The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

Database Commons: A Catalog of Worldwide Biological Databases

Biological databases serve as a global fundamental infrastructure for the worldwide scientific community, which dramatically aid the transformation of big data into knowledge discovery and drive significant innovations in a wide range of research fields. Given the rapid data production, biological databases continue to increase in size and importance. To build a catalog of worldwide biological databases, we curate a total of 5825 biological databases from 8931 publications, which are geographically distributed in 72 countries/regions and developed by 1975 institutions (as of September 20, 2022). We further devise a z-index, a novel index to characterize the scientific impact of a database, and rank all these biological databases as well as their hosting institutions and countries in terms of citation and z-index. Consequently, we present a series of statistics and trends of worldwide biological databases, yielding a global perspective to better understand their status and impact for life and health sciences. An up-to-date catalog of worldwide biological databases, as well as their curated meta-information and derived statistics, is publicly available at Database Commons (https://ngdc.cncb.ac.cn/databasecommons/).

Pharmacological network study on the effect of 6-gingerol on cervical cancer using computerized databases

Cervical cancer (CC) is the most frequent cancer in the female population worldwide. Although there are treatments available, they are ineffective and cause adverse effects. 6-gingerol is an active component in ginger with anticancer activity. This research aims to discover the mechanism by which 6-gingerol act as an anticancer agent on CC through a pharmacological network using bioinformatics databases. From MalaCard, Swiss Target Prediction, Comparative Toxicogenomics Database, and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, we obtained the target genes for 6-gingerol and CC and matched them. We got 26 genes and analyzed them in ShinyGO-0.76.3 and DAVID-Bioinformatics Resources. Then, we generated a protein-protein interaction network in Cytoscape and obtained 12 hub genes. Hub genes were analyzed in Gene Expression Profiling Interactive Analysis and TISIDB. In addition, molecular docking studies were performed between target proteins with 6-gingerol using SwissDock database. Finally, molecular dynamics studies for three proteins with the lowest interaction energy were implemented using Gromacs software. According to gene ontology results, 6-gingerol is involved in processes of apoptosis, cell cycle, and protein kinase complexes, affecting mitochondria and pathways related to HPV infection. CTNNB1 gene was negatively correlated with CD8+ infiltration but was not associated with a higher survival rate. Furthermore, the molecular docking study showed that 6-gingerol has a high binding to proteins, and the molecular dynamics showed a stable interaction of 6-gingerol to AKT1, CCNB1, and CTNNB1 proteins. Conclusion, our work helps to understand the anticancer activity of 6-gingerol in CC that should be studied experimentally.Communicated by Ramaswamy H. Sarma.

Design and Synthesis of Novel 5-((3-(Trifluoromethyl)piperidin-1-yl)sulfonyl)indoline-2,3-dione Derivatives as Promising Antiviral Agents: In Vitro, In Silico, and Structure-Activity Relationship Studies

Herein, a series of new isatin derivatives was designed and synthesized (1-9) as broad-spectrum antiviral agents. Consequently, the antiviral activities of the synthesized compounds (1-9) were pursued against three viruses, namely influenza virus (H1N1), herpes simplex virus 1 (HSV-1), and coxsackievirus B3 (COX-B3). In particular, compounds 9, 5, and 4 displayed the highest antiviral activity against H1N1, HSV-1, and COX-B3 with IC50 values of 0.0027, 0.0022, and 0.0092 µM, respectively. Compound 7 was the safest, with a CC50 value of 315,578.68 µM. Moreover, a quantitative PCR (real-time PCR) assay was carried out for the most relevant compounds. The selected compounds exhibited a decrease in viral gene expression. Additionally, the conducted in silico studies emphasized the binding affinities of the synthesized compounds and their reliable pharmacokinetic properties as well. Finally, a structure-antiviral activity relationship study was conducted to anticipate the antiviral activity change upon future structural modification.

Elucidation of the Bovine Intramammary Bacteriome and Resistome from healthy cows of Swiss dairy farms in the Canton Tessin

Healthy, untreated cows of nine dairy herds from the Swiss Canton Tessin were analyzed three times within one year to identify the most abundant species of the intramammary bacteriome. Aseptically collected milk samples were cultured and bacteria identified using MALDI-TOF. Of 256 cows analyzed, 96% were bacteriologically positive and 80% of the 1,024 quarters were positive for at least one bacterial species. 84.5% of the quarters were healthy with somatic cell counts (SCC) < 200,000 cells/mL, whereas 15.5% of the quarters showed a subclinical mastitis (SCC ≥ 200,000 cells/mL). We could assign 1,288 isolates to 104 different bacterial species including 23 predominant species. Non-aureus staphylococci and mammaliicocci (NASM) were most prevalent (14 different species; 73.5% quarters). Staphylococcus xylosus and Mammaliicoccus sciuri accounted for 74.7% of all NASM isolates. To describe the intramammary resistome, 350 isolates of the predominant species were selected and subjected to short-read whole genome sequencing (WGS) and phenotypic antibiotic resistance profiling. While complete genomes of eight type strains were available, the remaining 15 were de novo assembled with long reads as a resource for the community. The 23 complete genomes served for reference-based assembly of the Illumina WGS data. Both chromosomes and mobile genetic elements were examined for antibiotic resistance genes (ARGs) using in-house and online software tools. ARGs were then correlated with phenotypic antibiotic resistance data from minimum inhibitory concentration (MIC). Phenotypic and genomic antimicrobial resistance was isolate-specific. Resistance to clindamycin and oxacillin was most frequently observed (65 and 30%) in Staphylococcus xylosus but could not be linked to chromosomal or plasmid-borne ARGs. However, in several cases, the observed antimicrobial resistance could be explained by the presence of mobile genetic elements like tetK carried on small plasmids. This represents a possible mechanism of transfer between non-pathogenic bacteria and pathogens of the mammary gland within and between herds. The-to our knowledge-most extensive bacteriome reported and the first attempt to link it with the resistome promise to profoundly affect veterinary bacteriology in the future and are highly relevant in a One Health context, in particular for mastitis, the treatment of which still heavily relies on antibiotics.

