Taken together, our work showed that in silico analysis approaches could be used to identify cancer-related genes effectively. KCNE2, as a novel down-regulated gene in gastric cancer, suppressed cell proliferation and tumorigenesis of stomach.

Animals↗

PubMed2005

Comparison of mammalian cell entry operons of mycobacteria: in silico analysis and expression profiling.

Mammalian cell entry (mce) operons, implicated in the entry of mycobacteria into host cells, are present in pathogenic and saprophytic species. It is likely that the genes in these operons have functions other than those required for entry into host cells. Using in silico analysis we have identified domains within the mce operons that might justify their occurrence in saprophytic species like Mycobacterium smegmatis. Our analysis identified in addition to the mce domain, the presence of the Ttg2B and Ttg2C domains, typical of proteins involved in transport. We have also analysed and compared the expression profile between mce operons of Mycobacterium tuberculosis, Mycobacterium bovis and M. smegmatis under different growth conditions. In case of M. smegmatis, each operon presented domain truncation for at least one gene. We observe differential expression among the operons in M. smegmatis growing under different culture conditions. Bacilli growing in nutritionally rich medium with aeration, only the mce4 operon was expressed while during stationary phase of a standing culture, all four mce operons were expressed. In M. bovis, in addition to the absence of the mce3 operon, several protein domains encoded by the other operons were truncated. We detected expression of the mce2 operon in the exponential and stationary growth phase, while the mce1 operon was only expressed in the stationary growth phase. Differential expression of mce operons and their redundancy in the genome of the majority members of mycobacteria are discussed in view of our results.

Antigens, Bacterial↗

PubMed2005

In silico analysis of ORF1ab in coronavirus HKU1 genome reveals a unique putative cleavage site of coronavirus HKU1 3C-like protease.

Recently we have described the discovery and complete genome sequence of a novel coronavirus associated with pneumonia, coronavirus HKU1 (CoV-HKU1). In this study, a detailed in silico analysis of the ORF1ab, encoding the 7,182-amino acid replicase polyprotein in the CoV-HKU1 genome showed that the replicase polyprotein of CoV-HKU1 is cleaved by its papain-like proteases and 3C-like protease (3CL(pro)) into 16 polypeptides homologous to the corresponding polypeptides in other coronaviruses. Surprisingly, analysis of the putative cleavage sites of the 3CL(pro) revealed a unique putative cleavage site. In all known coronaviruses, the P1 positions at the cleavage sites of the 3CL(pro) are occupied by glutamine. This is also observed in CoV-HKU1, except for one site at the junction between nsp10 (helicase) and nsp11 (member of exonuclease family), where the P1 position is occupied by histidine. This amino acid substitution is due to a single nucleotide mutation in the CoV-HKU1 genome, CAG/A to CAT. This probably represents a novel cleavage site because the same mutation was consistently observed in CoV-HKU1 sequences from multiple specimens of different patients; the P2 and P1'-P12' positions of this cleavage site are consistent between CoV-HKU1 and other coronaviruses; and as the helicase is one of the most conserved proteins in coronaviruses, cleavage between nsp10 and nsp11 should be an essential step for the generation of the mature functional helicase. Experiments, including purification and C-terminal amino acid sequencing of the CoV-HKU1 helicase and trans-cleavage assays of the CoV-HKU1 3CL(pro) will confirm the presence of this novel cleavage site.

Amino Acid Sequence↗

PubMedDate not supplied

In-silico analysis of kallikrein gene expression in pancreatic and colon cancers.

Human kallikreins are a cluster of 15 serine protease genes located in the chromosomal band 19q13.4, a non-randomly rearranged region in many solid tumors, including pancreatic cancer. We utilized the SAGE and EST databases of the Cancer Genome Anatomy Project to perform in-silico analysis of kallikrein gene expression in normal and cancerous pancreatic and colon tissues and cell lines using virtual Northern blotting (VNB), digital differential display (DDD) and X-profiler. At least two kallikreins, KLK6 and KLK10, are significantly up-regulated in pancreatic cancer. We probed 2 normal and 6 pancreatic cancer SAGE libraries with gene-specific tags for each of these kallikreins. KLK6 was found to be expressed in 5/6 cancer libraries and showed the most marked (5-fold) increase in average expression levels in cancer vs. normal. These data were verified by screening the EST databases, where all mRNA clones isolated were from cancerous libraries, with no clones detected in normal pancreatic tissues or cell lines. X-profiler comparison of two pools of normal and cancerous pancreatic libraries further verified the significant increase of KLK6 expression levels in pancreatic cancer. DDD data showed a 13-fold increase in KLK10 expression in pancreatic cancer. Three kallikrein genes, KLK6, 8 and 10 are overexpressed in colon cancer compared to normal colon, while one kallikrein, KLK1, is down-regulated. While no expression of KLK6 was detected in normal colon, KLK6-specific tags were detectable in 2 cancer libraries. Similar results were obtained by EST screening; no KLK6 clones were detected in any of the 28 normal libraries examined, while 10 KLK6 EST clones were found in colon adenocarcinoma. KLK10 was not detectable in normal colon. Gene-specific tags were, however, detectable with high density in colon cancer and 7 EST clones were found to be expressed in colon Adenocarcinoma.

