BACKGROUND: The advancement of nanotechnology underscores the imperative need for establishing in silico predictive models to assess safety, particularly in the context of chronic respiratory afflictions such as lung fibrosis, a pathogenic transformation that is irreversible. While the compilation of predictive descriptors is pivotal for in silico model development, key features specifically tailored for predicting lung fibrosis remain elusive. This study aimed to uncover the essential predictive descriptors governing nanoparticle-induced pulmonary fibrosis. METHODS: We conducted a comprehensive analysis of the trajectory of metal oxide nanoparticles (MeONPs) within pulmonary systems. Two biological media (simulated lung fluid and phagolysosomal simulated fluid) and two cell lines (macrophages and epithelial cells) were meticulously chosen to scrutinize MeONP behaviors. Their interactions with MeONPs, also referred to as nano-bio interactions, can lead to alterations in the properties of the MeONPs as well as specific cellular responses. Physicochemical properties of MeONPs were assessed in biological media. The impact of MeONPs on cell membranes, lysosomes, mitochondria, and cytoplasmic components was evaluated using fluorescent probes, colorimetric enzyme substrates, and ELISA. The fibrogenic potential of MeONPs in mouse lungs was assessed by examining collagen deposition and growth factor release. Random forest classification was employed for analyzing in chemico, in vitro and in vivo data to identify predictive descriptors. RESULTS: The nano-bio interactions induced diverse changes in the 4 characteristics of MeONPs and had variable effects on the 14 cellular functions, which were quantitatively evaluated in chemico and in vitro. Among these 18 quantitative features, seven features were found to play key roles in predicting the pro-fibrogenic potential of MeONPs. Notably, IL-1β was identified as the most important feature, contributing 27.8% to the model's prediction. Mitochondrial activity (specifically NADH levels) in macrophages followed closely with a contribution of 17.6%. The remaining five key features include TGF-β1 release and NADH levels in epithelial cells, dissolution in lysosomal simulated fluids, zeta potential, and the hydrodynamic size of MeONPs. CONCLUSIONS: The pro-fibrogenic potential of MeONPs can be predicted by combination of key features at nano-bio interfaces, simulating their behavior and interactions within the lung environment. Among the 18 quantitative features, a combination of seven in chemico and in vitro descriptors could be leveraged to predict lung fibrosis in animals. Our findings offer crucial insights for developing in silico predictive models for nano-induced pulmonary fibrosis.

• Keywords
• biotransformation, lung fibrosis, nanosafety, nanotoxicity, predictive toxicology,
• MeSH
• A549 Cells MeSH
• Metal Nanoparticles * toxicity   chemistry   MeSH
• Humans MeSH
• Mice, Inbred C57BL MeSH
• Mice MeSH
• Lung drug effects   pathology   metabolism   MeSH
• Pulmonary Fibrosis * chemically induced   metabolism   pathology   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

UNLABELLED: The transport of ligands, ions or solvent molecules into proteins with buried binding sites or through the membrane is enabled by protein tunnels and channels. CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics. AVAILABILITY AND IMPLEMENTATION: CAVER Analyst is a multi-platform software written in JAVA. Binaries and documentation are freely available for non-commercial use at http://www.caver.cz.

• MeSH
• Ligands MeSH
• Computer Graphics * MeSH
• Proteins chemistry   metabolism   MeSH
• Software * MeSH
• User-Computer Interface MeSH
• Binding Sites MeSH
• Computational Biology methods   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Ligands MeSH
• Proteins MeSH

Probiotics or bacteriotherapy is today's hot issue for public entities (Food and Agriculture Organization, and World Health Organization) as well as health and food industries since Metchnikoff and his colleagues hypothesized the correlation between probiotic consumption and human's health. They contribute to the newest and highly efficient arena of promising biotherapeutics. These are usually attractive in biomedical applications such as gut-related diseases like irritable bowel disease, diarrhea, gastrointestinal disorders, fungal infections, various allergies, parasitic and bacterial infections, viral diseases, and intestinal inflammation, and are also worth immunomodulation. The useful impact of probiotics is not limited to gut-related diseases alone. Still, these have proven benefits in various acute and chronic infectious diseases, like cancer, human immunodeficiency virus (HIV) diseases, and high serum cholesterol. Recently, different researchers have paid special attention to investigating biomedical applications of probiotics, but consolidated data regarding bacteriotherapy with a detailed mechanistically applied approach is scarce and controversial. The present article reviews the bio-interface of probiotic strains, mainly (i) why the demand for probiotics?, (ii) the current status of probiotics, (iii) an alternative to antibiotics, (iv) the potential applications towards disease management, (v) probiotics and industrialization, and (vi) futuristic approach.