Phytochemical profiling and cytotoxic potential of Arnebia nobilis root extracts against hepatocellular carcinoma using in-vitro and in-silico approaches

Hepatocellular carcinoma is the fifth most prevalent cancer worldwide. The emergence of drug resistance and other adverse effects in available anticancer options are challenging to explore natural sources. The current study was designed to decipher the Arnebia nobilis (A. nobilis) extracts for detecting phytochemicals, in-vitro evaluation of antioxidative and cytotoxic potentials, and in-silico prediction of potent anticancer compounds. The phytochemical analysis revealed the presence of flavonoids, phenols, tannins, alkaloids, quinones, and cardiac glycosides, in the ethanol (ANE) and n-hexane (ANH) extracts of A. nobilis. ANH extract exhibited a better antioxidant potential to scavenge DPPH, nitric oxide and superoxide anion radicals than ANE extract, which showed better potential only against H2O2 radicals. In 24 h treatment, ANH extract revealed higher cytotoxicity (IC50 value: 22.77 µg/mL) than ANH extract (IC50 value: 46.74 µg/mL) on cancer (HepG2) cells without intoxicating the normal (BHK) cells using MTT assay. A better apoptotic potential was observed in ANH extract (49.10%) compared to ANE extract (41.35%) on HepG2 cells using the annexin V/PI method. GCMS analysis of ANH extract identified 35 phytocompounds, from which only 14 bioactive compounds were selected for molecular docking based on druggability criteria and toxicity filters. Among the five top scorers, deoxyshikonin exhibited the best binding affinities of - 7.2, - 9.2, - 7.2 and - 9.2 kcal/mol against TNF-α, TGF-βR1, Bcl-2 and iNOS, respectively, followed by ethyl cholate and 2-Methyl-6-(4-methylphenyl)hept-2-en-4-one along with their desirable ADMET properties. The phytochemicals of ANH extract could be used as a promising drug candidate for liver cancer after further validations.

Structure based design and synthesis of 3-(7-nitro-3-oxo-3,4-dihydroquinoxalin-2-yl)propanehydrazide derivatives as novel bacterial DNA-gyrase inhibitors: In-vitro, In-vivo, In-silico and SAR studies

Antimicrobial resistance (AMR) is one of the critical challenges that have been encountered over the past years. On the other hand, bacterial DNA gyrase is regarded as one of the most outstanding biological targets that quinolones can extensively inhibit, improving AMR. Hence, a novel series of 3-(7-nitro-3-oxo-3,4-dihydroquinoxalin-2-yl)propanehydrazide derivatives (3-6j) were designed and synthesized employing the quinoxaline-2-one scaffold and relying on the pharmacophoric features experienced by the quinolone antibiotic; ciprofloxacin. The antibacterial activity of the synthesized compounds was assessed via in-vitro approaches using eight different Gram-positive and Gram-negative bacterial species. Most of the synthesized compounds revealed eligible antibacterial activities. In particular, compounds 6d and 6e displayed promising antibacterial activity among the investigated compounds. For example, compounds 6d and 6e displayed MIC values of 9.40 and 9.00 µM, respectively, regarding S. aureus, and 4.70 and 4.50 µM, respectively, regarding S. pneumonia in comparison to ciprofloxacin (12.07 µM). The cytotoxicity of compounds 6d and 6e were performed on normal human WI-38 cell lines with IC50 values of 288.69 and 227.64 μM, respectively assuring their safety and selectivity. Besides, DNA gyrase inhibition assay of compounds 6d and 6e was carried out in comparison to ciprofloxacin, and interestingly, compounds 6d and 6e disclosed promising IC50 values of 0.242 and 0.177 μM, respectively, whereas ciprofloxacin displayed an IC50 value of 0.768 μM, assuring the proposed mechanism of action for the afforded compounds. Consequently, compounds 6d and 6e were further assessed via in-vivo approaches by evaluating blood counts, liver and kidney functions, and histopathological examination. Both compounds were found to be safer on the liver and kidney than the reference ciprofloxacin. Moreover, in-silico molecular docking studies were established and revealed reasonable binding affinities for all afforded compounds, particularly compound 6d which exhibited a binding score of -7.51 kcal/mol, surpassing the reference ciprofloxacin (-7.29 kcal/mol) with better anticipated stability at the DNA gyrase binding pocket. Moreover, ADME studies were conducted, disclosing an eligible bioavailability score of >0.55 for all afforded compounds, and reasonable GIT absorption without passing the blood brain barrier was attained for most investigated compounds, ensuring their efficacy and safety. Lastly, a structure activity relationship study for the synthesized compounds was established and unveiled that not only the main pharmacophores required for DNA gyrase inhibition are enough for exerting promising antimicrobial activities, but also derivatization with diverse aryl/hetero aryl aldehydes is essential for their enhanced antimicrobial potential.

