DNA microarray integromics analysis platform

Background: The study of interactions between molecules belonging to different biochemical families (such as lipids and nucleic acids) requires specialized data analysis methods. This article describes the DNA Microarray Integromics Analysis Platform, a unique web application that focuses on computational integration and analysis of "multi-omics" data. Our tool supports a range of complex analyses, including - among others - low- and high-level analyses of DNA microarray data, integrated analysis of transcriptomics and lipidomics data and the ability to infer miRNA-mRNA interactions. Results: We demonstrate the characteristics and benefits of the DNA Microarray Integromics Analysis Platform using two different test cases. The first test case involves the analysis of the nutrimouse dataset, which contains measurements of the expression of genes involved in nutritional problems and the concentrations of hepatic fatty acids. The second test case involves the analysis of miRNA-mRNA interactions in polysaccharide-stimulated human dermal fibroblasts infected with porcine endogenous retroviruses. Conclusions: The DNA Microarray Integromics Analysis Platform is a web-based graphical user interface for "multi-omics" data management and analysis. Its intuitive nature and wide range of available workflows make it an effective tool for molecular biology research. The platform is hosted at https://lifescience.plgrid.pl

Intermediates in the Protein Folding Process: A Computational Model

The paper presents a model for simulating the protein folding process in silico. The two-step model (which consists of the early stage—ES and the late stage—LS) is verified using two proteins, one of which is treated (according to experimental observations) as the early stage and the second as an example of the LS step. The early stage is based solely on backbone structural preferences, while the LS model takes into account the water environment, treated as an external hydrophobic force field and represented by a 3D Gauss function. The characteristics of 1ZTR (the ES intermediate, as compared with 1ENH, which is the LS intermediate) confirm the link between the gradual disappearance of ES characteristics in LS structural forms and the simultaneous emergence of LS properties in the 1ENH protein. Positive verification of ES and LS characteristics in these two proteins (1ZTR and 1ENH respectively) suggest potential applicability of the presented model to in silico protein folding simulations

Prediction of Functional Sites Based on the Fuzzy Oil Drop Model

A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localization of active sites in proteins. This paper describes a computational model that can be used to identify potential areas that are able to interact with other molecules (ligands, substrates, inhibitors, etc.). The model for active site recognition is based on the analysis of hydrophobicity distribution in protein molecules. It is shown, based on the analyses of proteins with known biological activity and of proteins of unknown function, that the region of significantly irregular hydrophobicity distribution in proteins appears to be function related

Introducing the Brassica Information Portal: Towards integrating genotypic and phenotypic Brassica crop data [version 1; referees: 2 approved]

The Brassica Information Portal (BIP) is a centralised repository for Brassica phenotypic data. Trait data associated with Brassica research and breeding experiments conducted on Brassica crops, used as vegetables, for livestock fodder and biofuels, is hosted on the site, together with information on the experimental plant materials used, as well as trial design. BIP is an open access and open source project, built on the schema of CropStoreDB, and as such can provide trait data management strategies for any crop data. A new user interface and programmatic submission/retrieval system helps to simplify data access for scientists and breeders. BIP opens up the opportunity to apply big data analyses to data generated by the Brassica Research Community. Here, we present a short description of the current status of the repository

Fuzzy oil drop model to interpret the structure of antifreeze proteins and their mutants

Mutations in proteins introduce structural changes and influence biological activity: the specific effects depend on the location of the mutation. The simple method proposed in the present paper is based on a two-step model of in silico protein folding. The structure of the first intermediate is assumed to be determined solely by backbone conformation. The structure of the second one is assumed to be determined by the presence of a hydrophobic center. The comparable structural analysis of the set of mutants is performed to identify the mutant-induced structural changes. The changes of the hydrophobic core organization measured by the divergence entropy allows quantitative comparison estimating the relative structural changes upon mutation. The set of antifreeze proteins, which appeared to represent the hydrophobic core structure accordant with “fuzzy oil drop” model was selected for analysis

Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment - GPCR Dock 2008 - was conducted in coordination with the publication of the crystal structure of the human adenosine A2Areceptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops

Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome.

The Polycomb repressive complexes PRC1 and PRC2 maintain embryonic stem cell (ESC) pluripotency by silencing lineage-specifying developmental regulator genes. Emerging evidence suggests that Polycomb complexes act through controlling spatial genome organization. We show that PRC1 functions as a master regulator of mouse ESC genome architecture by organizing genes in three-dimensional interaction networks. The strongest spatial network is composed of the four Hox gene clusters and early developmental transcription factor genes, the majority of which contact poised enhancers. Removal of Polycomb repression leads to disruption of promoter-promoter contacts in the Hox gene network. In contrast, promoter-enhancer contacts are maintained in the absence of Polycomb repression, with accompanying widespread acquisition of active chromatin signatures at network enhancers and pronounced transcriptional upregulation of network genes. Thus, PRC1 physically constrains developmental transcription factor genes and their enhancers in a silenced but poised spatial network. We propose that the selective release of genes from this spatial network underlies cell fate specification during early embryonic development