CRTC1/MAML2 gain-of-function interactions with MYC create a gene signature predictive of cancers with CREB-MYC involvement.

Chimeric oncoproteins created by chromosomal translocations are among the most common genetic mutations associated with tumorigenesis. Malignant mucoepidermoid salivary gland tumors, as well as a growing number of solid epithelial-derived tumors, can arise from a recurrent t (11, 19)(q21;p13.1) translocation that generates an unusual chimeric cAMP response element binding protein (CREB)-regulated transcriptional coactivator 1 (CRTC1)/mastermind-like 2 (MAML2) (C1/M2) oncoprotein comprised of two transcriptional coactivators, the CRTC1 and the NOTCH/RBPJ coactivator MAML2. Accordingly, the C1/M2 oncoprotein induces aberrant expression of CREB and NOTCH target genes. Surprisingly, here we report a gain-of-function activity of the C1/M2 oncoprotein that directs its interactions with myelocytomatosis oncogene (MYC) proteins and the activation of MYC transcription targets, including those involved in cell growth and metabolism, survival, and tumorigenesis. These results were validated in human mucoepidermoid tumor cells that harbor the t (11, 19)(q21;p13.1) translocation and express the C1/M2 oncoprotein. Notably, the C1/M2-MYC interaction is necessary for C1/M2-driven cell transformation, and the C1/M2 transcriptional signature predicts other human malignancies having combined involvement of MYC and CREB. These findings suggest that such gain-of-function properties may also be manifest in other oncoprotein fusions found in human cancer and that agents targeting the C1/M2-MYC interface represent an attractive strategy for the development of effective and safe anticancer therapeutics in tumors harboring the t (11, 19) translocation.

PubChem promiscuity: a web resource for gathering compound promiscuity data from PubChem.

SUMMARY: Promiscuity counts allow for a better understanding of a compound's assay activity profile and drug potential. Although PubChem contains a vast amount of compound and assay data, it currently does not have a convenient or efficient method to obtain in-depth promiscuity counts for compounds. PubChem promiscuity fills this gap. It is a Java servlet that uses NCBI Entrez (eUtils) web services to interact with PubChem and provide promiscuity counts in a variety of categories along with compound descriptors, including PAINS-based functional group detection. AVAILABILITY: http://chemutils.florida.scripps.edu/pcpromiscuity CONTACT: southern@scripps.edu

A Java API for working with PubChem datasets.

UNLABELLED: PubChem is a public repository of chemical structures and associated biological activities. The PubChem BioAssay database contains assay descriptions, conditions and readouts and biological screening results that have been submitted by the biomedical research community. The PubChem web site and Power User Gateway (PUG) web service allow users to interact with the data and raw files are available via FTP. These resources are helpful to many but there can also be great benefit by using a software API to manipulate the data. Here, we describe a Java API with entity objects mapped to the PubChem Schema and with wrapper functions for calling the NCBI eUtilities and PubChem PUG web services. PubChem BioAssays and associated chemical compounds can then be queried and manipulated in a local relational database. Features include chemical structure searching and generation and display of curve fits from stored dose-response experiments, something that is not yet available within PubChem itself. The aim is to provide researchers with a fast, consistent, queryable local resource from which to manipulate PubChem BioAssays in a database agnostic manner. It is not intended as an end user tool but to provide a platform for further automation and tools development. AVAILABILITY: http://code.google.com/p/pubchemdb.

A Massively Parallel Selection of Small Molecule-RNA Motif Binding Partners Informs Design of an Antiviral from Sequence.

Many RNAs cause disease; however, RNA is rarely exploited as a small-molecule drug target. Our programmatic focus is to define privileged RNA motif small-molecule interactions to enable the rational design of compounds that modulate RNA biology starting from only sequence. We completed a massive, library-versus-library screen that probed over 50 million binding events between RNA motifs and small molecules. The resulting data provide a rich encyclopedia of small-molecule RNA recognition patterns, defining chemotypes and RNA motifs that confer selective, avid binding. The resulting interaction maps were mined against the entire viral genome of hepatitis C virus (HCV). A small molecule was identified that avidly bound RNA motifs present in the HCV 30 UTR and inhibited viral replication while having no effect on host cells. Collectively, this study represents the first whole-genome pattern recognition between small molecules and RNA folds.

A two-stage differential hydrogen deuterium exchange method for the rapid characterization of protein/ligand interactions.