Systemic Lectin-Glycan Interaction of Pathogenic Enteric Bacteria in the Gastrointestinal Tract

Microorganisms, such as bacteria, viruses, and fungi, and host cells, such as plants and animals, have carbohydrate chains and lectins that reciprocally recognize one another. In hosts, the defense system is activated upon non-self-pattern recognition of microbial pathogen-associated molecular patterns. These are present in Gram-negative and Gram-positive bacteria and fungi. Glycan-based PAMPs are bound to a class of lectins that are widely distributed among eukaryotes. The first step of bacterial infection in humans is the adhesion of the pathogen's lectin-like proteins to the outer membrane surfaces of host cells, which are composed of glycans. Microbes and hosts binding to each other specifically is of critical importance. The adhesion factors used between pathogens and hosts remain unknown; therefore, research is needed to identify these factors to prevent intestinal infection or treat it in its early stages. This review aims to present a vision for the prevention and treatment of infectious diseases by identifying the role of the host glycans in the immune response against pathogenic intestinal bacteria through studies on the lectin-glycan interaction.

Female reproduction-specific proteins, origins in marine species, and their evolution in the animal kingdom

The survival of a species largely depends on the ability of individuals to reproduce, thus perpetuating their life history. The advent of metazoans (i.e. pluricellular animals) brought about the evolution of specialized tissues and organs, which in turn led to the development of complex protein regulatory pathways. This study sought to elucidate the evolutionary relationships between female reproduction-associated proteins by analyzing the transcriptomes of representative species from a selection of marine invertebrate phyla. Our study identified more than 50 reproduction-related genes across a wide evolutionary spectrum, from Porifera to Vertebrata. Among these, a total of 19 sequences had not been previously reported in at least one phylum, particularly in Porifera. Moreover, most of the structural differences between these proteins did not appear to be determined by environmental pressures or reproductive strategies, but largely obeyed a distinguishable evolutionary pattern from sponges to mammals.

Proteome-pI 2.0: proteome isoelectric point database update

Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.

Overcoming the Solubility Problem in E. coli: Available Approaches for Recombinant Protein Production

Despite the importance of recombinant protein production in the academy and industrial fields, many issues concerning the expression of soluble and homogeneous products are still unsolved. Several strategies were developed to overcome these obstacles; however, at present, there is no magic bullet that can be applied for all cases. Indeed, several key expression parameters need to be evaluated for each protein. Among the different hosts for protein expression, Escherichia coli is by far the most widely used. In this chapter, we review many of the different tools employed to circumvent protein insolubility problems.

A conserved Neurite Outgrowth and Guidance motif with biomimetic potential in neuronal Cell Adhesion Molecules

The discovery of conserved protein motifs can, in turn, unveil important regulatory signals, and when properly designed, synthetic peptides derived from such motifs can be used as biomimetics for biotechnological and therapeutic purposes. We report here that specific Ig-like repeats from the extracellular domains of neuronal Cell Adhesion Molecules share a highly conserved Neurite Outgrowth and Guidance (NOG) motif, which mediates homo- and heterophilic interactions crucial in neural development and repair. Synthetic peptides derived from the NOG motif of such proteins can boost neuritogenesis, and this potential is also retained by peptides with recombinant sequences, when fitting the NOG sequence pattern. The NOG motif discovery not only provides one more tile to the complex puzzle of neuritogenesis, but also opens the route to new neural regeneration strategies via a tunable biomimetic toolbox.

How do I get the most out of my protein sequence using bioinformatics tools?

Biochemical and biophysical experiments are essential for uncovering the three-dimensional structure and biological role of a protein of interest. However, meaningful predictions can frequently also be made using bioinformatics resources that transfer knowledge from a well studied protein to an uncharacterized protein based on their evolutionary relatedness. These predictions are helpful in developing specific hypotheses to guide wet-laboratory experiments. Commonly used bioinformatics resources include methods to identify and predict conserved sequence motifs, protein domains, transmembrane segments, signal sequences, and secondary as well as tertiary structure. Here, several such methods available through the MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) are described and how their combined use can provide meaningful information on a protein of unknown function is demonstrated. In particular, the identification of homologs of known structure using HHpred, internal repeats using HHrepID, coiled coils using PCOILS and DeepCoil, and transmembrane segments using Quick2D are focused on.

