Caty Chung

Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High- Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS)

The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.

Evolving BioAssay Ontology (BAO): modularization, integration and applications

The lack of established standards to describe and annotate biological assays and screening outcomes in the domain of drug and chemical probe discovery is a severe limitation to utilize public and proprietary drug screening data to their maximum potential. We have created the BioAssay Ontology (BAO) project (http://bioassayontology.org) to develop common reference metadata terms and definitions required for describing relevant information of low-and high-throughput drug and probe screening assays and results. The main objectives of BAO are to enable effective integration, aggregation, retrieval, and analyses of drug screening data. Since we first released BAO on the BioPortal in 2010 we have considerably expanded and enhanced BAO and we have applied the ontology in several internal and external collaborative projects, for example the BioAssay Research Database (BARD). We describe the evolution of BAO with a design that enables modeling complex assays including profile and panel assays such as those in the Library of Integrated Network-based Cellular Signatures (LINCS). One of the critical questions in evolving BAO is the following: how can we provide a way to efficiently reuse and share among various research projects specific parts of our ontologies without violating the integrity of the ontology and without creating redundancies. This paper provides a comprehensive answer to this question with a description of a methodology for ontology modularization using a layered architecture. Our modularization approach defines several distinct BAO components and separates internal from external modules and domain-level from structural components. This approach facilitates the generation/extraction of derived ontologies (or perspectives) that can suit particular use cases or software applications. We describe the evolution of BAO related to its formal structures, engineering approaches, and content to enable modeling of complex assays and integration with other ontologies and datasets.

Formalization, Annotation and Analysis of Diverse Drug and Probe Screening Assay Datasets Using the BioAssay Ontology (BAO)

Huge amounts of high-throughput screening (HTS) data for probe and drug development projects are being generated in the pharmaceutical industry and more recently in the public sector. The resulting experimental datasets are increasingly being disseminated via publically accessible repositories. However, existing repositories lack sufficient metadata to describe the experiments and are often difficult to navigate by non-experts. The lack of standardized descriptions and semantics of biological assays and screening results hinder targeted data retrieval, integration, aggregation, and analyses across different HTS datasets, for example to infer mechanisms of action of small molecule perturbagens. To address these limitations, we created the BioAssay Ontology (BAO). BAO has been developed with a focus on data integration and analysis enabling the classification of assays and screening results by concepts that relate to format, assay design, technology, target, and endpoint. Previously, we reported on the higher-level design of BAO and on the semantic querying capabilities offered by the ontology-indexed triple store of HTS data. Here, we report on our detailed design, annotation pipeline, substantially enlarged annotation knowledgebase, and analysis results. We used BAO to annotate assays from the largest public HTS data repository, PubChem, and demonstrate its utility to categorize and analyze diverse HTS results from numerous experiments. BAO is publically available from the NCBO BioPortal at http://bioportal.bioontology.org/ontologies/1533. BAO provides controlled terminology and uniform scope to report probe and drug discovery screening assays and results. BAO leverages description logic to formalize the domain knowledge and facilitate the semantic integration with diverse other resources. As a consequence, BAO offers the potential to infer new knowledge from a corpus of assay results, for example molecular mechanisms of action of perturbagens.

Discovery of a novel submicromolar inhibitor of the lymphoid specific tyrosine phosphatase.

We report here a class of thiazolidine-2,4-diones and 2-thioxothiazolidin-4-ones as potent inhibitors of the lymphoid specific tyrosine phosphatase (Lyp) identified from high throughput screens. Chemical modification by incorporating the known phosphotyrosine (pTyr) mimics led to the discovery of a salicylate-based inhibitor with submicromolar potency.

Comparison of Miniaturized Time-Resolved Fluorescence Resonance Energy Transfer and Enzyme-Coupled Luciferase High-Throughput Screening Assays to Discover Inhibitors of Rho-Kinase II (ROCK-II)

