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Introduction: Structural colour patterns and their functions in insect wings are less known. Wing interference patterns (WIPs) are colour patterns apparent when wings are viewed against black backgrounds; the angle of incident light and wing surface structures also influence the resulting wing colour pattern. To date, WIPs are correlated with mate attraction, while the impact of geography and environment on WIPs remains unexplored. We explore WIP variation in Drosophila melanogaster populations collected from three altitudes and also compare WIP variation in sibling species D. melanogaster and D. simulans reared at three different temperatures to understand if local selection pressures could also influence WIPs. Methodology: Wings of D. melanogaster males were collected from three different altitudes, and D. melanogaster and D. simulans males reared at three different temperatures were imaged. Images were analysed for their relative red, green and blue content in the RGB colour space. In representative images, wing thickness was assessed using the Newton colour series. Results: An altitudinal cline in WIPs was observed in the cosmopolitan D. melanogaster collected from the Western Himalayas. Relative RGB values and increase in altitudes were negatively correlated. Thermal responses in WIPs were parallel for both D. melanogaster and D. simulans. Relative RGB values were negatively correlated with rearing temperature. In both species, wing thickness measurements indicated that the wings of flies reared at low temperatures had greater blueness (cyan and magenta) compared to flies reared at moderate to high temperatures; the latter had more green and yellow content. Wing thickness pattern was also consistent for D. melanogaster flies collected from low versus higher altitudes. Discussion: We find WIPs to be a plastic trait in response to temperature. WIP response to thermal variation corroborates with the temperature of the geographic origin in D. melanogaster. The adaptive significance of WIP variation and associated wing thickness remains unclear. Future studies could explore the underlying adaptive significance of structural colour patterning under different environmental conditions. [ABSTRACT FROM AUTHOR]

Abstract: Predictive quantitative structure–toxicity and toxicophore models were developed for a diverse series of hERG K+ channel blockers, acting as anti-arrhythmic agents using QSAR+ module in Cerius2 and HypoGen module in Catalyst software, respectively. The 2D-QSTR analysis has been performed on a dataset of 68 molecules carefully selected from literature for which IC50 values measured on hERG K+ channels expressed in mammalian cells lines using the voltage patch clamp assay technique were reported. Their biological data, expressed as IC50, spanned from 7.0nM to 1.4mM, with 7 orders difference. Several types of descriptors including electrotopological, thermodynamic, ADMET, graph theoretical (topological and information content) were used to derive a quantitative relationship between the channel blockers and its physico-chemical properties. Statistically significant QSTR model was obtained using genetic function approximation methodology, having seven descriptors, with a correlation coefficient (r 2) of 0.837, cross-validated correlation coefficient (q 2) of 0.776 and predictive correlation coefficient () of 0.701, indicating the robustness of the model. Toxicophore model generated using HypoGen module in Catalyst, on these datasets, showed three important features for hERG K+ channel blockers, (i) hydrophobic group (HP), (ii) ring aromatic group (RA) and (iii) hydrogen bond acceptor lipid group (HBAl). The most predictive hypothesis (Hypo 1), consisting of these three features had a best correlation coefficient of 0.820, a low rms deviation of 1.740, and a high cost difference of 113.50, which represents a true correlation and a good predictivity. The hypothesis, Hypo 1 was validated by a test set consisting of 12 molecules and by a cross-validation of 95% confidence level. Accordingly, our 2D-QSTR and toxicophore model has strong predictivity to identify structurally diverse hERG K+ channel blockers with desired biological activity. These models provide a useful framework for understanding binding, and gave structural insight into the specific protein–ligand interactions responsible for affinity, and how one might modify any given structure to mitigate binding. [Copyright &y& Elsevier]

