Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development

© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, WeinheimThousands of (Quantitative) Structure-Activity Relationships (Q)SAR models have been described in peer-reviewed publications; however, this way of sharing seldom makes models available for the use by the research community outside of the developer's laboratory. Conversely, on-line models allow broad dissemination and application representing the most effective way of sharing the scientific knowledge. Approaches for sharing and providing on-line access to models range from web services created by individual users and laboratories to integrated modeling environments and model repositories. This emerging transition from the descriptive and informative, but “static”, and for the most part, non-executable print format to interactive, transparent and functional delivery of “living” models is expected to have a transformative effect on modern experimental research in areas of scientific and regulatory use of (Q)SAR models

In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids.

Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs) represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery

QSAR modeling and chemical space analysis of antimalarial compounds

© 2017, Springer International Publishing Switzerland.Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones

Let’s not forget tautomers

A compound exhibits tautomerism if it can be represented by two structures that are related by an intramolecular movement of hydrogen from one atom to another. The different tautomers of a molecule usually have different molecular fingerprints, hydrophobicities and pKa’s as well as different 3D shape and electrostatic properties; additionally, proteins frequently preferentially bind a tautomer that is present in low abundance in water. As a result, the proper treatment of molecules that can tautomerize, ~25% of a database, is a challenge for every aspect of computer-aided molecular design. Library design that focuses on molecular similarity or diversity might inadvertently include similar molecules that happen to be encoded as different tautomers. Physical property measurements might not establish the properties of individual tautomers with the result that algorithms based on these measurements may be less accurate for molecules that can tautomerize—this problem influences the accuracy of filtering for library design and also traditional QSAR. Any 2D or 3D QSAR analysis must involve the decision of if or how to adjust the observed Ki or IC50 for the tautomerization equilibria. QSARs and recursive partitioning methods also involve the decision as to which tautomer(s) to use to calculate the molecular descriptors. Docking virtual screening must involve the decision as to which tautomers to include in the docking and how to account for tautomerization in the scoring. All of these decisions are more difficult because there is no extensive database of measured tautomeric ratios in both water and non-aqueous solvents and there is no consensus as to the best computational method to calculate tautomeric ratios in different environments

Detection of magnetic dipole lines of Fe XII in the ultraviolet spectrum of the dwarf star Epsilon Eri

We report observations of the dwarf star Epsilon Eri (K2 V) made with the Space Telescope Imaging Spectrograph (STIS) on the Hubble Space Telescope (HST). The high sensitivity of the STIS instrument has allowed us to detect the magnetic dipole transitions of Fe XII at 1242.00A and 1349.38A for the first time in a star other than the Sun. The width of the stronger line at 1242.00A has also been measured; such measurements are not possible for the permitted lines of Fe XII in the extreme ultraviolet. To within the accurcy of the measurements, the N V and the Fe XII lines occur at their rest wavelengths. Electron densities and line widths have been measured from other transition region lines. Together, these can be used to investigate the non-thermal energy flux in the lower and upper transition region, which is useful in constraining possible heating processes. The Fe XII lines are also present in archival STIS spectra of other G/K-type dwarfs.Comment: 12 pages, 4 figures, submitted to MNRAS letters (11 Jan 2001

Natural Variation in Arabidopsis Cvi-0 Accession Reveals an Important Role of MPK12 in Guard Cell CO2 Signaling

Plant gas exchange is regulated by guard cells that form stomatal pores. Stomatal adjustments are crucial for plant survival; they regulate uptake of CO2 for photosynthesis, loss of water, and entrance of air pollutants such as ozone. We mapped ozone hypersensitivity, more open stomata, and stomatal CO2-insensitivity phenotypes of the Arabidopsis thaliana accession Cvi-0 to a single amino acid substitution in MITOGEN-ACTIVATED PROTEIN (MAP) KINASE 12 (MPK12). In parallel, we showed that stomatal CO2-insensitivity phenotypes of a mutant cis (CO2-insensitive) were caused by a deletion of MPK12. Lack of MPK12 impaired bicarbonate-induced activation of S-type anion channels. We demonstrated that MPK12 interacted with the protein kinase HIGH LEAF TEMPERATURE 1 (HT1)-a central node in guard cell CO2 signaling-and that MPK12 functions as an inhibitor of HT1. These data provide a new function for plant MPKs as protein kinase inhibitors and suggest a mechanism through which guard cell CO2 signaling controls plant water management.</p

Bioactive Compounds of Rambutan (Nephelium lappaceum L.)

Rambutan, a widely popular tropical fruit encompasses rich amount of bioactive compounds. All parts of this plant (leaves, bark, root, fruits, fruit skin, pulp and seeds) finds traditional usage, and are linked with high therapeutic values. Rambutan fruits parts like that of peel, pulp and seeds have been scientifically investigated in-depth and is reported to encompass high amounts of bioactive compounds (such as polyphenol, flavonoid, alkaloid, essential mineral, dietary fiber). These compounds contribute towards antioxidant, antimicrobial, anticancer, antidiabetic and anti-obesity activities. However, literature pertaining towards potential industrial applications (food, cosmetics, pharmaceutical) of rambutan fruits are limited. In the present chapter, it is intended to document some of the interesting research themes published on rambutan fruits, and identify the existing gaps to open up arena for future research work.This chapter theme is based on our ongoing project—VALORTECH, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 810630

The Transcriptional Response in Human Umbilical Vein Endothelial Cells Exposed to Insulin: A Dynamic Gene Expression Approach

BACKGROUND: In diabetes chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation through the activation of the MAP kinases, which in turn regulate cellular proliferation. However, it is not known whether insulin itself could increase the transcription of specific genes for cellular proliferation in the endothelium. Hence, the characterization of transcriptional modifications in endothelium is an important step for a better understanding of the mechanism of insulin action and the relationship between endothelial cell dysfunction and insulin resistance. METHODOLOGY AND PRINCIPAL FINDINGS: The transcriptional response of endothelial cells in the 440 minutes following insulin stimulation was monitored using microarrays and compared to a control condition. About 1700 genes were selected as differentially expressed based on their treated minus control profile, thus allowing the detection of even small but systematic changes in gene expression. Genes were clustered in 7 groups according to their time expression profile and classified into 15 functional categories that can support the biological effects of insulin, based on Gene Ontology enrichment analysis. In terms of endothelial function, the most prominent processes affected were NADH dehydrogenase activity, N-terminal myristoylation domain binding, nitric-oxide synthase regulator activity and growth factor binding. Pathway-based enrichment analysis revealed "Electron Transport Chain" significantly enriched. Results were validated on genes belonging to "Electron Transport Chain" pathway, using quantitative RT-PCR. CONCLUSIONS: As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment. Since chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation, some of the genes identified in the present work are potential novel candidates in diabetes complications related to endothelial dysfunction