• Keywords
• Antibiotics, Bio-interface, Gut-associated diseases, Immunomodulation, Probiotics,
• MeSH
• Bacteria * drug effects   MeSH
• Gastrointestinal Diseases therapy   immunology   microbiology   MeSH
• Immunologic Factors therapeutic use   MeSH
• Immunomodulation MeSH
• Humans MeSH
• Disease Management MeSH
• Probiotics * therapeutic use   administration & dosage   MeSH
• Secondary Metabolism MeSH
• Gastrointestinal Microbiome MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Immunologic Factors MeSH

Protein interactions play a crucial role among the different functions of a cell and are central to our understanding of cellular processes both in health and disease. Here we present Galaxy InteractoMIX (http://galaxy.interactomix.com), a platform composed of 13 different computational tools each addressing specific aspects of the study of protein-protein interactions, ranging from large-scale cross-species protein-wide interactomes to atomic resolution level of protein complexes. Galaxy InteractoMIX provides an intuitive interface where users can retrieve consolidated interactomics data distributed across several databases or uncover links between diseases and genes by analyzing the interactomes underlying these diseases. The platform makes possible large-scale prediction and curation protein interactions using the conservation of motifs, interology, or presence or absence of key sequence signatures. The range of structure-based tools includes modeling and analysis of protein complexes, delineation of interfaces and the modeling of peptides acting as inhibitors of protein-protein interactions. Galaxy InteractoMIX includes a range of ready-to-use workflows to run complex analyses requiring minimal intervention by users. The potential range of applications of the platform covers different aspects of life science, biomedicine, biotechnology and drug discovery where protein associations are studied.

• Keywords
• Galaxy platform, integration, interactomics, network analyses, workflows,
• MeSH
• Amino Acid Motifs MeSH
• Conserved Sequence MeSH
• Protein Interaction Mapping * MeSH
• Models, Molecular MeSH
• Workflow MeSH
• Software * MeSH
• User-Computer Interface MeSH
• Computational Biology methods   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Channels, tunnels, and pores serve as pathways for the transport of molecules and ions through protein structures, thus participating to their functions. MOLEonline ( https://mole.upol.cz ) is an interactive web-based tool with enhanced capabilities for detecting and characterizing channels, tunnels, and pores within protein structures. MOLEonline has two distinct calculation modes for analysis of channel and tunnels or transmembrane pores. This application gives researchers rich analytical insights into channel detection, structural characterization, and physicochemical properties. ChannelsDB 2.0 ( https://channelsdb2.biodata.ceitec.cz/ ) is a comprehensive database that offers information on the location, geometry, and physicochemical characteristics of tunnels and pores within macromolecular structures deposited in Protein Data Bank and AlphaFill databases. These tunnels are sourced from manual deposition from literature and automatic detection using software tools MOLE and CAVER. MOLEonline and ChannelsDB visualization is powered by the LiteMol Viewer and Mol* viewer, ensuring a user-friendly workspace. This chapter provides an overview of user applications and usage.

• Keywords
• Biomacromolecule, PDB, Physicochemical properties, Pore, Protein, Residues, Tunnel, Visualization, Voronoi, mmCIF, Channel,
• MeSH
• Databases, Protein * MeSH
• Web Browser MeSH
• Ion Channels metabolism   chemistry   MeSH
• Protein Conformation MeSH
• Models, Molecular MeSH
• Proteins chemistry   metabolism   MeSH
• Software * MeSH
• User-Computer Interface MeSH
• Computational Biology methods   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Ion Channels MeSH
• Proteins MeSH

BACKGROUND: Slow-fast analysis is a simple and effective method to reduce the influence of substitution saturation, one of the causes of phylogenetic noise and long branch attraction (LBA) artifacts. In several steps of increasing stringency, the slow-fast analysis omits the fastest substituting alignment positions from the analysed dataset and thus increases its signal/noise ratio. RESULTS: Our program SlowFaster automates the process of assessing the substitution rate of the alignment positions and the process of producing new alignments by deleting the saturated positions. Its use is very simple. It goes through the whole process in several steps: data input - necessary choices - production of new alignments. CONCLUSION: SlowFaster is a user-friendly tool providing new alignments prepared with slow-fast analysis. These data can be used for further phylogenetic analyses with lower risk of long branch attraction artifacts.

• MeSH
• Blastocystis genetics   MeSH
• Time Factors MeSH
• Phylogeny * MeSH
• DNA, Protozoan MeSH
• Sequence Alignment MeSH
• User-Computer Interface * MeSH
• Computational Biology methods   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA, Protozoan MeSH

MOTIVATION: One of the objectives of protein engineering is to propose and construct modified proteins with improved activity for the substrate of interest. Systematic computational investigation of many protein variants requires the preparation and handling of a large number of data files. The type of the data generated during the modelling of protein variants and the estimation of their activities offers the possibility of process automatization. RESULTS: The graphical program TRITON has been developed for modelling protein mutants and assessment of their activities. Protein mutants are modelled from the wild type structure by homology modelling using the external program MODELLER. Chemical reactions taking place in the mutants active site are modelled using the semi-empirical quantum mechanic program MOPAC. Semi-quantitative predictions of mutants activities can be achieved by evaluating the changes in energies of the system and partial atomic charges of active site residues during the reaction. The program TRITON offers graphical tools for the preparation of the input data files, for calculation and for the analysis of the generated output data. AVAILABILITY: The program TRITON can run under operating systems IRIX, Linux and NetBSD. The software is available at http://www.chemi.muni.cz/lbsd/triton.ht ml.