The galactopeptide dendrimer GalAG2 ((β-Gal-OC6H4CO-Lys-Pro-Leu)4(Lys-Phe-Lys-Ile)2Lys-His-Ile-NH2) binds strongly to the Pseudomonas aeruginosa (PA) lectin LecA, and it inhibits PA biofilms, as well as disperses already established ones. By starting with the crystal structure of the terminal tripeptide moiety GalA-KPL in complex with LecA, a computational mutagenesis study was carried out on the galactotripeptide to optimize the peptide-lectin interactions. 25 mutants were experimentally evaluated by a hemagglutination inhibition assay, 17 by isothermal titration calorimetry, and 3 by X-ray crystallography. Two of these tripeptides, GalA-KPY (dissociation constant (K(D))=2.7 μM) and GalA-KRL (K(D)=2.7 μM), are among the most potent monovalent LecA ligands reported to date. Dendrimers based on these tripeptide ligands showed improved PA biofilm inhibition and dispersal compared to those of GalAG2, particularly G2KPY ((β-Gal-OC6H4CO-Lys-Pro-Tyr)4(Lys-Phe-Lys-Ile)2Lys-His-Ile-NH2). The possibility to retain and even improve the biofilm inhibition in several analogues of GalAG2 suggests that it should be possible to fine-tune this dendrimer towards therapeutic use by adjusting the pharmacokinetic parameters in addition to the biofilm inhibition through amino acid substitutions., (Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The galactose specific lectin LecA mediates biofilm formation in the opportunistic pathogen P. aeruginosa . The interaction between LecA and aromatic β-galactoside biofilm inhibitors involves an intermolecular CH-π T-shape interaction between C(ε1)-H of residue His50 in LecA and the aromatic ring of the galactoside aglycone. The generality of this interaction was tested in a diverse family of β-galactosides. LecA binding to aromatic β-galactosides (KD ∼ 8 μM) was consistently stronger than to aliphatic β-galactosides (KD ∼ 36 μM). The CH-π interaction was observed in the X-ray crystal structures of six different LecA complexes, with shorter than the van der Waals distances indicating productive binding. Related XH/cation/π-π interactions involving other residues were identified in complexes of aromatic glycosides with a variety of carbohydrate binding proteins such as concanavalin A. Exploiting such interactions might be generally useful in drug design against these targets.

Aryl hydrazine and hydrazide analogues were synthesized based on p-tolyl hydrazine, isolated as a breakdown product of a secondary metabolite from the mushroom, Agaricus bisporus, and tested to be highly active molecule than 5-fluorouracil in in vitro anticancer studies. The synthesized analogues were tested for anticancer activity using NCI protocol. Anolgues 12 and 15 emerged as molecules with significant in vitro anticancer activity. Molecular docking study revealed the binding orientations of aryl hydrazines and hydrazides analogues in the active sites of thymidylate synthase.

In Silico predictive ADME/Tox screening of compounds is one of the hottest areas in drug discovery. To provide predictions of compound drug-like characteristics early in modern drug-discovery decision making, computational technologies have been widely accepted to develop rapid high throughput in silico ADMET analysis. It is widely perceived that the early screening of chemical entities can significantly reduce the expensive costs associated with late stage failures of drugs due to poor ADME/Tox properties. Drug toxic effects are broadly defined to include toxicity, mutagenicity, carcinogenicity, teratogenicity, neurotoxicity and immunotoxicity. Toxicity prediction techniques and structure-activity relationships relies on the accurate estimation and representation of physico-chemical and toxicological properties. This review highlights some of the freely and commercially available softwares for toxicity predictions. The information content can be utilized as a guide for the scientists involved in the drug discovery arena.

In this study, we have focused on the implication of a multiscreening approach in the evaluation of Pseudomonas aeruginosa deacetylase LpxC inhibitory activity of dual PDE4-TNFalpha inhibitors. A genetic function approximation (GFA) directed quantitative structure-activity relationship (QSAR) model was developed for LpxC inhibition on the basis of reported biological activity (Kline and Andersen, J. Med. Chem. 2002, 45, 3112-3129). Subsequently, reported PDE4-TNFalpha inhibitors (Klienman and Campbell, J. Med. Chem. 1998, 41, 266-270) were screened using the QSAR model. Whereby, the compounds were predicted to have equipotent activity with the most potent compound in reported LpxC inhibitor series. A docking analysis of these compounds carried out on the LpxC homology model corroborated the initial results. The compounds were then validated using surface electronic properties analysis and subjected to an adsorption, distribution, metabolism, excretion, and toxicity filter. Taken together, a multiscreening strategy was used to validate potential leads for LpxC inhibition.