Discovery of a small molecule RXFP3/4 agonist that increases food intake in rats upon acute central administration.

The relaxin family peptide receptors have been implicated in numerous physiological processes including energy homeostasis, cardiac function, wound healing, and reproductive function. Two family members, RXFP3 and RXFP4, are class A GPCRs with endogenous peptide ligands (relaxin-3 and insulin-like peptide 5 (INSL5), respectively). Polymorphisms in relaxin-3 and RXFP3 have been associated with obesity, diabetes, and hypercholesterolemia. Moreover, central administration of relaxin-3 in rats has been shown to increase food intake, leading to body weight gain. Reported RXFP3 and RXFP4 ligands have been restricted to peptides (both endogenous and synthetic) as well as a low molecular weight positive allosteric modulator requiring a non-endogenous orthosteric ligand. Described here is the discovery of the first potent low molecular weight dual agonists of RXFP3/4. The scaffold identified is competitive with a chimeric relaxin-3/INSL5 peptide for RXFP3 binding, elicits similar downstream signaling as relaxin-3, and increases food intake in rats following acute central administration. This is the first report of small molecule RXFP3/4 agonism.

Dark chemical matter as a promising starting point for drug lead discovery.

High-throughput screening (HTS) is an integral part of early drug discovery. Herein, we focused on those small molecules in a screening collection that have never shown biological activity despite having been exhaustively tested in HTS assays. These compounds are referred to as 'dark chemical matter' (DCM). We quantified DCM, validated it in quality control experiments, described its physicochemical properties and mapped it into chemical space. Through analysis of prospective reporter-gene assay, gene expression and yeast chemogenomics experiments, we evaluated the potential of DCM to show biological activity in future screens. We demonstrated that, despite the apparent lack of activity, occasionally these compounds can result in potent hits with unique activity and clean safety profiles, which makes them valuable starting points for lead optimization efforts. Among the identified DCM hits was a new antifungal chemotype with strong activity against the pathogen Cryptococcus neoformans but little activity at targets relevant to human safety.

PITPs as targets for selectively interfering with phosphoinositide signaling in cells.

Sec14-like phosphatidylinositol transfer proteins (PITPs) integrate diverse territories of intracellular lipid metabolism with stimulated phosphatidylinositol-4-phosphate production and are discriminating portals for interrogating phosphoinositide signaling. Yet, neither Sec14-like PITPs nor PITPs in general have been exploited as targets for chemical inhibition for such purposes. Herein, we validate what is to our knowledge the first small-molecule inhibitors (SMIs) of the yeast PITP Sec14. These SMIs are nitrophenyl(4-(2-methoxyphenyl)piperazin-1-yl)methanones (NPPMs) and are effective inhibitors in vitro and in vivo. We further establish that Sec14 is the sole essential NPPM target in yeast and that NPPMs exhibit exquisite targeting specificities for Sec14 (relative to related Sec14-like PITPs), propose a mechanism for how NPPMs exert their inhibitory effects and demonstrate that NPPMs exhibit exquisite pathway selectivity in inhibiting phosphoinositide signaling in cells. These data deliver proof of concept that PITP-directed SMIs offer new and generally applicable avenues for intervening with phosphoinositide signaling pathways with selectivities superior to those afforded by contemporary lipid kinase-directed strategies.

A large genomic island allows Neisseria meningitidis to utilize propionic acid, with implications for colonization of the human nasopharynx.

Neisseria meningitidis is an important human pathogen that is capable of killing within hours of infection. Its normal habitat is the nasopharynx of adult humans. Here we identify a genomic island (the prp gene cluster) in N. meningitidis that enables this species to utilize propionic acid as a supplementary carbon source during growth, particularly under nutrient poor growth conditions. The prp gene cluster encodes enzymes for a methylcitrate cycle. Novel aspects of the methylcitrate cycle in N. meningitidis include a propionate kinase which was purified and characterized, and a putative propionate transporter. This genomic island is absent from the close relative of N. meningitidis, the commensal Neisseria lactamica, which chiefly colonizes infants not adults. We reason that the possession of the prp genes provides a metabolic advantage to N. meningitidis in the adult oral cavity, which is rich in propionic acid-generating bacteria. Data from classical microbiological and sequence-based microbiome studies provide several lines of supporting evidence that N. meningitidis colonization is correlated with propionic acid generating bacteria, with a strong correlation between prp-containing Neisseria and propionic acid generating bacteria from the genus Porphyromonas, and that this may explain adolescent/adult colonization by N. meningitidis.

Target prediction for an open access set of compounds active against Mycobacterium tuberculosis.

Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), infects an estimated two billion people worldwide and is the leading cause of mortality due to infectious disease. The development of new anti-TB therapeutics is required, because of the emergence of multi-drug resistance strains as well as co-infection with other pathogens, especially HIV. Recently, the pharmaceutical company GlaxoSmithKline published the results of a high-throughput screen (HTS) of their two million compound library for anti-mycobacterial phenotypes. The screen revealed 776 compounds with significant activity against the M. tuberculosis H37Rv strain, including a subset of 177 prioritized compounds with high potency and low in vitro cytotoxicity. The next major challenge is the identification of the target proteins. Here, we use a computational approach that integrates historical bioassay data, chemical properties and structural comparisons of selected compounds to propose their potential targets in M. tuberculosis. We predicted 139 target--compound links, providing a necessary basis for further studies to characterize the mode of action of these compounds. The results from our analysis, including the predicted structural models, are available to the wider scientific community in the open source mode, to encourage further development of novel TB therapeutics.

Dafadine inhibits DAF-9 to promote dauer formation and longevity of Caenorhabditis elegans.

The DAF-9 cytochrome P450 is a key regulator of dauer formation, developmental timing and longevity in the nematode Caenorhabditis elegans. Here we describe the first identified chemical inhibitor of DAF-9 and the first reported small-molecule tool that robustly induces dauer formation in typical culture conditions. This molecule (called dafadine) also inhibits the mammalian ortholog of DAF-9(CYP27A1), suggesting that dafadine can be used to interrogate developmental control and longevity in other animals.

A predictive model for drug bioaccumulation and bioactivity in Caenorhabditis elegans.

The resistance of Caenorhabditis elegans to pharmacological perturbation limits its use as a screening tool for novel small bioactive molecules. One strategy to improve the hit rate of small-molecule screens is to preselect molecules that have an increased likelihood of reaching their target in the worm. To learn which structures evade the worm's defenses, we performed the first survey of the accumulation and metabolism of over 1,000 commercially available drug-like small molecules in the worm. We discovered that fewer than 10% of these molecules accumulate to concentrations greater than 50% of that present in the worm's environment. Using our dataset, we developed a structure-based accumulation model that identifies compounds with an increased likelihood of bioavailability and bioactivity, and we describe structural features that facilitate small-molecule accumulation in the worm. Preselecting molecules that are more likely to reach a target by first applying our model to the tens of millions of commercially available compounds will undoubtedly increase the success of future small-molecule screens with C. elegans.

Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples.

Next-generation sequencing has proven an extremely effective technology for molecular counting applications where the number of sequence reads provides a digital readout for RNA-seq, ChIP-seq, Tn-seq and other applications. The extremely large number of sequence reads that can be obtained per run permits the analysis of increasingly complex samples. For lower complexity samples, however, a point of diminishing returns is reached when the number of counts per sequence results in oversampling with no increase in data quality. A solution to making next-generation sequencing as efficient and affordable as possible involves assaying multiple samples in a single run. Here, we report the successful 96-plexing of complex pools of DNA barcoded yeast mutants and show that such 'Bar-seq' assessment of these samples is comparable with data provided by barcode microarrays, the current benchmark for this application. The cost reduction and increased throughput permitted by highly multiplexed sequencing will greatly expand the scope of chemogenomics assays and, equally importantly, the approach is suitable for other sequence counting applications that could benefit from massive parallelization.

Genome tectonics: linking dynamic genome organization with cellular nutrient.

BACKGROUND: Our daily intake of food provides nutrients for the maintenance of health, growth and development. The field of nutrigenomics aims to link dietary intake/nutrients to changes in epigenetic status and gene expression. SUMMARY: Although the relationship between our diet and our genes in under intense investigation, there is still as significant aspect of our genome that have received little attention with regards to this. In the past 15 years the importance of genome organization has become increasingly evident, with research identifying small scale local changes to large segments of the genome dynamically repositioning within the nucleus in response to/or mediating change in gene expression. The discovery of these dynamic processes and organization maybe as significant as dynamic plate tectonics is to geology, there is little information tying genome organization to specific nutrients or dietary intake. KEY MESSAGES: Here we detail key principles of genome organization and structure, with emphasis on genome folding and organization, and link how these contribute to our future understand of nutrigenomics.

An integrated platform of genomic assays reveals small-molecule bioactivities.