The peroxisome proliferator-activated receptor is a member of the nuclear receptor superfamily of transcriptional regulators. Regulation of the nuclear receptors occurs through changes to the structure and dynamics of the ligand-binding domain. Therefore, the need has arisen for a rapid method capable of detecting changes in the dynamics of nuclear receptors following ligand binding. We recently described how solution-phase amide hydrogen/deuterium exchange (HDX) provides a biophysical technique for probing changes in protein dynamics induced by ligand interaction. Building from this platform, we have optimized the robustness of the differential HDX experiment by minimizing systematic errors, and have increased the efficiency of the chromatographic separation through the use of high-pressure liquid chromatography. Using knowledge gained previously from comprehensive HDX experiments of PPARgamma, a modest throughput method to probe changes in the dynamics of key regions of the receptor was developed. A collection of ten synthetic and endogenous PPARgamma ligands were characterized with this new method requiring approximately 24 h of analysis. This is a dramatic improvement over the 10 d of analysis that would have been required with our previous approach for comprehensive differential HDX analysis. In addition to demonstrating the utility of this approach, the study presented here is the first to measure changes to the dynamics of PPARgamma upon the binding of putative endogenous ligands.

Hydrogen/deuterium-exchange (H/D-Ex) of PPARgamma LBD in the presence of various modulators.

A nuclear receptor, peroxisome proliferator-activated receptor gamma (PPARgamma), is a ligand-dependent transcription factor involved in glucose homeostasis and adipocyte differentiation. PPARgamma is the molecular target of various natural and synthetic molecules, including anti-diabetic agents such as rosiglitazone. Amide hydrogen/deuterium-exchange (H/D-Ex), coupled with proteolysis and mass spectrometry, was applied to study the dynamics of the PPARgamma ligand binding domain (LBD) with or without molecules that modulate PPARgamma activity. The H/D-Ex patterns of ligand-free PPARgamma LBD show that the ligand binding pocket of LBD is significantly more dynamic than the rest of the LBD. Presumably, the binding pocket is intrinsically disordered in order to accommodate different ligands. The presence of two full agonists (rosiglitazone and GW1929), a partial agonist (nTZDpa), and a covalent antagonist (GW9662), changed the dynamics/conformation of PPARgamma LBD and slowed the H/D exchange rate in various regions of the protein. The full agonists slowed the H/D exchange more globally and to a greater extent than the partial agonist or the antagonist, indicating that the full agonist stabilizes the PPARgamma LBD more than the partial agonist or the antagonist. One interesting observation is that the two full agonists significantly stabilized helix 12 while the partial agonist and the antagonist did not perturb the H/D exchange of this region. The results showed that the change in protein dynamics induced by ligand binding may be an important factor for the activation of genes and that H/D-Ex is a useful method for analyzing the biological activity of drug leads.

Studying a Drug-like, RNA-Focused Small Molecule Library Identifies Compounds That Inhibit RNA Toxicity in Myotonic Dystrophy.

There are many RNA targets in the transcriptome to which small molecule chemical probes and lead therapeutics are desired. However, identifying compounds that bind and modulate RNA function in cellulo is difficult. Although rational design approaches have been developed, they are still in their infancies and leave many RNAs "undruggable". In an effort to develop a small molecule library that is biased for binding RNA, we computationally identified "drug-like" compounds from screening collections that have favorable properties for binding RNA and for suitability as lead drugs. As proof-of-concept, this collection was screened for binding to and modulating the cellular dysfunction of the expanded repeating RNA (r(CUG)(exp)) that causes myotonic dystrophy type 1. Hit compounds bind the target in cellulo, as determined by the target identification approach Competitive Chemical Cross-Linking and Isolation by Pull-down (C-ChemCLIP), and selectively improve several disease-associated defects. The best compounds identified from our 320-member library are more potent in cellulo than compounds identified by high-throughput screening (HTS) campaigns against this RNA. Furthermore, the compound collection has a higher hit rate (9% compared to 0.01-3%), and the bioactive compounds identified are not charged; thus, RNA can be "drugged" with compounds that have favorable pharmacological properties. Finally, this RNA-focused small molecule library may serve as a useful starting point to identify lead "drug-like" chemical probes that affect the biological (dys)function of other RNA targets by direct target engagement.

Rapid analysis of protein structure and dynamics by hydrogen/deuterium exchange mass spectrometry.

An automated approach for the rapid analysis of protein structure has been developed and used to study acid-induced conformational changes in human growth hormone. The labeling approach involves hydrogen/deuterium exchange (H/D-Ex) of protein backbone amide hydrogens with rapid and sensitive detection by mass spectrometry (MS). Briefly, the protein is incubated for defined intervals in a deuterated environment. After rapid quenching of the exchange reaction, the partially deuterated protein is enzymatically digested and the resulting peptide fragments are analyzed by liquid chromatography mass spectrometry (LC-MS). The deuterium buildup curve measured for each fragment yields an average amide exchange rate that reflects the environment of the peptide in the intact protein. Additional analyses allow mapping of the free energy of folding on localized segments along the protein sequence affording unique dynamic and structural information. While amide H/D-Ex coupled with MS is recognized as a powerful technique for studying protein structure and protein-ligand interactions, it has remained a labor-intensive task. The improvements in the amide H/D-Ex methodology described here include solid phase proteolysis, automated liquid handling and sample preparation, and integrated data reduction software that together improve sequence coverage and resolution, while achieving a sample throughput nearly 10-fold higher than the commonly used manual methods.