Adenocarcinoma↗

PubMed2004

Trophoblastic cDNA cloning of porcine Pregnancy-Associated Glycoprotein genes (pPAG) and in silico analysis of coded polypeptide precursors.

Multiple Pregnancy-Associated Glycoprotein (PAG) genes, coding various chorionic products that belong to the aspartic proteinase family (AP), have been discovered in various eutherians (Placentalia). This paper presents cloning of five novel porcine PAG (pPAG) cDNAs: pPAG3, pPAG4, pPAG5, pPAG6, pPAG8 and pPAG10. All cDNAs have been identified by trophoblastic library screening on 13-17 days post coitum (dpc). These cloned and sequenced pPAG cDNAs have been deposited in GenBank database of National Institute of Heath/ National Center of Biotechnology Information (NIH/NCBI) with various accession numbers: AF315377, AF272734, AY188554, AF272735, AY373029 and one during submission. The open reading frames (ORF) of cloned cDNA sequences allowed for identification and in silico analysis of polypeptide pPAG precursors, including their identity content and various amino acid substitutions, which caused hypothetical structure changes of the pPAG precursors. In conclusion, our results concerning transcriptomal cloning and in silico analyses of the novel identified trophoblastic cDNA of the pPAG genes provided contributive data regarding porcine genome identification and physiology of the gestation in this species.

Amino Acid Sequence↗

PubMed2002

Genomics of steroid hormones: in silico analysis of nucleotide sequence variants (polymorphisms) of the enzymes involved in the biosynthesis and metabolism of steroid hormones.

Alterations of steroid hormone biosynthesis and metabolism are suspected to be involved in the pathogenesis of several diseases. Several polymorphisms of the enzymes involved in these processes have already been described and some could be associated with certain diseases. We attempted to examine the sequence variants of these genes in order to find novel variants by an in silico analysis. We analyzed the known human nucleotide sequences of the enzymes p450 side-chain cleavage enzyme, steroid 17-alpha-hydroxylase/17,20-lyase, 3-beta-hydroxysteroid dehydrogenase types 1 and 2, 21-hydroxylase, 11-beta-hydroxylase, aldosterone synthase, aromatase, 11-beta-hydroxysteroid dehydrogenase types 1 and 2, steroid 5-alpha-reductase types 1 and 2, steroid 5-beta-reductase, dehydroepiandrosterone sulfotransferase, 17-beta-hydroxysteroid dehydrogenase types 1-3. The analysis was performed using the National Center for Biotechnology Information Database by the search tool blastn. We found numerous sequence variants in both coding and non-coding sequences. The majority of these sequence variants have already been described, nevertheless, some appear as novel variants. Some of these may also have functional significance. We hypothesize over the possible significance of these findings and briefly review the available literature.

Base Sequence↗

PubMed2001

In silico analysis of cancer through the Cancer Genome Anatomy Project.

The Cancer Genome Anatomy Project (CGAP) was designed and implemented to provide public datasets, material resources and informatics tools to serve as a platform to support the elucidation of the molecular signatures of cancer. This overview of CGAP describes the status of this effort to develop resources based on gene expression, polymorphism identification and chromosome aberrations, and we describe a variety of analytical tools designed to facilitate in silico analysis of these datasets.

Animals↗

PubMed2005

An in silico analysis of trypanosomatid RNA polymerases: insights into their unusual transcription.

African trypanosomes employ both Pol I (RNA polymerase I) and Pol II to transcribe protein-coding genes in large polycistronic units of up to 50 genes. Subsequent processing produces mature capped mRNAs. Evidence suggests that regulation of gene expression is primarily exerted post-transcriptionally. Here, we use the recently completed genome sequences of three trypanosomatids, Trypanosoma brucei, Trypanosoma cruzi and Leishmania major, in an in silico analysis of their fundamental RNA polymerase complexes. The core complement of Pol II subunits, including those that are shared with Pol I and Pol III are present. However, both Pol I and Pol III complexes are missing members of the rpoE-rpoF subunit groups. Out of the five shared subunits, both RPB5 and RPB6 have two isoforms in the three trypanosomes. One represents the canonical polymerase subunit and the other differs by insertion or deletion of stretches of charged residues. We propose that these alternative isoforms function in distinct polymerase complexes, and may influence recruitment of the trypanosome RPB4-RPB7 heterodimer.