Bioactive compounds are widely used to modulate protein function and can serve as important leads for drug development. Identifying the in vivo targets of these compounds remains a challenge. Using yeast, we integrated three genome-wide gene-dosage assays to measure the effect of small molecules in vivo. A single TAG microarray was used to resolve the fitness of strains derived from pools of (i) homozygous deletion mutants, (ii) heterozygous deletion mutants and (iii) genomic library transformants. We demonstrated, with eight diverse reference compounds, that integration of these three chemogenomic profiles improves the sensitivity and specificity of small-molecule target identification. We further dissected the mechanism of action of two protein phosphatase inhibitors and in the process developed a framework for the rational design of multidrug combinations to sensitize cells with specific genotypes more effectively. Finally, we applied this platform to 188 novel synthetic chemical compounds and identified both potential targets and structure-activity relationships.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

Multiple sequence alignments.

Multiple sequence alignments are very widely used in all areas of DNA and protein sequence analysis. The main methods that are still in use are based on 'progressive alignment' and date from the mid to late 1980s. Recently, some dramatic improvements have been made to the methodology with respect either to speed and capacity to deal with large numbers of sequences or to accuracy. There have also been some practical advances concerning how to combine three-dimensional structural information with primary sequences to give more accurate alignments, when structures are available.

M-Coffee: combining multiple sequence alignment methods with T-Coffee.

We introduce M-Coffee, a meta-method for assembling multiple sequence alignments (MSA) by combining the output of several individual methods into one single MSA. M-Coffee is an extension of T-Coffee and uses consistency to estimate a consensus alignment. We show that the procedure is robust to variations in the choice of constituent methods and reasonably tolerant to duplicate MSAs. We also show that performances can be improved by carefully selecting the constituent methods. M-Coffee outperforms all the individual methods on three major reference datasets: HOMSTRAD, Prefab and Balibase. We also show that on a case-by-case basis, M-Coffee is twice as likely to deliver the best alignment than any individual method. Given a collection of pre-computed MSAs, M-Coffee has similar CPU requirements to the original T-Coffee. M-Coffee is a freeware open-source package available from http://www.tcoffee.org/.

CHEMGENIE: integration of chemogenomics data for applications in chemical biology.

Increasing amounts of biological data are accumulating in the pharmaceutical industry and academic institutions. However, data does not equal actionable information, and guidelines for appropriate data capture, harmonization, integration, mining, and visualization need to be established to fully harness its potential. Here, we describe ongoing efforts at Merck & Co. to structure data in the area of chemogenomics. We are integrating complementary data from both internal and external data sources into one chemogenomics database (Chemical Genetic Interaction Enterprise; CHEMGENIE). Here, we demonstrate how this well-curated database facilitates compound set design, tool compound selection, target deconvolution in phenotypic screening, and predictive model building.

Supervised multivariate analysis of sequence groups to identify specificity determining residues.

BACKGROUND: Proteins that evolve from a common ancestor can change functionality over time, and it is important to be able identify residues that cause this change. In this paper we show how a supervised multivariate statistical method, Between Group Analysis (BGA), can be used to identify these residues from families of proteins with different substrate specifities using multiple sequence alignments. RESULTS: We demonstrate the usefulness of this method on three different test cases. Two of these test cases, the Lactate/Malate dehydrogenase family and Nucleotidyl Cyclases, consist of two functional groups. The other family, Serine Proteases consists of three groups. BGA was used to analyse and visualise these three families using two different encoding schemes for the amino acids. CONCLUSION: This overall combination of methods in this paper is powerful and flexible while being computationally very fast and simple. BGA is especially useful because it can be used to analyse any number of functional classes. In the examples we used in this paper, we have only used 2 or 3 classes for demonstration purposes but any number can be used and visualised.

Discovery of a proteolytic flagellin family in diverse bacterial phyla that assembles enzymatically active flagella.

Bacterial flagella are cell locomotion and occasional adhesion organelles composed primarily of the polymeric protein flagellin, but to date have not been associated with any enzymatic function. Here, we report the bioinformatics-driven discovery of a class of enzymatic flagellins that assemble to form proteolytically active flagella. Originating by a metallopeptidase insertion into the central flagellin hypervariable region, this flagellin family has expanded to at least 74 bacterial species. In the pathogen, Clostridium haemolyticum, metallopeptidase-containing flagellin (which we termed flagellinolysin) is the second most abundant protein in the flagella and is localized to the extracellular flagellar surface. Purified flagellar filaments and recombinant flagellin exhibit proteolytic activity, cleaving nearly 1000 different peptides. With ~ 20,000 flagellin copies per ~ 10-µm flagella this assembles the largest proteolytic complex known. Flagellum-mediated extracellular proteolysis expands our understanding of the functional plasticity of bacterial flagella, revealing this family as enzymatic biopolymers that mediate interactions with diverse peptide substrates.So far no enzymatic activity has been attributed to flagellin, the major component of bacterial flagella. Here the authors use bioinformatic analysis and identify a metallopeptidase insertion in flagellins from 74 bacterial species and show that recombinant flagellin and flagellar filaments have proteolytic activity.