Expasy, the Swiss Bioinformatics Resource Portal, as designed by its users

The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss) creates, maintains and disseminates a portfolio of reliable and state-of-the-art bioinformatics services and resources for the storage, analysis and interpretation of biological data. Through Expasy (https://www.expasy.org), the Swiss Bioinformatics Resource Portal, the scientific community worldwide, freely accesses more than 160 SIB resources supporting a wide range of life science and biomedical research areas. In 2020, Expasy was redesigned through a user-centric approach, known as User-Centred Design (UCD), whose aim is to create user interfaces that are easy-to-use, efficient and targeting the intended community. This approach, widely used in other fields such as marketing, e-commerce, and design of mobile applications, is still scarcely explored in bioinformatics. In total, around 50 people were actively involved, including internal stakeholders and end-users. In addition to an optimised interface that meets users' needs and expectations, the new version of Expasy provides an up-to-date and accurate description of high-quality resources based on a standardised ontology, allowing to connect functionally-related resources.

Novel 6-hydroxyquinolinone derivatives: Design, synthesis, antimicrobial evaluation, in silico study and toxicity profiling

Infectious diseases of bacteria and fungi have become a major risk to public health because of antibiotic and antifungal resistance. However, the availability of effective antibacterial and antifungal agents is becoming increasingly limited with growing resistance to existing drugs. In response to that, novel agents are critically needed to overcome such resistance. A new series of 6-hydroxyquinolinone 3, 4, 5a, 5b, 6a and 6b bearing different side chains were synthesized and evaluated as antimicrobials against numbers of bacteria and fungi, using inhibition zone technique. As one of these derivatives, compound 3 was identified as a potent antibacterial and antifungal agent against all tested microorganisms with good minimum inhibitory concentration values comparable to reference drugs. Molecular docking studies were performed on antibacterial and antifungal targets; microbial DNA gyrase B of Staphylococcus aureus (PDB ID: 4URO); N-myristoyltransferase of Candida albicans (PDB ID: 1IYK), respectively, to predict the most probable type of interaction at the active site of the target protein in addition to binding affinities and orientations of docked ligands. Additionally, in silico prediction in terms of detailed physicochemical ADME and toxicity profile relating drug-likeness as well as medicinal chemistry friendliness was performed to all synthesized compounds. The results indicated that a novel 4,6-dihydroxyquinolin-2(1H)-one (3) is likely to be a newly synthesized drug candidate, indicating low toxicity in addition to good in silico absorption. In order to pave the way for more logical production of such compounds, structure-activity and toxicity relationships are also discussed.

The Bgee suite: integrated curated expression atlas and comparative transcriptomics in animals

Bgee is a database to retrieve and compare gene expression patterns in multiple animal species, produced by integrating multiple data types (RNA-Seq, Affymetrix, in situ hybridization, and EST data). It is based exclusively on curated healthy wild-type expression data (e.g., no gene knock-out, no treatment, no disease), to provide a comparable reference of normal gene expression. Curation includes very large datasets such as GTEx (re-annotation of samples as ‘healthy’ or not) as well as many small ones. Data are integrated and made comparable between species thanks to consistent data annotation and processing, and to calls of presence/absence of expression, along with expression scores. As a result, Bgee is capable of detecting the conditions of expression of any single gene, accommodating any data type and species. Bgee provides several tools for analyses, allowing, e.g., automated comparisons of gene expression patterns within and between species, retrieval of the prefered conditions of expression of any gene, or enrichment analyses of conditions with expression of sets of genes. Bgee release 14.1 includes 29 animal species, and is available at https://bgee.org/ and through its Bioconductor R package BgeeDB.

A Proline-Based Tectons and Supramolecular Synthons for Drug Design 2.0: A Case Study of ACEI

Proline is a unique, endogenous amino acid, prevalent in proteins and essential for living organisms. It is appreciated as a tecton for the rational design of new bio-active substances. Herein, we present a short overview of the subject. We analyzed 2366 proline-derived structures deposited in the Cambridge Structure Database, with emphasis on the angiotensin-converting enzyme inhibitors. The latter are the first-line antihypertensive and cardiological drugs. Their side effects prompt a search for improved pharmaceuticals. Characterization of tectons (molecular building blocks) and the resulting supramolecular synthons (patterns of intermolecular interactions) involving proline derivatives, as presented in this study, may be useful for in silico molecular docking and macromolecular modeling studies. The DFT, Hirshfeld surface and energy framework methods gave considerable insight into the nature of close inter-contacts and supramolecular topology. Substituents of proline entity are important for the formation and cooperation of synthons. Tectonic subunits contain proline moieties characterized by diverse ionization states: -N and -COOH(-COO-), -N+ and -COOH(-COO-), -NH and -COOH(-COO-), -NH+ and -COOH(-COO-), and -NH2+ and -COOH(-COO-). Furthermore, pharmacological profiles of ACE inhibitors and their impurities were determined via an in silico approach. The above data were used to develop comprehensive classification, which may be useful in further drug design studies.

