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PubMed2005

Docking to single-domain and multiple-domain proteins: old and new challenges.

The diverse selection of targets in the CAPRI experiments provides grounds for determining the limits of our rigid-body docking program MolFit, and for extending it. We find that the sensitivity of MolFit is high, enabling it to produce reasonably accurate docking solutions when the structures undergo moderate local conformation changes upon complex formation or when the docked molecules are modeled. Yet the ranks of these solutions are sometimes too low to meet the requirements of CAPRI assessment. This indicates that the selectivity of MolFit, which was optimized for docking of unbound X-ray structures, and which relies on the availability of external data from biochemical and bioinformatic sources, needs readjustment in order to meet the challenges presented by NMR or modeled structures. A different challenge is presented by large global conformation changes such as movements of domains. We show that such changes can be accommodated within the rigid-body approximation by employing rigid multibody multistage docking procedures. We also address the difficulty of ranking results from 2-body and multibody docking scans in cases in which there are no external data favoring one option over the other.

Algorithms↗

PubMed2003

Sequence analysis of the genome of the temperate Yersinia enterocolitica phage PY54.

The temperate Yersinia phage PY54 belongs to the unusual group of phages that replicate as linear plasmids with covalently closed ends. Besides Escherichia coli phage N15, PY54 is the only member of this group to be identified. We have determined the complete sequence (46,339 bp) of the PY54 genome. Bioinformatic analyses revealed 67 open reading frames (ORFs) with good coding potential located on both DNA strands. The comparison of the deduced PY54 gene products with known proteins encoded by other phages and bacteria along with functional studies have enabled us to assign the possible functions of 25 ORFs. In the left arm of the PY54 genome, we identified a number of ORFs that obviously code for head and tail proteins. Furthermore, this part of the phage genome contains genes probably involved in plasmid partitioning. Regarding the predicted gene functions and gene order, the PY54 and N15 left arms are similar. However, there are only weak DNA homologies and, in contrast to N15, the Yersinia phage harbours only a few ORFs related to genes found in lambdoid phages. The PY54 right arm comprises mainly regulatory genes as well as genes important for plasmid replication, DNA methylation, and host cell lysis. Out of 36 deduced products of the right arm, 13 revealed strongest database homologies to N15 proteins, of which the protelomerase and the Rep protein are exclusively homologous to their N15 counterparts. A number of PY54 genes essential for the lytic or lysogenic cycle were identified by functional analysis and characterization of phage mutants. In order to study transcription during the lytic and lysogenic stage, we analysed 34 PY54 ORFs by reverse transcriptase (RT)-PCR. The phage transcription patterns in lysogenic bacteria and at the late lytic stage of infection are nearly identical. The reasons for this finding are spontaneous release of phages during lysogeny and a high rate of phages that lysogenize their Yersinia host upon infection.

Amino Acid Sequence↗

PubMed2003

Bioinformatic analysis of ClpS, a protein module involved in prokaryotic and eukaryotic protein degradation.

ClpS is a small protein, usually encoded immediately upstream of ClpA in the genomes of proteobacteria. Recent results show that it is a molecular adaptor for substrate recognition by ClpA in Escherichia coli. We analyzed ClpS by bioinformatic methods and found that ClpS homologs are also found in organisms that lack ClpA, such as actinobacteria, cyanobacteria, and plant chloroplasts. Furthermore, ClpS is homologous to a domain in the eukaryotic E3 ubiquitin ligase, N-recognin. This domain has previously been described as responsible for the recognition of type 2 N-end rule substrates. Despite very low levels of sequence similarity to proteins of known structure, there appears to be substantial structural similarity between ClpS and the C-terminal domain of ribosomal protein L7/12 (1CTF).

Adenosine Triphosphatases↗

PubMedDate not supplied

4D bioinformatics: a new look at the ribosome as an example.

We have adapted the Java Molecular Viewer (JMV) to virtual reality display environments, through a number of extensions to the Java 3D code. Phylogenetic information derived from multiple alignments (temporal information) can be overlaid onto molecule structures (spatial information). The number of sequences included in the underlying multiple alignment can be changed instantaneously, resulting in dynamical updates of the displayed information. JMV was also extended to handle an infinite number of objects (molecules) in the same display. The objects can be manipulated in six degrees of freedom simultaneously or independently. We have used the small subunit ribosomal RNA to demonstrate the system (http:// cave.ucalgary.ca), which can be used for any molecule with a resolved structure.

