William J. Welsh

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.

Bisphenol A and its analogues activate human pregnane X receptor.

Background: Bisphenol A (BPA) is a base chemical used extensively in many consumer products. BPA and its analogues are present in environmental and human samples. Many endocrine-disrupting chemicals, including BPA, have been shown to activate the pregnane X receptor (PXR), a nuclear receptor that functions as a master regulator of xenobiotic metabolism. However, the detailed mechanism by which these chemicals activate PXR remains unknown. Objective: We investigated the mechanism by which BPA interacts with and activates PXR and examined selected BPA analogues to determine whether they bind to and activate PXR. Methods: Cell-based reporter assays, in silico ligand–PXR docking studies, and site-directed mutagenesis were combined to study the interaction between BPA and PXR. We also investigated the influence of BPA and its analogues on the regulation of PXR target genes in human LS180 cells. Results: We found that BPA and several of its analogues are potent agonists for human PXR (hPXR) but do not affect mouse PXR activity. We identified key residues within hPXR’s ligand-binding pocket that constitute points of interaction with BPA. We also deduced the structural requirements of BPA analogues that activate hPXR. BPA and its analogues can also induce PXR target gene expression in human LS180 cells. Conclusions: The present study advances our understanding of the mechanism by which BPA interacts with and activates human PXR. Activation of PXR by BPA may explain some of the adverse effects of BPA in humans.

Detecting hidden sequence propensity for amyloid fibril formation

The preponderance of evidence implicates protein misfolding in many unrelated human diseases. In all cases, normal correctly folded proteins transform from their proper native structure into an abnormal β‐rich structure known as amyloid fibril. Here we introduce a computational algorithm to detect nonnative (hidden) sequence propensity for amyloid fibril formation. Analyzing sequence–structure relationships in terms of tertiary contact (TC), we find that the hidden β‐strand propensity of a query local sequence can be quantitatively estimated from the secondary structure preferences of template sequences of known secondary structure found in regions of high TC. The present method correctly pinpoints the minimal peptide fragment shown experimentally as the likely local mediator of amyloid fibril formation in β‐amyloid peptide, islet amyloid polypeptide (hIAPP), α‐synuclein, and human acetylcholinesterase (AChE). It also found previously unrecognized β‐strand propensities in the prototypical helical protein myoglobin that has been reported as amyloidogenic. Analysis of 2358 nonhomologous protein domains provides compelling evidence that most proteins contain sequences with significant hidden β‐strand propensity. The present method may find utility in many medically relevant applications, such as the engineering of protein sequences and the discovery of therapeutic agents that specifically target these sequences for the prevention and treatment of amyloid diseases.

New Predictive Models for Blood–Brain Barrier Permeability of Drug-like Molecules

PurposeThe goals of the present study were to apply a generalized regression model and support vector machine (SVM) models with Shape Signatures descriptors, to the domain of blood–brain barrier (BBB) modeling.Materials and MethodsThe Shape Signatures method is a novel computational tool that was used to generate molecular descriptors utilized with the SVM classification technique with various BBB datasets. For comparison purposes we have created a generalized linear regression model with eight MOE descriptors and these same descriptors were also used to create SVM models.ResultsThe generalized regression model was tested on 100 molecules not in the model and resulted in a correlation r2u2009=u20090.65. SVM models with MOE descriptors were superior to regression models, while Shape Signatures SVM models were comparable or better than those with MOE descriptors. The best 2D shape signature models had 10-fold cross validation prediction accuracy between 80–83% and leave-20%-out testing prediction accuracy between 80–82% as well as correctly predicting 84% of BBB+ compounds (nu2009=u200995) in an external database of drugs.ConclusionsOur data indicate that Shape Signatures descriptors can be used with SVM and these models may have utility for predicting blood–brain barrier permeation in drug discovery.

Shape Signatures: New Descriptors for Predicting Cardiotoxicity In Silico

Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for cardiotoxicity. The Shape Signatures method is used to generate molecular descriptors that are then utilized with widely used classification techniques such as k nearest neighbors ( k-NN), support vector machines (SVM), and Kohonen self-organizing maps (SOM). The performances of these approaches were assessed by applying them to a data set of compounds with varying affinity toward the 5-HT(2B) receptor as well as a set of human ether-a-go-go-related gene (hERG) potassium channel inhibitors. Our classification models for 5-HT(2B) represented the first attempt at global computational models for this receptor and exhibited average accuracies in the range of 73-83%. This level of performance is comparable to using commercially available molecular descriptors. The overall accuracy of the hERG Shape Signatures-SVM models was 69-73%, in line with other computational models published to date. Our data indicate that Shape Signatures descriptors can be used with SVM and Kohonen SOM and perform better in classification problems related to the analysis of highly clustered and heterogeneous property spaces. Such models may have utility for predicting the potential for cardiotoxicity in drug discovery mediated by the 5-HT(2B) receptor and hERG.