The Voltage-Dependent Deactivation of the KvAP Channel Involves the Breakage of Its S4 Helix

Voltage-gated potassium channels (Kv) allow ion permeation upon changes of the membrane electrostatic potential (Vm). Each subunit of these tetrameric channels is composed of six transmembrane helices, of which the anti-parallel helix bundle S1-S4 constitutes the voltage-sensor domain (VSD) and S5-S6 forms the pore domain. Here, using 82 molecular dynamics (MD) simulations involving 266 replicated VSDs, we report novel responses of the archaebacterial potassium channel KvAP to membrane polarization. We show that the S4 α-helix, which is straight in the experimental crystal structure solved under depolarized conditions (Vm ∼ 0), breaks into two segments when the cell membrane is hyperpolarized (Vm << 0), and reversibly forms a single straight helix following depolarization (Vm = 0). The outermost segment of S4 translates along the normal to the membrane, bringing new perspective to previously paradoxical accessibility experiments that were initially thought to imply the displacement of the whole VSD across the membrane. The novel model is applied through steered and unbiased MD simulations to the recently solved whole structure of KvAP. The simulations show that the resting state involves a re-orientation of the S5 α-helix by ∼ 5-6 degrees in respect to the normal of the bilayer, which could result in the constriction and closure of the selectivity filter. Our findings support the idea that the breakage of S4 under (hyper)polarization is a general feature of Kv channels with a non-swapped topology.

A Supramolecular Approach to Structure-Based Design with A Focus on Synthons Hierarchy in Ornithine-Derived Ligands: Review, Synthesis, Experimental and in Silico Studies

The success of innovative drugs depends on an interdisciplinary and holistic approach to their design and development. The supramolecular architecture of living systems is controlled by non-covalent interactions to a very large extent. The latter are prone to extensive cooperation and like a virtuoso play a symphony of life. Thus, the design of effective ligands should be based on thorough knowledge on the interactions at either a molecular or high topological level. In this work, we emphasize the importance of supramolecular structure and ligand-based design keeping the potential of supramolecular H-bonding synthons in focus. In this respect, the relevance of supramolecular chemistry for advanced therapies is appreciated and undisputable. It has developed tools, such as Hirshfeld surface analysis, using a huge data on supramolecular interactions in over one million structures which are deposited in the Cambridge Structure Database (CSD). In particular, molecular interaction surfaces are useful for identification of macromolecular active sites followed by in silico docking experiments. Ornithine-derived compounds are a new, promising class of multi-targeting ligands for innovative therapeutics and cosmeceuticals. In this work, we present the synthesis together with the molecular and supramolecular structure of a novel ornithine derivative, namely N-α,N-δ)-dibenzoyl-(α)-hydroxymethylornithine, 1. It was investigated by modern experimental and in silico methods in detail. The incorporation of an aromatic system into the ornithine core induces stacking interactions, which are vital in biological processes. In particular, rare C=O…π intercontacts have been identified in 1. Supramolecular interactions were analyzed in all structures of ornithine derivatives deposited in the CSD. The influence of substituent was assessed by the Hirshfeld surface analysis. It revealed that the crystal packing is stabilized mainly by H…O, O…H, C…H, Cl (Br, F)…H and O…O interactions. Additionally, π…π, C-H…π and N-O…π interactions were also observed. All relevant H-bond energies were calculated using the Lippincott and Schroeder H-bond model. A library of synthons is provided. In addition, the large synthons (Long-Range Synthon Aufbau Module) were considered. The DFT optimization either in vacuo or in solutio yields very similar molecular species. The major difference with the relevant crystal structure was related to the conformation of terminal benzoyl C15-C20 ring. Furthermore, in silico prediction of the extensive physicochemical ADME profile (absorption, distribution, metabolism and excretion) related to the drug-likeness and medicinal chemistry friendliness revealed that a novel ornithine derivative 1 has the potential to be a new drug candidate. It has shown good in silico absorption and very low toxicity.

CoCoScore: context-aware co-occurrence scoring for text mining applications using distant supervision

MOTIVATION

Information extraction by mining the scientific literature is key to uncovering relations between biomedical entities. Most existing approaches based on natural language processing extract relations from single sentence-level co-mentions, ignoring co-occurrence statistics over the whole corpus. Existing approaches counting entity co-occurrences ignore the textual context of each co-occurrence.

RESULTS

We propose a novel corpus-wide co-occurrence scoring approach to relation extraction that takes the textual context of each co-mention into account. Our method, called CoCoScore, scores the certainty of stating an association for each sentence that co-mentions two entities. CoCoScore is trained using distant supervision based on a gold-standard set of associations between entities of interest. Instead of requiring a manually annotated training corpus, co-mentions are labeled as positives/negatives according to their presence/absence in the gold standard. We show that CoCoScore outperforms previous approaches in identifying human disease-gene and tissue-gene associations as well as in identifying physical and functional protein-protein associations in different species. CoCoScore is a versatile text mining tool to uncover pairwise associations via co-occurrence mining, within and beyond biomedical applications.

AVAILABILITY AND IMPLEMENTATION

CoCoScore is available at: https://github.com/JungeAlexander/cocoscore.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Profile of the In Vitro Anti-Tumor Activity and In Silico ADME Predictions of Novel Benzothiazole Amide-Functionalized Imidazolium Ionic Liquids

A focused array of green imidazolium ionic liquids (ILs) encompassing benzothiazole ring and amide linkage were designed and synthesized using quaternization and metathesis protocols. The synthesized ILs have been fully characterized by usual spectroscopic methods and screened for their anticancer activities against human cancer cell lines originating from breast and colon cancers. Collectively, our biological data demonstrate that the newly synthesized series has variable anticancer activities in the examined cancer types. The synthesized ILs 8, 10 and 21-29 comprising the methyl and methyl sulfonyl benzothiazole ring emerged as the most potent compounds with promising antiproliferative activities relative to their benzothiazole ring counterparts. Furthermore, the mechanism underlying the observed anticancer activity was investigated. The most active compound 22 appears to exert its anticancer effect through apoptosis dependent pathway in breast cancer cells. Interestingly, compound 22 has also shown good in silico absorption (81.75%) along with high gastro-intestinal absorption as per ADME predictions.