Animals↗

PubMed2025

AutoPVPrimer: A comprehensive AI-Enhanced pipeline for efficient plant virus primer design and assessment.

Plant viruses pose a significant threat to global agriculture and require efficient tools for their timely detection. We present AutoPVPrimer, an innovative pipeline that integrates artificial intelligence (AI) and machine learning to accelerate the development of plant virus primers. The pipeline uses Biopython to automatically retrieve different genomic sequences from the NCBI database to increase the robustness of the subsequent primer design. The design_primers_with_tuning module uses a random forest classifier that optimizes parameters and provides flexibility for different experimental conditions. Quality control measures, including the evaluation of poly-X content and melting temperature, increase primer reliability. Unique to AutoPVPrimer is the visualize_primer_dimer module, which supports the visual evaluation of primer dimers-a feature missing in other tools. Primer specificity is validated via primer BLAST, which contributes to the overall efficiency of the pipeline. AutoPVPrimer has been successfully applied to the tomato mosaic virus, proving its adaptability and efficiency. The modular design allows customization by the user and extends the applicability to different plant viruses and experimental scenarios. The pipeline represents a significant advance in primer design and provides researchers with an effective tool to accelerate molecular biology experiments. Future developments aim to extend compatibility and incorporate user feedback to consolidate AutoPVPrimer as an innovative contribution to the bioinformatics toolbox and a promising resource for the advancement of plant virology research.

DNA Primers↗

PubMed2005

Bridging the gap between medical and bioinformatics: an ontological case study in colon carcinoma.

Ontological principles are needed in order to bridge the gap between medical and biological information in a robust and computable fashion. This is essential in order to draw inferences across the levels of granularity which span medicine and biology, an example of which include the understanding of the roles of tumor markers in the development and progress of carcinoma. Such information integration is also important for the integration of genomics information with the information contained in the electronic patient records in such a way that real time conclusions can be drawn. In this paper, we describe a large multi-granular datasource built by using ontological principles and focusing on the case of colon carcinoma.

Colonic Neoplasms↗

PubMed2003

Bioinformatics analysis of experimentally determined protein complexes in the yeast Saccharomyces cerevisiae.

Many important cellular functions are implemented by protein complexes that act as sophisticated molecular machines of varying size and temporal stability. Here we demonstrate quantitatively that protein complexes in the yeast Saccharomyces cerevisiae are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or nonessential), and share identical functional classification and cellular localization. This core is surrounded by a functionally mixed group of proteins, which likely represent short-lived or spurious attachments. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.

Computational Biology↗

PubMed2006

Open source tools and toolkits for bioinformatics: significance, and where are we?

This review summarizes important work in open-source bioinformatics software that has occurred over the past couple of years. The survey is intended to illustrate how programs and toolkits whose source code has been developed or released under an Open Source license have changed informatics-heavy areas of life science research. Rather than creating a comprehensive list of all tools developed over the last 2-3 years, we use a few selected projects encompassing toolkit libraries, analysis tools, data analysis environments and interoperability standards to show how freely available and modifiable open-source software can serve as the foundation for building important applications, analysis workflows and resources.

Algorithms↗

PubMed1999

An ontology for bioinformatics applications.

MOTIVATION: An ontology of biological terminology provides a model of biological concepts that can be used to form a semantic framework for many data storage, retrieval and analysis tasks. Such a semantic framework could be used to underpin a range of important bioinformatics tasks, such as the querying of heterogeneous bioinformatics sources or the systematic annotation of experimental results. RESULTS: This paper provides an overview of an ontology [the Transparent Access to Multiple Biological Information Sources (TAMBIS) ontology or TaO] that describes a wide range of bioinformatics concepts. The present paper describes the mechanisms used for delivering the ontology and discusses the ontology's design and organization, which are crucial for maintaining the coherence of a large collection of concepts and their relationships. AVAILABILITY: The TAMBIS system, which uses a subset of the TaO described here, is accessible over the Web via http://img.cs.man.ac.uk/tambis (although in the first instance, we will use a password mechanism to limit the load on our server). The complete model is also available on the Web at the above URL.