• MeSH
• Models, Chemical MeSH
• Enzymes chemistry   genetics   MeSH
• Catalysis MeSH
• Mutation genetics   MeSH
• Computer Simulation * MeSH
• Protein Engineering methods   MeSH
• Sequence Homology, Amino Acid MeSH
• Software * MeSH
• User-Computer Interface MeSH
• Binding Sites genetics   MeSH
• Computational Biology methods   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Enzymes MeSH

A common Authentication and Authorisation Infrastructure (AAI) that would allow single sign-on to services has been identified as a key enabler for European bioinformatics. ELIXIR AAI is an ELIXIR service portfolio for authenticating researchers to ELIXIR services and assisting these services on user privileges during research usage. It relieves the scientific service providers from managing the user identities and authorisation themselves, enables the researcher to have a single set of credentials to all ELIXIR services and supports meeting the requirements imposed by the data protection laws. ELIXIR AAI was launched in late 2016 and is part of the ELIXIR Compute platform portfolio. By the end of 2017 the number of users reached 1000, while the number of relying scientific services was 36. This paper presents the requirements and design of the ELIXIR AAI and the policies related to its use, and how it can be used for serving some example services, such as document management, social media, data discovery, human data access, cloud compute and training services.

• Keywords
• GA4GH, GDPR, IAM, authentication, authorisation, data access,
• MeSH
• Biomedical Research methods   MeSH
• Humans MeSH
• Software * MeSH
• Database Management Systems * MeSH
• User-Computer Interface MeSH
• Computational Biology methods   MeSH
• Research Personnel MeSH
• Computer Security * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design.Significance: In order to facilitate access of research groups without bioinformatics support to public transcriptomics data, we have developed a free online tool with an easy-to-use interface that allows researchers to obtain quality information in a readily publishable format. Cancer Res; 78(21); 6320-8. ©2018 AACR.

• MeSH
• Algorithms MeSH
• Databases, Factual MeSH
• Databases, Genetic MeSH
• Genomics MeSH
• Internet MeSH
• Medical Oncology MeSH
• Humans MeSH
• Neoplasms genetics   MeSH
• Computer Graphics MeSH
• Proteomics MeSH
• Workflow MeSH
• Software MeSH
• Transcriptome MeSH
• User-Computer Interface MeSH
• Computational Biology methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: Genetic testing rapidly penetrates into all medical specialties and medical students must acquire skills in this area. However, many of them consider it difficult. Furthermore, many find these topics less appealing and not connected to their future specialization in different fields of clinical medicine. Student-centred strategies such as problem-based learning, gamification and the use of real data can increase the appeal of a difficult topic such as genetic testing, a field at the crossroads of genetics, molecular biology and bioinformatics. METHODS: We designed an electronic teaching application which students registered in the undergraduate Medical Biology course can access online. A study was carried out to assess the influence of implementation of the new method. We performed pretest/posttest evaluation and analyzed the results using the sign test with median values. We also collected students' personal comments. RESULTS: The newly developed interactive application simulates the process of molecular genetic diagnostics of a hereditary disorder in a family. Thirteen tasks guide students through clinical and laboratory steps needed to reach the final diagnosis. Genetics and genomics are fields strongly dependent on electronic databases and computer-based data analysis tools. The tasks employ publicly available internet bioinformatic resources used routinely in medical genetics departments worldwide. Authenticity is assured by the use of modified and de-identified clinical and laboratory data from real families analyzed in our previous research projects. Each task contains links to databases and data processing tools needed to solve the task, and an answer box. If the entered answer is correct, the system allows the user to proceed to the next task. The solving of consecutive tasks arranged into a single narrative resembles a computer game, making the concept appealing. There was a statistically significant improvement of knowledge and skills after the practical class, and most comments on the application were positive. A demo version is available at https://medbio.lf2.cuni.cz/demo_m/ . Full version is available on request from the authors. CONCLUSIONS: Our concept proved to be appealing to the students and effective in teaching medical molecular genetics. It can be modified for training in the use of electronic information resources in other medical specialties.

• Keywords
• Bioinformatics, E-learning, Gamification, Genomics, Interactive teaching application, Medical databases, Medical genetics, Problem-based learning,
• MeSH
• Genetic Diseases, Inborn diagnosis   MeSH
• Genetic Testing * MeSH
• Genetics, Medical education   MeSH
• Humans MeSH
• Molecular Medicine education   MeSH
• Computer-Assisted Instruction * MeSH
• Problem-Based Learning MeSH
• Education, Medical, Undergraduate methods   MeSH
• User-Computer Interface MeSH
• Video Games MeSH
• Computational Biology education   MeSH
• Teaching MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Evaluation Study MeSH