Proteomic and Metabolomic Characteristics of Extremophilic Fungi Under Simulated Mars Conditions

Filamentous fungi have been associated with extreme habitats, including nuclear power plant accident sites and the International Space Station (ISS). Due to their immense adaptation and phenotypic plasticity capacities, fungi may thrive in what seems like uninhabitable niches. This study is the first report of fungal survival after exposure of monolayers of conidia to simulated Mars conditions (SMC). Conidia of several Chernobyl nuclear accident-associated and ISS-isolated strains were tested for UV-C and SMC sensitivity, which resulted in strain-dependent survival. Strains surviving exposure to SMC for 30 min, ISSFT-021-30 and IMV 00236-30, were further characterized for proteomic, and metabolomic changes. Differential expression of proteins involved in ribosome biogenesis, translation, and carbohydrate metabolic processes was observed. No significant metabolome alterations were revealed. Lastly, ISSFT-021-30 conidia re-exposed to UV-C exhibited enhanced UV-C resistance when compared to the conidia of unexposed ISSFT-021.

The Promoter Regions of Intellectual Disability-Associated Genes Are Uniquely Enriched in LTR Sequences of the MER41 Primate-Specific Endogenous Retrovirus: An Evolutionary Connection Between Immunity and Cognition

Social behavior and neuronal connectivity in rodents have been shown to be shaped by the prototypical T lymphocyte-derived pro-inflammatory cytokine Interferon-gamma (IFNγ). It has also been demonstrated that STAT1 (Signal Transducer And Activator Of Transcription 1), a transcription factor (TF) crucially involved in the IFNγ pathway, binds consensus sequences that, in humans, are located with a high frequency in the LTRs (Long Terminal Repeats) of the MER41 family of primate-specific HERVs (Human Endogenous Retroviruses). However, the putative role of an IFNγ/STAT1/MER41 pathway in human cognition and/or behavior is still poorly documented. Here, we present evidence that the promoter regions of intellectual disability-associated genes are uniquely enriched in LTR sequences of the MER41 HERVs. This observation is specific to MER41 among more than 130 HERVs examined. Moreover, we have not found such a significant enrichment in the promoter regions of genes that associate with autism spectrum disorder (ASD) or schizophrenia. Interestingly, ID-associated genes exhibit promoter-localized MER41 LTRs that harbor TF binding sites (TFBSs) for not only STAT1 but also other immune TFs such as, in particular, NFKB1 (Nuclear Factor Kappa B Subunit 1) and STAT3 (Signal Transducer And Activator Of Transcription 3). Moreover, IL-6 (Interleukin 6) rather than IFNγ, is identified as the main candidate cytokine regulating such an immune/MER41/cognition pathway. Of note, differences between humans and chimpanzees are observed regarding the insertion sites of MER41 LTRs in the promoter regions of ID-associated genes. Finally, a survey of the human proteome has allowed us to map a protein-protein network which links the identified immune/MER41/cognition pathway to FOXP2 (Forkhead Box P2), a key TF involved in the emergence of human speech. Our work suggests that together with the evolution of immune genes, the stepped self-domestication of MER41 in the genomes of primates could have contributed to cognitive evolution. We further propose that non-inherited forms of ID might result from the untimely or quantitatively inappropriate expression of immune signals, notably IL-6, that putatively regulate cognition-associated genes via promoter-localized MER41 LTRs.

Bioinformatics on a national scale: an example from Switzerland

Switzerland has been a pioneer in the field of bioinformatics since the early 1980s. As time passed, the need for one entity to gather and represent bioinformatics on a national scale was felt and, in 1998, the SIB Swiss Institute of Bioinformatics was created. Hence, 2018 marks the Institute's 20th anniversary. Today, the Institute federates 65 research and service groups across the country-whose activity domains range from genomics, proteomics, medicine and health to structural biology, systems biology, phylogeny and evolution-and a group whose sole task is dedicated to training. The Institute hosts 12 competence centres that provide bioinformatics and biocuration expertise to life scientists across the country. SIB sensed early on that the wealth of data produced by modern technologies in medicine and the growing self-awareness of patients was about to revolutionize the way medical data are considered. In 2012, it created a Clinical Bioinformatics group to address the issue of personalized health, thus working towards a more global approach to patient management, and more targeted and effective therapies. In this respect, SIB has a major role in the Swiss Personalized Health Network to make patient-related data available to research throughout the country. The uniqueness of the Institute's governance structure has also inspired the structure of other European life science organizations, notably ELIXIR.