Assessing interactions between Ghsr and Mc3r reveals a role for AgRP in the expression of food anticipatory activity in male mice.

The stomach hormone ghrelin and hypothalamic melanocortin neurons belong to a gut-brain circuit controlling appetite and metabolic homeostasis. Mice lacking melanocortin-3 receptor (Mc3rKO) or growth hormone secretagogue receptor (GhsrKO) genes exhibit attenuated food anticipatory activity (FAA), a rise in locomotor activity anticipating mealtime, suggesting common circuitry regulating anticipatory responses to nutrient loading. To investigate the interaction between Ghsrs and Mc3rs, we compared food anticipatory responses in GhsrKO, Mc3rKO, and double Ghsr;Mc3r knockout (DKO) mice subjected to a hypocaloric restricted feeding (RF) protocol in constant dark or 12-hour light, 12-hour dark settings. DKO are viable, exhibiting no overt behavioral or metabolic phenotypes in ad libitum or fasting conditions. FAA was initially attenuated in all mutant strains in constant darkness. However, GhsrKO eventually exhibited a robust food anticipatory response, suggesting compensation. Mc3rKO and DKO did not compensate, indicating a continued requirement for Mc3rs in maintaining the expression of FAA in situations of RF. Abnormal regulation of hypothalamic agouti-related peptide/neuropeptide Y (AgRP/Npy) neurons previously observed during fasting may contribute to attenuated FAA in Mc3rKO. AgRP and Npy expression measured 1 hour before food presentation correlated positively with FAA. Absence of Mc3rs (but not Ghsrs) was associated with lower AgRP/Npy expression, suggesting attenuated responses to signals of negative energy balance. These observations support the importance of Mc3rs as modulators of anticipatory responses to feeding, with mice able to compensate for loss of Ghsrs. The behavioral deficits of Mc3rKO displayed during RF may be partially explained by reduced hunger sensations owing to abnormal regulation of orexigenic AgRP/Npy neurons.

An Overview of the Challenges in Designing, Integrating, and Delivering BARD: A Public Chemical-Biology Resource and Query Portal for Multiple Organizations, Locations, and Disciplines.

Recent industry-academic partnerships involve collaboration among disciplines, locations, and organizations using publicly funded "open-access" and proprietary commercial data sources. These require the effective integration of chemical and biological information from diverse data sources, which presents key informatics, personnel, and organizational challenges. The BioAssay Research Database (BARD) was conceived to address these challenges and serve as a community-wide resource and intuitive web portal for public-sector chemical-biology data. Its initial focus is to enable scientists to more effectively use the National Institutes of Health Roadmap Molecular Libraries Program (MLP) data generated from the 3-year pilot and 6-year production phases of the Molecular Libraries Probe Production Centers Network (MLPCN), which is currently in its final year. BARD evolves the current data standards through structured assay and result annotations that leverage BioAssay Ontology and other industry-standard ontologies, and a core hierarchy of assay definition terms and data standards defined specifically for small-molecule assay data. We initially focused on migrating the highest-value MLP data into BARD and bringing it up to this new standard. We review the technical and organizational challenges overcome by the interdisciplinary BARD team, veterans of public- and private-sector data-integration projects, who are collaborating to describe (functional specifications), design (technical specifications), and implement this next-generation software solution.

Improved crystallographic structures using extensive combinatorial refinement.

Identifying errors and alternate conformers and modeling multiple main-chain conformers in poorly ordered regions are overarching problems in crystallographic structure determination that have limited automation efforts and structure quality. Here, we show that implementation of a full factorial designed set of standard refinement approaches, termed ExCoR (Extensive Combinatorial Refinement), significantly improves structural models compared to the traditional linear tree approach, in which individual algorithms are tested linearly and are only incorporated if the model improves. ExCoR markedly improved maps and models and reveals building errors and alternate conformations that were masked by traditional refinement approaches. Surprisingly, an individual algorithm that renders a model worse in isolation could still be necessary to produce the best overall model, suggesting that model distortion allows escape from local minima of optimization target function, here shown to be a hallmark limitation of the traditional approach. ExCoR thus provides a simple approach to improving structure determination.