Animals↗

PubMed2003

Simulating haplotype blocks in the human genome.

SUMMARY: A bioinformatic tool was written to simulate haplotypes and SNPs under a modified coalescent with recombination. The most important feature of this program is that it allows for the specification of non-homogeneous recombination rates, which results in the formation of the so-called 'haplotype blocks' of the human genome. The program also implements different mutation models and flexible demographic histories. The samples generated can be very useful to better understand the architecture of the human genome and to investigate its impact in association studies searching for disease genes. AVAILABILITY: The SNPsim package is available at http://www.evolgenics.com/software

Algorithms↗

PubMed2025

Semiparametric efficient estimation of small genetic effects in large-scale population cohorts.

Population genetics seeks to quantify DNA variant associations with traits or diseases, as well as interactions among variants and with environmental factors. Computing millions of estimates in large cohorts in which small effect sizes and tight confidence intervals are expected, necessitates minimizing model-misspecification bias to increase power and control false discoveries. We present TarGene, a unified statistical workflow for the semi-parametric efficient and double robust estimation of genetic effects including $ k $-point interactions among categorical variables in the presence of confounding and weak population dependence. $ k $-point interactions, or Average Interaction Effects (AIEs), are a direct generalization of the usual average treatment effect (ATE). We estimate genetic effects with cross-validated and/or weighted versions of Targeted Minimum Loss-based Estimators (TMLE) and One-Step Estimators (OSE). The effect of dependence among data units on variance estimates is corrected by using sieve plateau variance estimators based on genetic relatedness across the units. We present extensive realistic simulations to demonstrate power, coverage, and control of type I error. Our motivating application is the targeted estimation of genetic effects on trait, including two-point and higher-order gene-gene and gene-environment interactions, in large-scale genomic databases such as UK Biobank and All of Us. All cross-validated and/or weighted TMLE and OSE for the AIE $ k $-point interaction, as well as ATEs, conditional ATEs and functions thereof, are implemented in the general purpose Julia package TMLE.jl. For high-throughput applications in population genomics, we provide the open-source Nextflow pipeline and software TarGene which integrates seamlessly with modern high-performance and cloud computing platforms.

Humans↗

PubMed2004

Principle component analysis in F/10 and G/11 xylanase.

A bioinformatics method was used to analyze F/10 and G/11 xylanase basing on principle component analysis, and a model was made to classify between these two folds with an ideal result. The principle components were predicated to be secondary structures, the components were analyzed with the architecture of each family, and found comparable with (beta/alpha)(8)-barrel of F/10 xylanase and right-hand structure of G/11 xylanase. Compared with sequence similarities, this method gave discriminating features a clear meaning. The largest component did not appear in the model, which revealed no difference between these two families.

Amino Acid Sequence↗

PubMed2005

Structure and modeling studies of the carboxy-terminus region of human tropoelastin.

Elastin macromolecular assembly is a highly complex mechanism involving many steps including coacervation, cross-linking, and probably other (not known) phenomena. In past studies, it has been proposed that the C-terminal part of tropoelastin is also involved in this process and may play a key role in tropoelastin interactions with other proteins of the final elastic fibres scaffold. Presented here are the results of the biophysical studies (biospectroscopy, bioinformatics) of the C-terminal domain of tropoelastin. We report the detailed structures adopted by the oxidized (native) and reduced forms of the free synthetic peptide with sequence encoded by exon 36 of human tropoelastin (GGACLGKACGRKRK) and propose a dynamical interpretation of which structures may be involved in interactions with other extra-cellular matrix proteins. We also suggest that these structures may be retrieved in other proteins sharing a consensus sequence; however no definitive conclusion can be drawn here on a possible structure-function relationship.

Amino Acid Sequence↗

PubMed1998

A distributed environment for physical map construction.

MOTIVATION: With the main focus of the Human Genome Project shifting to sequencing, bioinformatics support for constructing large-scale genomic maps of other organisms is still required. We attempt to provide for this with our work, aimed at the delivery of robust and user-friendly contig-building software on the WWW. RESULTS: We present a prototype distributed analytical environment for molecular biologists working in the area of genomic mapping. It consists of the WWW server for constructing contigs from users' data with a hypertext output connected to Java-based map visualization software. AVAILABILITY: Freely available on http://www.mpimg-berlin-dahlem.mpg. de/ approximately andy/server/ CONTACT: andy@rag3.rz-berlin.mpg.de

Algorithms↗

PubMed2006

GARBAN II: an integrative framework for extracting biological information from proteomic and genomic data.