Evolution-guided evaluation of the inverted terminal repeats of the synthetic transposon Sleeping Beauty

Sleeping Beauty (SB) is a synthetic Tc1/mariner transposon that is widely used for genetic engineering in vertebrates, including humans. Its sequence was derived from a consensus of sequences found in fish species including the Atlantic salmon (Salmo salar). One of the functional components of SB, the transposase enzyme, has been subject to extensive mutagenesis yielding hyperactive protein variants for advanced applications. The second functional component, the transposon inverted terminal repeats (ITRs), has so far not been extensively modified, mainly due to a lack of natural sequence information. Importantly, as genome sequences become available, they can provide a rich source of information for a refined molecular definition of the functional components of these transposons. Here we have mined the Salmo salar genome for a comprehensive set of transposon sequences that were used to build a refined consensus sequence. We synthetically produced the new consensus ITR sequences and used them to build a new transposon, the performance of which has been tested in cell-based transposition assays. The consensus sequence did not support enhanced transposition, suggesting alternative mechanisms responsible for the preferential amplification of these sequence variants in the salmon genome.

TISSUES 2.0: an integrative web resource on mammalian tissue expression

Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene–tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms compared.

Database URL: http://tissues.jensenlab.org/

Genomic data integration systematically biases interactome mapping

Elucidating the complete network of protein-protein interactions, or interactome, is a fundamental goal of the post-genomic era, yet existing interactome maps are far from complete. To increase the throughput and resolution of interactome mapping, methods for protein-protein interaction discovery by co-migration have been introduced. However, accurate identification of interacting protein pairs within the resulting large-scale proteomic datasets is challenging. Consequently, most computational pipelines for co-migration data analysis incorporate external genomic datasets to distinguish interacting from non-interacting protein pairs. The effect of this procedure on interactome mapping is poorly understood. Here, we conduct a rigorous analysis of genomic data integration for interactome recovery across a large number of co-migration datasets, spanning diverse experimental and computational methods. We find that genomic data integration leads to an increase in the functional coherence of the resulting interactome maps, but this comes at the expense of a decrease in power to discover novel interactions. Importantly, putative novel interactions predicted by genomic data integration are no more likely to later be experimentally discovered than those predicted from co-migration data alone. Our results reveal a widespread and unappreciated limitation in a methodology that has been widely used to map the interactome of humans and model organisms.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Bioinformatics-based tools in drug discovery: the cartography from single gene to integrative biological networks

Originally developed for the analysis of biological sequences, bioinformatics has advanced into one of the most widely recognized domains in the scientific community. Despite this technological evolution, there is still an urgent need for nontoxic and efficient drugs. The onus now falls on the 'omics domain to meet this need by implementing bioinformatics techniques that will allow for the introduction of pioneering approaches in the rational drug design process. Here, we categorize an updated list of informatics tools and explore the capabilities of integrative bioinformatics in disease control. We believe that our review will serve as a comprehensive guide toward bioinformatics-oriented disease and drug discovery research.

Epithelial-to-Mesenchymal Transition Antagonizes Response to Targeted Therapies in Lung Cancer by Suppressing BIM

Purpose: Epithelial-to-mesenchymal transition (EMT) confers resistance to a number of targeted therapies and chemotherapies. However, it has been unclear why EMT promotes resistance, thereby impairing progress to overcome it.Experimental Design: We have developed several models of EMT-mediated resistance to EGFR inhibitors (EGFRi) in EGFR-mutant lung cancers to evaluate a novel mechanism of EMT-mediated resistance.Results: We observed that mesenchymal EGFR-mutant lung cancers are resistant to EGFRi-induced apoptosis via insufficient expression of BIM, preventing cell death despite potent suppression of oncogenic signaling following EGFRi treatment. Mechanistically, we observed that the EMT transcription factor ZEB1 inhibits BIM expression by binding directly to the BIM promoter and repressing transcription. Derepression of BIM expression by depletion of ZEB1 or treatment with the BH3 mimetic ABT-263 to enhance "free" cellular BIM levels both led to resensitization of mesenchymal EGFR-mutant cancers to EGFRi. This relationship between EMT and loss of BIM is not restricted to EGFR-mutant lung cancers, as it was also observed in KRAS-mutant lung cancers and large datasets, including different cancer subtypes.Conclusions: Altogether, these data reveal a novel mechanistic link between EMT and resistance to lung cancer targeted therapies. Clin Cancer Res; 24(1); 197-208. ©2017 AACR.

Computational Studies of Snake Venom Toxins

Most snake venom toxins are proteins, and participate to envenomation through a diverse array of bioactivities, such as bleeding, inflammation, and pain, cytotoxic, cardiotoxic or neurotoxic effects. The venom of a single snake species contains hundreds of toxins, and the venoms of the 725 species of venomous snakes represent a large pool of potentially bioactive proteins. Despite considerable discovery efforts, most of the snake venom toxins are still uncharacterized. Modern bioinformatics tools have been recently developed to mine snake venoms, helping focus experimental research on the most potentially interesting toxins. Some computational techniques predict toxin molecular targets, and the binding mode to these targets. This review gives an overview of current knowledge on the ~2200 sequences, and more than 400 three-dimensional structures of snake toxins deposited in public repositories, as well as of molecular modeling studies of the interaction between these toxins and their molecular targets. We also describe how modern bioinformatics have been used to study the snake venom protein phospholipase A2, the small basic myotoxin Crotamine, and the three-finger peptide Mambalgin.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Zika virus NS5 protein potential inhibitors: an enhanced in silico approach in drug discovery

The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico 'per-residue energy decomposition pharmacophore' virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.