Kinases are important drug discovery targets for a wide variety of therapeutic indications; consequently, the measurement of kinase activity remains a common high-throughput screening (HTS) application. Recently, enzyme-coupled luciferase-kinase (LK) format assays have been introduced. This format measures luminescence resulting from metabolism of adenosine triphosphate (ATP) via a luciferin/luciferase-coupled reaction. In the research presented here, 1536-well format time-resolved fluorescence resonance energy transfer (TR-FRET) and LK assays were created to identify novel Rho-associated kinase II (ROCK-II) inhibitors. HTS campaigns for both assays were conducted in this miniaturized format. It was found that both assays were able to consistently reproduce the expected pharmacology of inhibitors known to be specific to ROCK-II (fasudil IC50: 283 ± 27 nM and 336 ± 54 nM for TR-FRET and LK assays, respectively; Y-27632 IC50: 133 ± 7.8 nM and 150 ± 22 nM for TR-FRET and LK assays, respectively). In addition, both assays proved robust for HTS efforts, demonstrating excellent plate Z′ values during the HTS campaign (0.84 ± 0.03; 0.72 ± 0.05 for LK and TR-FRET campaigns, respectively). Both formats identified scaffolds of known and novel ROCK-II inhibitors with similar sensitivity. A comparison of the performance of these 2 assay formats in an HTS campaign was enabled by the existence of a subset of 25,000 compounds found in both our institutional and the Molecular Library Screening Center Network screening files. Analysis of the HTS campaign results based on this subset of common compounds showed that both formats had comparable total hit rates, hit distributions, amount of hit clusters, and format-specific artifact. It can be concluded that both assay formats are suitable for the discovery of ROCK-II inhibitors, and the choice of assay format depends on reagents and/or screening technology available. (Journal of Biomolecular Screening 2008:17-28)

Inhibition of lymphoid tyrosine phosphatase by benzofuran salicylic acids

The lymphoid tyrosine phosphatase (Lyp, PTPN22) is a critical negative regulator of T cell antigen receptor (TCR) signaling. A single-nucleotide polymorphism (SNP) in the ptpn22 gene correlates with the incidence of various autoimmune diseases, including type 1 diabetes, rheumatoid arthritis, and systemic lupus erythematosus. Since the disease-associated allele is a more potent inhibitor of TCR signaling, specific Lyp inhibitors may become valuable in treating autoimmunity. Using a structure-based approach, we synthesized a library of 34 compounds that inhibited Lyp with IC(50) values between 0.27 and 6.2 μM. A reporter assay was employed to screen for compounds that enhanced TCR signaling in cells, and several inhibitors displayed a dose-dependent, activating effect. Subsequent probing for Lyps direct physiological targets by immunoblot analysis confirmed the ability of the compounds to inhibit Lyp in T cells. Selectivity profiling against closely related tyrosine phosphatases and in silico docking studies with the crystal structure of Lyp yielded valuable information for the design of Lyp-specific compounds.

Discovery of Potent Non-urea Inhibitors of Soluble Epoxide Hydrolase

Soluble epoxide hydrolase (sEH) is a novel target for the treatment of hypertension and vascular inflammation. A new class of potent non-urea sEH inhibitors was identified via high throughput screening (HTS) and chemical modification. IC(50)s of the most potent compounds range from micromolar to low nanomolar.

Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: Integrated access to diverse large-scale cellular perturbation response data

Abstract The Library of Integrated Network-based Cellular Signatures (LINCS) program is a national consortium funded by the NIH to generate a diverse and extensive reference library of cell-based perturbation-response signatures, along with novel data analytics tools to improve our understanding of human diseases at the systems level. In contrast to other large-scale data generation efforts, LINCS Data and Signature Generation Centers (DSGCs) employ a wide range of assay technologies cataloging diverse cellular responses. Integration of, and unified access to LINCS data has therefore been particularly challenging. The Big Data to Knowledge (BD2K) LINCS Data Coordination and Integration Center (DCIC) has developed data standards specifications, data processing pipelines, and a suite of end-user software tools to integrate and annotate LINCS-generated data, to make LINCS signatures searchable and usable for different types of users. Here, we describe the LINCS Data Portal (LDP) (http://lincsportal.ccs.miami.edu/), a unified web interface to access datasets generated by the LINCS DSGCs, and its underlying database, LINCS Data Registry (LDR). LINCS data served on the LDP contains extensive metadata and curated annotations. We highlight the features of the LDP user interface that is designed to enable search, browsing, exploration, download and analysis of LINCS data and related curated content.

Potent inhibitors of Huntingtin protein aggregation in a cell-based assay.

A quinazoline that decreases polyglutamine aggregate burden in a cell-based assay was identified from a high-throughput screen of a chemical-compound library, provided by the NIH Molecular Libraries Small Molecule Repository (MLSMR). A structure and activity study yielded leads with submicromolar potency.

Discovery of novel small molecule cell type-specific enhancers of NF-κB nuclear translocation

An IKKbeta inhibitor reported to block NF-kappaB transcriptional activities in Jurkat T cells, was found to enhance NF-kappaB translocation in HUVEC cells. These studies suggested a noncanonical NF-kappaB signaling pathway independent of IKKbeta in HUVEC cells.