Computational Discovery of Novel Low Micromolar Human Pregnane X Receptor Antagonists

Very few antagonists have been identified for the human pregnane X receptor (PXR). These molecules may be of use for modulating the effects of therapeutic drugs, which are potent agonists for this receptor (e.g., some anticancer compounds and macrolide antibiotics), with subsequent effects on transcriptional regulation of xenobiotic metabolism and transporter genes. A recent novel pharmacophore for PXR antagonists was developed using three azoles and consisted of two hydrogen bond acceptor regions and two hydrophobic features. This pharmacophore also suggested an overall small binding site that was identified on the outer surface of the receptor at the AF-2 site and validated by docking studies. Using computational approaches to search libraries of known drugs or commercially available molecules is preferred over random screening. We have now described several new smaller antagonists of PXR discovered with the antagonist pharmacophore with in vitro activity in the low micromolar range [S-p-tolyl 3′,5-dimethyl-3,5′-biisoxazole-4′-carbothioate (SPB03255) (IC50, 6.3 μM) and 4-(3-chlorophenyl)-5-(2,4-dichlorobenzylthio)-4H-1,2,4-triazol-3-ol (SPB00574) (IC50, 24.8 μM)]. We have also used our computational pharmacophore and docking tools to suggest that most of the known PXR antagonists, such as coumestrol and sulforaphane, could also interact on the outer surface of PXR at the AF-2 domain. The involvement of this domain was also suggested by further site-directed mutagenesis work. We have additionally described an FDA approved prodrug, leflunomide (IC50, 6.8 μM), that seems to be a PXR antagonist in vitro. These observations are important for predicting whether further molecules may interact with PXR as antagonists in vivo with potential therapeutic applications.

Ligand specificity and evolution of liver X receptors

Liver X receptors (LXRs) are key regulators of lipid and cholesterol metabolism in mammals. Little is known, however, about the function and evolution of LXRs in non-mammalian species. The present study reports the cloning of LXRs from African clawed frog (Xenopus laevis), Western clawed frog (Xenopus tropicalis), and zebrafish (Danio rerio), and their functional characterization and comparison with human and mouse LXRs. Additionally, an ortholog of LXR in the chordate invertebrate Ciona intestinalis was cloned and functionally characterized. Ligand specificities of the frog and zebrafish LXRs were very similar to LXRalpha and LXRbeta from human and mouse. All vertebrate LXRs studied were activated robustly by the synthetic ligands T-0901317 and GW3965 and by a variety of oxysterols. In contrast, Ciona LXR was not activated by T-0901317 or GW3965 but was activated by a limited number of oxysterols, as well as some androstane and pregnane steroids. Pharmacophore analysis, homology modeling, and docking studies of Ciona LXR predict a receptor with a more restricted ligand-binding pocket and less intrinsic disorder in the ligand-binding domain compared to vertebrate LXRs. The results suggest that LXRs have a long evolutionary history, with vertebrate LXRs diverging from invertebrate LXRs in ligand specificity.

Evolving carbapenemases: can medicinal chemists advance one step ahead of the coming storm?