Triage by ranking to support the curation of protein interactions

Database URL

http://candy.hesge.ch/nextA5.

CEBS: a comprehensive annotated database of toxicological data

The Chemical Effects in Biological Systems database (CEBS) is a comprehensive and unique toxicology resource that compiles individual and summary animal data from the National Toxicology Program (NTP) testing program and other depositors into a single electronic repository. CEBS has undergone significant updates in recent years and currently contains over 11 000 test articles (exposure agents) and over 8000 studies including all available NTP carcinogenicity, short-term toxicity and genetic toxicity studies. Study data provided to CEBS are manually curated, accessioned and subject to quality assurance review prior to release to ensure high quality. The CEBS database has two main components: data collection and data delivery. To accommodate the breadth of data produced by NTP, the CEBS data collection component is an integrated relational design that allows the flexibility to capture any type of electronic data (to date). The data delivery component of the database comprises a series of dedicated user interface tables containing pre-processed data that support each component of the user interface. The user interface has been updated to include a series of nine Guided Search tools that allow access to NTP summary and conclusion data and larger non-NTP datasets. The CEBS database can be accessed online at http://www.niehs.nih.gov/research/resources/databases/cebs/.

"Big Data" for Breast Cancer: Where to look and what you will find

Accessing the massive amount of breast cancer data that are currently publicly available may seem daunting to the brand new graduate student embarking on his/her first project or even to the seasoned lab leader, who may wish to explore a new avenue of investigation. In this review, we provide an overview of data resources focusing on high-throughput data and on cancer-related data resources. Although not intended as an exhaustive list, the information included in this review will provide a jumping-off point with descriptions of and links to the various data resources of interest. The review is divided into six sections: (1) compendia of data resources; (2) biomolecular repository “Hubs”; (3) a list of cancer-related data resources, which provides information on contents of the resource and whether the resource enables upload and analysis of investigator provided data; (4) a list of seminal publications containing specific breast cancer data, e.g., publications from METBRIC, Sanger, TCGA; (5) a list of journals focused on data science that include cancer-related “Big Data”; and (6) miscellaneous resources.

World data centre for microorganisms: an information infrastructure to explore and utilize preserved microbial strains worldwide

The World Data Centre for Microorganisms (WDCM) was established 50 years ago as the data center of the World Federation for Culture Collections (WFCC)—Microbial Resource Center (MIRCEN). WDCM aims to provide integrated information services using big data technology for microbial resource centers and microbiologists all over the world. Here, we provide an overview of WDCM including all of its integrated services. Culture Collections Information Worldwide (CCINFO) provides metadata information on 708 culture collections from 72 countries and regions. Global Catalogue of Microorganism (GCM) gathers strain catalogue information and provides a data retrieval, analysis, and visualization system of microbial resources. Currently, GCM includes >368 000 strains from 103 culture collections in 43 countries and regions. Analyzer of Bioresource Citation (ABC) is a data mining tool extracting strain related publications, patents, nucleotide sequences and genome information from public data sources to form a knowledge base. Reference Strain Catalogue (RSC) maintains a database of strains listed in International Standards Organization (ISO) and other international or regional standards. RSC allocates a unique identifier to strains recommended for use in diagnosis and quality control, and hence serves as a valuable cross-platform reference. WDCM provides free access to all these services at www.wdcm.org.

neXtA5: accelerating annotation of articles via automated approaches in neXtProt

The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein-protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being implemented into the neXtProt annotation pipeline.Available on: http://babar.unige.ch:8082/neXtA5Database URL: http://babar.unige.ch:8082/neXtA5/fetcher.jsp.

Comparative Proteomic Analysis of Mature and Immature Oocytes of the Swamp Buffalo (Bubalus bubalis)

Maternal protein components change markedly during mammalian oogenesis. Many of these proteins have yet to be characterized and verified. In this study, a proteomics approach was used to evaluate changes in proteins during oogenesis in the Swamp Buffalo (Bubalus bubalis). Proteins from 500 immature oocytes and 500 in vitro matured oocytes were subjected to two-dimensional electrophoresis, and more than 400 spots were detected. Image analysis indicated that 17 proteins were differentially expressed between the two groups. Eight proteins were identified by mass spectrometry. In mature oocytes, three proteins were down-regulated: major vault protein (MVP), N-acetyllactosaminide β-1,6-N-acetylglucosaminyl-transferase (GCNT-2), and gem-associated protein (GEMIN)8, whereas five other proteins, heat shock protein (HSP)60, Ras-responsive element-binding protein 1 (RREB-1), heat shock cognate 71 kDa protein (HSC71), hemoglobin subunit α (HBA), and BMP-2-inducible protein kinase (BMP-2K), were up-regulated. The expression profiles of HSP60 and GEMIN8 were further verified by Western blotting. The changes in HSP60 protein expression demonstrate the increasing need for mitochondrial protein importation to facilitate macromolecular assembly during oocyte maturation. The down-regulation of GEMIN8 production implies that RNA splicing is impaired in mature oocytes.