Address: http://bioinformatics.biol.uoa.gr/GNOMM

The Outer Membranes of Gram-negative bacteria are asymmetric lipid bilayers, composed by standard lipids in the inner leaflet and mostly lipopolysaccharides (LPSs) in their outer leaflet. Outer membranes and their components are of critical importance for bacterial cell structure and function, as outer membrane proteins can regulate a diverse range of functions, while the organization and dynamics of LPSs can influence bacterial resistance against antimicrobial agents and cause toxic reactions in human hosts, leading to a number of diseases.
Despite their significance, the experimental study of outer membranes is challenging. Molecular Dynamics (MD) simulations can be a useful tool in modeling the structure and dynamics of membranes and membrane proteins. However, the preparation and simulation of outer membrane proteins in their native LPS-containing outer membrane environment is not straightforward.
The Gram-Negative Outer Membrane Modeler (GNOMM) is an automated workflow for the construction of LPS-rich outer membrane systems in MD simulations. GNOMM currently supports four widely used force fields, namely, the CHARMM36 all-atom, GROMOS 54A7 united-atom, MARTINI coarse-grained and PACE hybrid resolution models, and enables the building of membrane and protein-membrane systems with complex lipid bilayers containing LPSs. The generated output configurations can be subsequently used to perform Molecular Dynamics simulations with the freely available, high performance GROMACS simulation engine.

*Co-created with Mrs Avgi-Elena Apostolakou, Msc.
Address: http://bioinformatics.biol.uoa.gr/hGPCRnet

The Extended Human GPCR Network (hGPCRnet) is a web application presenting novel network approach in the study of protein-protein interactions of GPCR signaling pathways, combined with cell expression evidence from over 70 distinct tissues.  It allows for the concurrent study of all major GPCR signaling pathways (G-protein, β-arrestin, oligomerization etc) with the additional integration of cell specificity information, thus leading to a more directed view of GPCR functionality in a specific cell type.  This combination of network analysis with cell expression evidence enables a more directed approach in studying GPCR signaling and pharmacology.

Address: http://bioinformatics.biol.uoa.gr/nucenvdb

The Nuclear Envelope is a double membrane system surrounding the nucleus of eukaryotic cells. It consists of two membranes with distinct features, the outer and the inner nuclear membranes. A large number of proteins located at the Envelope have been identified, performing a wide variety of functions, from the bidirectional exchange of molecules between the cytoplasm and the nucleus and the correct positioning of the nucleus in the cell to chromatin tethering, genome organization, regulation of signaling cascades and even transporting enormous cargo. In fact, it is already prominent that the complexity of the Nuclear Envelope rivals that of the plasma membrane.
NucEnvDB is a publicly available database of Nuclear Envelope proteins and their interactions. The database currently contains information on 2863 manually annotated proteins with known presence in the Nuclear Envelope, obtained from 394 species. Each database entry contains useful annotation including a detailed description of the protein’s subcellular location, its position in the Nuclear Envelope, its interactions with other proteins and cross-references to major biological repositories.
Through the NucEnvDB web interface, users can perform simple or advanced text searches, as well as BLAST and HMMER queries against the database’s protein sequences and domains. Furthermore, they can create, analyze and export protein-protein interaction networks from the database’s components, using a specially designed network preparation pipeline that applies Cytoscape.js and the Markov Clustering algorithm (MCL). Finally, they can perform functional enrichment analysis on database components using WebGestaltR, an R implementation of the WEB-based Gene SeT AnaLysis Toolkit (WebGestalt). The entire database is available for download in text, FASTA and XML formats.
NucEnvDB is currently the only available repository focused on the Nuclear Envelope and its protein components. Given the rising interest in studying the Nuclear Envelope, a previously unattended subcellular component, we expect NucEnvDB to be a valuable resource for genome-wide and/or proteome-wide analyses and, potentially, the design of novel prediction algorithms aimed at Nuclear Envelope proteins.

*Co-created with Mr George Spannogiannis and Mr. George Filis, Msc
Address: http://bioinformatics.biol.uoa.gr/RTK-PRED

Signal transduction is an essential process for the survival of all multicellular organisms. It regulates several biological functions including cellular proliferation, apoptosis and maintenance of homeostasis. In metazoa, a protein family with a significant role in signal transduction includes protein tyrosine kinases (PTKs). A distinguishable group of PTKs is formed by transmembrane receptor tyrosine kinases (RTKs). Their extracellular N-terminus constitutes the binding site for hormones and growth factors, while their intracellular C-terminus catalyzes the phosphorylation of tyrosine residues. RTKs have been implicated in severe diseases such as cancer, neurodegenerative and cardiovascular diseases.
RTK-PRED combines profile Hidden Makov Models (pHMMs) with a transmembrane prediction algorithm, PHOBIUS (http://phobius.sbc.su.se/) for the automated detection and annotation of RTKs from sequence alone.

*Co-created with Mrs Sofia Zafeiropoulou, Msc
Address: http:onthefly.pavlopouloslab.info

Retrieving all of the necessary information from databases about bioentities mentioned in an article is not a trivial or an easy task. Following the daily literature about a specific biological topic and collecting all the necessary information about the bioentities mentioned in the literature manually is tedious and time consuming. OnTheFly2.0 is a web application mainly designed for non-computer experts which aims to automate data collection and knowledge extraction from biological literature in a user friendly and efficient way. OnTheFly2.0 is able to extract bioentities from individual articles such as HTML, plain text, Microsoft Word, Excel and PDF files. Through an intuitive and easy-to-use graphical interface, the text of a document is extensively parsed for bioentities such as protein and gene names, chemical compounds, organisms, environmental entities and ontology terms. Utilizing high quality data integration platforms, OnTheFly2.0 allows the generation of informative summaries, interaction networks and at-a-glance popup windows containing knowledge related to the bioentities found in documents.  

 

*Co-created with Mr Ioannis Kasionis, Bsc and Dr. Evangelos Karatzas, PhD
Address: http://darling.pavlopouloslab.info

Finding, exploring and filtering frequent sentence-based associations between a disease and a biomedical entity co-mentioned in disease-related PubMed literature is a challenge, as the volume of publications increases. Darling is a web application which utilizes Name Entity Recognition to identify human related biomedical terms in PubMed articles mentioned in OMIM, DisGeNET and Human Phenotype Ontology (HPO) disease records and generates an interactive biomedical entity association network. Nodes in this network represent genes, proteins, chemicals, functions, tissues, diseases, environments and phenotypes. Users can search by identifiers, terms/entities or free text and explore the relevant abstracts in an annotated format.