Genomic and proteomic analyses generate a massive amount of data that requires specific bioinformatic tools for its management and interpretation. GARBAN II, developed from the previous GARBAN platform, provides an integrated framework to simultaneously analyse and compare multiple datasets from DNA microarrays and proteomic studies. The general architecture, gene classification and comparison, and graphical representation have been redesigned to ensure a user-friendly feature and to improve the capabilities and efficiency of this system. Additionally, GARBAN II has been extended with new applications to display networks of coexpressed genes and to integrate access to BioRag and MotifScanner so as to facilitate the holistic analysis of users' data.

Animals↗

PubMed2026

transfactor: transcription factor activity estimation via probabilistic gene expression deconvolution.

Gene expression is a primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential gene expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies. Single-cell RNA-sequencing; TF activity; bioinformatics; GRN.

Transcription Factors↗

PubMed2007

Cold nights impair leaf growth and cell cycle progression in maize through transcriptional changes of cell cycle genes.

Low temperature inhibits the growth of maize (Zea mays) seedlings and limits yield under field conditions. To study the mechanism of cold-induced growth retardation, we exposed maize B73 seedlings to low night temperature (25 degrees C /4 degrees C, day/night) from germination until the completion of leaf 4 expansion. This treatment resulted in a 20% reduction in final leaf size compared to control conditions (25 degrees C/18 degrees C, day/night). A kinematic analysis of leaf growth rates in control and cold-treated leaves during daytime showed that cold nights affected both cell cycle time (+65%) and cell production (-22%). In contrast, the size of mature epidermal cells was unaffected. To analyze the effect on cell cycle progression at the molecular level, we identified through a bioinformatics approach a set of 43 cell cycle genes and analyzed their expression in proliferating, expanding, and mature cells of leaves exposed to either control or cold nights. This analysis showed that: (1) the majority of cell cycle genes had a consistent proliferation-specific expression pattern; and (2) the increased cell cycle time in the basal meristem of leaves exposed to cold nights was associated with differential expression of cell cycle inhibitors and with the concomitant down-regulation of positive regulators of cell division.

Biomechanical Phenomena↗

PubMed2026

Common Molecular Mechanisms and Candidate Drug Targets in Type 2 Diabetes Mellitus and Atherosclerotic Cardiovascular Disease.

This study examined the mechanisms underlying the comorbidity between type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD), while identifying potential therapeutic targets. Common differentially expressed genes (C-DEGs) between T2DM and ASCVD were extracted from the GSE78721 and GSE12288 datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, protein-protein interaction (PPI) network construction, hub gene identification, and Drug-Gene Interaction Database (DGIdb) analysis were conducted. The association between hub C-DEGs and immune-infiltrating cells was analyzed using the CIBERSORT method. Expression levels of hub C-DEGs were quantified through qRT-PCR and Western blot analyses. A total of 32 C-DEGs were identified, comprising 20 upregulated and 12 downregulated genes. C-DEGs were predominantly enriched in key pathways, including viral myocarditis, arrhythmogenic right ventricular cardiomyopathy, hypertrophic cardiomyopathy, and dilated cardiomyopathy. PPI analysis revealed 29 nodes and 39 edges, leading to the identification of eight hub C-DEGs (HSP90B1, PLAU, SLPI, TOP3A, NCF4, PRF1, TUBA1C, and CS) across both datasets. Furthermore, hub C-DEGs (TOP3A, SLPI, NCF4, PRF1, and PLAU) demonstrated significant correlations with immune-infiltrating cell levels. Drugs specifically targeting these hub C-DEGs present promising candidates for the treatment of T2DM and ASCVD. Additionally, the expression of hub C-DEGs at both mRNA and protein levels was validated in patients with T2DM and ASCVD. An integrated bioinformatics analysis facilitated the screening of candidate therapeutic targets, mechanisms, and drugs for T2DM and ASCVD, offering new insights into molecular therapies for these conditions.

Diabetes Mellitus, Type 2↗