Open Source Drug Discovery: Highly Potent Antimalarial Compounds Derived from the Tres Cantos Arylpyrroles.

The development of new antimalarial compounds remains a pivotal part of the strategy for malaria elimination. Recent large-scale phenotypic screens have provided a wealth of potential starting points for hit-to-lead campaigns. One such public set is explored, employing an open source research mechanism in which all data and ideas were shared in real time, anyone was able to participate, and patents were not sought. One chemical subseries was found to exhibit oral activity but contained a labile ester that could not be replaced without loss of activity, and the original hit exhibited remarkable sensitivity to minor structural change. A second subseries displayed high potency, including activity within gametocyte and liver stage assays, but at the cost of low solubility. As an open source research project, unexplored avenues are clearly identified and may be explored further by the community; new findings may be cumulatively added to the present work.

Application of Titration-Based Screening for the Rapid Pilot Testing of High-Throughput Assays.

Pilot testing of an assay intended for high-throughput screening (HTS) with small compound sets is a necessary but often time-consuming step in the validation of an assay protocol. When the initial testing concentration is less than optimal, this can involve iterative testing at different concentrations to further evaluate the pilot outcome, which can be even more time-consuming. Quantitative HTS (qHTS) enables flexible and rapid collection of assay performance statistics, hits at different concentrations, and concentration-response curves in a single experiment. Here we describe the qHTS process for pilot testing in which eight-point concentration-response curves are produced using an interplate asymmetric dilution protocol in which the first four concentrations are used to represent the range of typical HTS screening concentrations and the last four concentrations are added for robust curve fitting to determine potency/efficacy values. We also describe how these data can be analyzed to predict the frequency of false-positives, false-negatives, hit rates, and confirmation rates for the HTS process as a function of screening concentration. By taking into account the compound pharmacology, this pilot-testing paradigm enables rapid assessment of the assay performance and choosing the optimal concentration for the large-scale HTS in one experiment.

Mapping the cellular response to small molecules using chemogenomic fitness signatures.

Genome-wide characterization of the in vivo cellular response to perturbation is fundamental to understanding how cells survive stress. Identifying the proteins and pathways perturbed by small molecules affects biology and medicine by revealing the mechanisms of drug action. We used a yeast chemogenomics platform that quantifies the requirement for each gene for resistance to a compound in vivo to profile 3250 small molecules in a systematic and unbiased manner. We identified 317 compounds that specifically perturb the function of 121 genes and characterized the mechanism of specific compounds. Global analysis revealed that the cellular response to small molecules is limited and described by a network of 45 major chemogenomic signatures. Our results provide a resource for the discovery of functional interactions among genes, chemicals, and biological processes.

Miniature short hairpin RNA screens to characterize antiproliferative drugs.

The application of new proteomics and genomics technologies support a view in which few drugs act solely by inhibiting a single cellular target. Indeed, drug activity is modulated by complex, often incompletely understood cellular mechanisms. Therefore, efforts to decipher mode of action through genetic perturbation such as RNAi typically yields "hits" that fall into several categories. Of particular interest to the present study, we aimed to characterize secondary activities of drugs on cells. Inhibiting a known target can result in clinically relevant synthetic phenotypes. In one scenario, drug perturbation could, for example, improperly activate a protein that normally inhibits a particular kinase. In other cases, additional, lower affinity targets can be inhibited as in the example of inhibition of c-Kit observed in Bcr-Abl-positive cells treated with Gleevec. Drug transport and metabolism also play an important role in the way any chemicals act within the cells. Finally, RNAi per se can also affect cell fitness by more general off-target effects, e.g., via the modulation of apoptosis or DNA damage repair. Regardless of the root cause of these unwanted effects, understanding the scope of a drug's activity and polypharmacology is essential for better understanding its mechanism(s) of action, and such information can guide development of improved therapies. We describe a rapid, cost-effective approach to characterize primary and secondary effects of small-molecules by using small-scale libraries of virally integrated short hairpin RNAs. We demonstrate this principle using a "minipool" composed of shRNAs that target the genes encoding the reported protein targets of approved drugs. Among the 28 known reported drug-target pairs, we successfully identify 40% of the targets described in the literature and uncover several unanticipated drug-target interactions based on drug-induced synthetic lethality. We provide a detailed protocol for performing such screens and for analyzing the data. This cost-effective approach to mammalian knockdown screens, combined with the increasing maturation of RNAi technology will expand the accessibility of similar approaches in academic settings.