Dac-Trung Nguyen

The NCGC Pharmaceutical Collection: A comprehensive resource of clinically approved drugs enabling repurposing and chemical genomics

Resources from the National Institutes of Health Chemical Genomics Center include a database and a physical collection of approved drugs. Small-molecule compounds approved for use as drugs may be “repurposed” for new indications and studied to determine the mechanisms of their beneficial and adverse effects. A comprehensive collection of all small-molecule drugs approved for human use would be invaluable for systematic repurposing across human diseases, particularly for rare and neglected diseases, for which the cost and time required for development of a new chemical entity are often prohibitive. Previous efforts to build such a comprehensive collection have been limited by the complexities, redundancies, and semantic inconsistencies of drug naming within and among regulatory agencies worldwide; a lack of clear conceptualization of what constitutes a drug; and a lack of access to physical samples. We report here the creation of a definitive, complete, and nonredundant list of all approved molecular entities as a freely available electronic resource and a physical collection of small molecules amenable to high-throughput screening.

Examining the Chirality, Conformation and Selective Kinase Inhibition of 3-((3R,4R)-4-methyl-3-(methyl(7H-pyrrolo[2,3-d]pyrimidin-4-yl)amino)piperidin-1-yl)-3-oxopropanenitrile (CP-690,550)

Here, we examine the significance that stereochemistry plays within the clinically relevant Janus kinase 3 (Jak3) inhibitor 1 (CP-690,550). A synthesis of all four enantiopure stereoisomers of the drug was carried out and an examination of each compound revealed that only the enantiopure 3R,4R isomer was capable of blocking Stat5 phosphorylation (Jak3 dependent). Each compound was profiled across a panel of over 350 kinases, which revealed a high level of selectivity for the Jak family kinases for these related compounds. Each stereoisomer retained a degree of binding to Jak3 and Jak2 and the 3R,4S and 3S,4R stereoisomers were further revealed to have binding affinity for selected members of the STE7 and STE20 subfamily of kinases. Finally, an appraisal of the minimum energy conformation of each stereoisomer and molecular docking at Jak3 was performed in an effort to better understand each compounds selectivity and potency profiles.

A Specific Mechanism for Nonspecific Activation in Reporter-Gene Assays

The importance of bioluminescence in enabling a broad range of high-throughput screening (HTS) assay formats is evidenced by widespread use in industry and academia. Therefore, understanding the mechanisms by which reporter enzyme activity can be modulated by small molecules is critical to the interpretation of HTS data. In this Perspective, we provide evidence for stabilization of luciferase by inhibitors in cell-based luciferase reporter-gene assays resulting in the counterintuitive phenomenon of signal activation. These data were derived from our analysis of luciferase inhibitor compound structures and their prevalence in the Molecular Libraries Small Molecule Repository using 100 HTS experiments available in PubChem. Accordingly, we found an enrichment of luciferase inhibitors in luciferase reporter-gene activation assays but not in assays using other reporters. In addition, for several luciferase inhibitor chemotypes, we measured reporter stabilization and signal activation in cells that paralleled the inhibition determined using purified luciferase to provide further experimental support for these contrasting effects.

A Grid Algorithm for High Throughput Fitting of Dose-Response Curve Data

We describe a novel algorithm, Grid algorithm, and the corresponding computer program for high throughput fitting of dose-response curves that are described by the four-parameter symmetric logistic dose-response model. The Grid algorithm searches through all points in a grid of four dimensions (parameters) and finds the optimum one that corresponds to the best fit. Using simulated dose-response curves, we examined the Grid program’s performance in reproducing the actual values that were used to generate the simulated data and compared it with the DRC package for the language and environment R and the XLfit add-in for Microsoft Excel. The Grid program was robust and consistently recovered the actual values for both complete and partial curves with or without noise. Both DRC and XLfit performed well on data without noise, but they were sensitive to and their performance degraded rapidly with increasing noise. The Grid program is automated and scalable to millions of dose-response curves, and it is able to process 100,000 dose-response curves from high throughput screening experiment per CPU hour. The Grid program has the potential of greatly increasing the productivity of large-scale dose-response data analysis and early drug discovery processes, and it is also applicable to many other curve fitting problems in chemical, biological, and medical sciences.