Carbapenems can be an effective treatment of infections with multidrug-resistant Gram-negative bacteria such as Pseudomonas aeruginosa,1 Acinetobacter spp.,2 Klebsiella pneumoniae,3 and other Enterobacteriaceae.4 They are semi-synthetic or synthetic β-lactam compounds that are distinguished from other β-lactam compounds such as penicillins and cephalosporins by the absence of a sulfur atom in the bicyclic core and a different stereochemistry at Cα of the β-lactam ring (in penicillins and carbapenems, this atom is usually referred to as C6; in cephalosporins as C7) (Figure 1). The most popular carbapenem antibiotics are imipenem5, 6 (Merck, 1985), meropenem7, 8 (Sumitomo Pharmaceuticals and AstraZeneca, 1996), ertapenem9, 10 (Merck, 2005), and doripenem11, 12 (Shionogi Co. and Johnson & Johnson, 2005) (Figure 2). All of these broad-spectrum drugs are used intravenously. Carbapenems are considered to be drugs of last resort due to the fact that they are not inactivated by and effectively inhibit many β-lactamases (most Ambler class A and C β-lactamases13), while these enzymes efficiently hydrolyze penicillins and cephalosporins. β-Lactamases hydrolyze the β-lactam ring of β-lactam antibiotics blocking peptidyltransferase (also referred to as penicillin binding protein or PBP) activity that is critical for the peptidoglycan biosynthesis of the bacterial cell wall.14 β-Lactam antibiotics inhibit peptidyltransferase by forming a stable acyl-enzyme intermediate after an active-site serine of pepdityltransferase cleaves the β-lactam ring through a nucleophilic attack.15 Similar to peptidyltransferase, most β-lactamases contain an active site serine, which exerts a nucleophilic attack on and cleaves the β-lactam ring, resulting in turnover by the enzyme. These enzymes are referred to as serine β-lactamases (SBLs) and, based on sequence and structural homology, have been grouped into classes A, C, and D by Ambler.13 CTX-M β-lactamases are a group of class A SBLs expressed by Enterobacteriaceae that confer resistance toward the third-generation cephalosporin cefotaxime (Figure 3).16 As a consequence, carbapenems are frequently used to treat infections with Enterobacteriaceae expressing these enzymes. The increased use of carbapenems drives the emergence of carbapenem resistance mechanisms. n n n nFigure 1 n nChemical structures of the bicyclic cores of different classes of β-lactam antibiotics. The penem core is found in penicillins and consists of a β-lactam ring fused with a tetrahydrodrothiazole ring. The cephem core is found in cephalosporins ... n n n n n nFigure 2 n nChemical structures of four commonly prescribed carbapenems: imipenem ((5R,6S)-3-[2-(aminomethylideneamino)ethylsulfanyl]-6-(1-hydroxyethyl)-7-oxo-1-azabicyclo[3.2.0]hept-2-ene-2-carboxylic acid), meropenem (3-[5-(dimethylcarbamoyl)pyrrolidin-2-yl] sulfanyl-6- ... n n n n n nFigure 3 n nChemical structures of selected non-carbapenem β-lactam antibiotics in clinical use: oxacillin ((2S,5R,6R)-3,3-dimethyl-6-[(5-methyl-3-phenyl-1,2-oxazole-4-carbonyl)amino]-7-oxo-4-thia-1-azabicyclo[3.2.0]heptane-2-carboxylic acid), a penicillin; ... n n n nAn increasing number of recent reports indicate that some β-lactamases can efficiently hydrolyze carbapenems. This alarming situation is made worse by the lack of new antibiotics at or near clinic that are active against resistant Gram-negative organisms, particularly nonfermenters such as Pseudomonas aeruginosa and Acinetobacter baumannii. Among SBLs, the most notable carbapenemases are variants of the OXA group (class D) and Klebsiella pneumoniae carbapenemases (KPCs, class A). Metallo-β-lactamases (MBLs), a separate class of enzymes (Ambler class B13), employ a water/hydroxide ion nucleophile activated by coordination to one or two Zn(II) ions and recognize a broad spectrum of β-lactams, including carbapenems. This perspective focuses on the MBLs of the IMP type (IMPs efficiently hydrolyze imipenem) and the VIM type (VIM represents Verona integron-borne metallo-β-lactamase), since these enzymes seem to be the clinically most important MBLs.17 n nWe will (1) give a summary of these four important groups of carbapenemases, OXA, KPC, IMP, and VIM, including their epidemiology, structure, mechanism, and substrate specificity, (2) summarize approaches that have been undertaken to develop MBL inhibitors to reverse antibiotic resistance (potent SBL inhibitors such as clavulanic acid18 are already in clinical use), and (3) propose a novel approach to efficiently screen for such drugs using the Shape Signatures algorithm.

Hybrid Scoring and Classification Approaches to Predict Human Pregnane X Receptor Activators

PurposeThe human pregnane X receptor (PXR) is a transcriptional regulator of many genes involved in xenobiotic metabolism and excretion. Reliable prediction of high affinity binders with this receptor would be valuable for pharmaceutical drug discovery to predict potential toxicological responsesMaterials and MethodsComputational models were developed and validated for a dataset consisting of human PXR (PXR) activators and non-activators. We used support vector machine (SVM) algorithms with molecular descriptors derived from two sources, Shape Signatures and the Molecular Operating Environment (MOE) application software. We also employed the molecular docking program GOLD in which the GoldScore method was supplemented with other scoring functions to improve docking results.ResultsThe overall test set prediction accuracy for PXR activators with SVM was 72% to 81%. This indicates that molecular shape descriptors are useful in classification of compounds binding to this receptor. The best docking prediction accuracy (61%) was obtained using 1D Shape Signature descriptors as a weighting factor to the GoldScore. By pooling the available human PXR data sets we revealed those molecular features that are associated with human PXR activators.ConclusionsThese combined computational approaches using molecular shape information may assist scientists to more confidently identify PXR activators.

Structure-based Design of Novel Small-Molecule Inhibitors of Plasmodium falciparum

Malaria is endemic in most developing countries, with nearly 500 million cases estimated to occur each year. The need to design a new generation of antimalarial drugs that can combat the most drug-resistant forms of the malarial parasite is well recognized. In this study, we wanted to develop inhibitors of key proteins that form the invasion machinery of the malarial parasite. A critical feature of host-cell invasion by apicomplexan parasites is the interaction between the carboxy terminal tail of myosin A (MyoA) and the myosin tail interacting protein (MTIP). Using the cocrystal structure of the Plasmodium knowlesi MTIP and the MyoA tail peptide as input to the hybrid structure-based virtual screening approach, we identified a series of small molecules as having the potential to inhibit MTIP-MyoA interactions. Of the initial 15 compounds tested, a pyrazole-urea compound inhibited P. falciparum growth with an EC(50) value of 145 nM. We screened an additional 51 compounds belonging to the same chemical class and identified 8 compounds with EC(50) values less than 400 nM. Interestingly, the compounds appeared to act at several stages of the parasites life cycle to block growth and development. The pyrazole-urea compounds identified in this study could be effective antimalarial agents because they competitively inhibit a key protein-protein interaction between MTIP and MyoA responsible for the gliding motility and the invasive features of the malarial parasite.