Animals↗

PubMed2000

In silico analysis of gene expression patterns during early development of Xenopus laevis.

The information as to where and when a mRNA is present in a given cell is essential to bridge the gap between the DNA sequence of a gene and its physiological function. Therefore, a major component of functional genomics is to characterize the levels and the spatio-temporal domains of gene expression. Currently, there is just a few specialised public databases available storing the data on gene expression while they are needed as a resource for the field. Moreover, there is a need to develop and assess computational tools to compare and analyse expression profiles in a suitable way for biological interpretation. Here we describe our recent work on developing a database on gene expression for the frog Xenopus laevis, and on setting up and using new tools for the analysis and comparison of gene expression patterns. We used histogram clustering to compare expression profiles at both gene and tissue levels using a set of data coming from the characterization of the expression of genes during early development of Xenopus. This enabled us to draw a tree of tissue relatedness and to identify coexpressed genes by in silico analysis.

Animals↗

PubMed2006

In silico analysis of genes nucleoprotein, neuraminidase and hemagglutinin: a comparative study on different strains of influenza A (Bird flu) virus sub-type H5N1.

The avian influenza (bird flu) is an infectious disease of birds, ranging from a mild to a severe form of illness. Influenza viruses pose significant challenges to both human and animal health. The proteins, nucleoprotein (NP), neuraminidase (NA) and hemagglutinin (HA) of influenza A virus (Bird flu virus) sub-type A/Hatay/2004/(H5N1) from chicken were selected for this study. Our in silico analysis predicted that HA of influenza A virus is highly sensitive to mutations and hence it is significant for its pathogenic nature. None of the mutations was detected as an important change except in NA where K332R was at a PKC phosphorylation site. Analysis of the sequence comparison showed that the maximum number of mutations were observed in HA. These mutations are significant as they are involved in change in polarity or hydrophobicity as well as in propensity of each amino acid residue to stabilize the secondary structure. The program MAPMUTATION can be used to monitor the mutations, and predict the trend of mutations.

Amino Acid Sequence↗

PubMed2006

Crystallographic and in silico analysis of the sialoside-binding characteristics of the Siglec sialoadhesin.

The Siglec family of receptors mediates cell-surface interactions through recognition of sialylated glycoconjugates. Previously reported structures of the N-terminal domain of the Siglec sialoadhesin (SnD1) in complex with various sialic acid analogs revealed the structural template for sialic acid binding. To characterize further the carbohydrate-binding properties, we have determined the crystal structures of SnD1 in the absence of ligand, and in complex with 2-benzyl-Neu5NPro and 2-benzyl-Neu5NAc. These structures reveal that SnD1 undergoes very few structural changes on ligand binding and detail how two novel classes of sialic acid analogs bind, one of which unexpectedly can induce Siglec dimerization. In conjunction with in silico analysis, this set of structures informs us about the design of putative ligands with enhanced binding affinities and specificities to different Siglecs, and provides data with which to test the effectiveness of different computational drug design protocols.

Algorithms↗

PubMed2026

In silico analysis of metal resistance genes in Pseudomonas extremaustralis 2E-UNGS: Genomic insights and safety assessment for wastewater biotreatment.

Pseudomonas extremaustralis 2E-UNGS is a non-pathogenic strain isolated from the polluted Reconquista River basin (Buenos Aires Metropolitan Area, Argentina), with a 20-year history of study focused on its survival strategies that have enabled its application in various processes such as waste biotreatment and biosensing. Regarding bacterial-metal interactions, P. extremaustralis 2E-UNGS is capable of biosorbing Cd(II), Zn(II), and Cu(II), and biotransforming Cr(VI) to Cr(III), facilitating both the removal of these metals from aqueous systems and their use in biosensor development. The complete circular chromosome (6,372,594 bp) has been annotated in the NCBI GenBank under accession number NZ_CP091043.1. The aim of this work was to perform an in-depth exploration of the P. extremaustralis 2E-UNGS genome to support the optimization of sustainable bioprocesses within the One Health framework. To this end, the integration of experimental evidence with a detailed in silico analysis of key genes involved in metal-microorganism interactions, antibiotic resistance, and their interconnections provides valuable insights for the optimization of future biotechnological applications. Considering its antibiotic resistance profile, together with the activation of efflux pumps induced by metal stimuli-particularly observed under Zn(II) exposure-P. extremaustralis 2E-UNGS can be regarded as suitable for the design of confined bioreactor processes, minimizing the risk of potential accidental environmental releases. Therefore, modulation of gene expression emerges as a promising approach to enhance the efficiency of metal-loaded wastewater biotreatments.

Pseudomonas↗