Potent and selective small molecule inhibitors of specific isoforms of Cdc2-like kinases (Clk) and dual specificity tyrosine-phosphorylation-regulated kinases (Dyrk).

Continued examination of substituted 6-arylquinazolin-4-amines as Clk4 inhibitors resulted in selective inhibitors of Clk1, Clk4, Dyrk1A and Dyrk1B. Several of the most potent inhibitors were validated as being highly selective within a comprehensive kinome scan.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high-throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation.

Pharos: Collating protein information to shed light on the druggable genome

The ‘druggable genome’ encompasses several protein families, but only a subset of targets within them have attracted significant research attention and thus have information about them publicly available. The Illuminating the Druggable Genome (IDG) program was initiated in 2014, has the goal of developing experimental techniques and a Knowledge Management Center (KMC) that would collect and organize information about protein targets from four families, representing the most common druggable targets with an emphasis on understudied proteins. Here, we describe two resources developed by the KMC: the Target Central Resource Database (TCRD) which collates many heterogeneous gene/protein datasets and Pharos (https://pharos.nih.gov), a multimodal web interface that presents the data from TCRD. We briefly describe the types and sources of data considered by the KMC and then highlight features of the Pharos interface designed to enable intuitive access to the IDG knowledgebase. The aim of Pharos is to encourage ‘serendipitous browsing’, whereby related, relevant information is made easily discoverable. We conclude by describing two use cases that highlight the utility of Pharos and TCRD.

BioAssay Research Database (BARD): chemical biology and probe-development enabled by structured metadata and result types.

BARD, the BioAssay Research Database (https://bard.nih.gov/) is a public database and suite of tools developed to provide access to bioassay data produced by the NIH Molecular Libraries Program (MLP). Data from 631 MLP projects were migrated to a new structured vocabulary designed to capture bioassay data in a formalized manner, with particular emphasis placed on the description of assay protocols. New data can be submitted to BARD with a user-friendly set of tools that assist in the creation of appropriately formatted datasets and assay definitions. Data published through the BARD application program interface (API) can be accessed by researchers using web-based query tools or a desktop client. Third-party developers wishing to create new tools can use the API to produce stand-alone tools or new plug-ins that can be integrated into BARD. The entire BARD suite of tools therefore supports three classes of researcher: those who wish to publish data, those who wish to mine data for testable hypotheses, and those in the developer community who wish to build tools that leverage this carefully curated chemical biology resource.

Dealing with the Data Deluge: Handling the Multitude Of Chemical Biology Data Sources

Over the last 20 years, there has been an explosion in the amount and type of biological and chemical data that has been made publicly available in a variety of online databases. While this means that vast amounts of information can be found online, there is no guarantee that it can be found easily (or at all). A scientist searching for a specific piece of information is faced with a daunting task—many databases have overlapping content, use their own identifiers and, in some cases, have arcane and unintuitive user interfaces. In this overview, a variety of well‐known data sources for chemical and biological information are highlighted, focusing on those most useful for chemical biology research. The issue of using data from multiple sources and the associated problems such as identifier disambiguation are highlighted. A brief discussion is then provided on Tripod, a recently developed platform that supports the integration of arbitrary data sources, providing users a simple interface to search across a federated collection of resources. Curr. Protoc. Chem. Biol. 4:193‐209

Advancing precision medicine with personalized drug screening

Personalized drug screening (PDS) of approved drug libraries enables rapid development of specific small-molecule therapies for individual patients. With a multidisciplinary team including clinicians, researchers, ethicists, informaticians and regulatory professionals, patient treatment can be optimized with greater efficacy and fewer adverse effects by using PDS as an approach to find remedies. In addition, PDS has the potential to rapidly identify therapeutics for a patient suffering from a disease without an existing therapy. From cancer to bacterial infections, we review specific maladies addressed with PDS campaigns. We predict that PDS combined with personal genomic analyses will contribute to the development of future precision medicine endeavors.