Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem. Here, we explore how to use this comprehensive mapping of chemical biology space to support the development of large-scale quantitative structure-activity relationship (QSAR) models. We propose a new deep learning consensus architecture (DLCA) that combines consensus and multitask deep learning approaches together to generate large-scale QSAR models. This method improves knowledge transfer across different target/assays while also integrating contributions from models based on different descriptors. The proposed approach was validated and compared with proteochemometrics, multitask deep learning, and Random Forest methods paired with various descriptors types. DLCA models demonstrated improved prediction accuracy for both regression and classification tasks. The best models together with their modeling sets are provided through publicly available web services at https://predictor.ncats.io .

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (-)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening.

INTRODUCTION: Drug plasma protein binding remains highly relevant to research and drug development, making the assessment and profiling of compound affinity to plasma proteins essential to drug discovery efforts. Although there are a number of fully-characterized methods, they lack the throughput to handle large numbers of compounds. As the evaluation of adsorption, distribution, metabolism, and excretion is addressed earlier in the drug development timeline, the need for higher-throughput methods has grown. Areas Covered: This review will highlight recent developments on methods for profiling drug plasma binding, with an emphasis on fluorescent probes and emerging high-throughput methodologies. Expert Opinion: There have been a number of high-throughput assays developed in recent years to meet the scaled up demands for compound profiling. Ultimately, the selection of assay technology relies on a number of factors, such as capabilities of the laboratory and the breadth and amount of data required. Fluorescent probe displacement assays are highly flexible and amenable to high-throughput screening, easily scaling up to handle large compound libraries. Recent developments in fluorescence technologies, such as homogenous time-resolved fluorescence and probes utilizing the aggregation-induced emission effect, have improved the sensitivity of these assays. Other technologies, such as microscale thermophoresis and quantitative structure-activity relationship modeling, are gaining popularity as alternative techniques for drug plasma protein binding characterization.

Aldehyde dehydrogenases (ALDHs) are responsible for the metabolism of aldehydes (exogenous and endogenous) and possess vital physiological and toxicological functions in areas such as CNS, inflammation, metabolic disorders, and cancers. Overexpression of certain ALDHs (e.g., ALDH1A1) is an important biomarker in cancers and cancer stem cells (CSCs) indicating the potential need for the identification and development of small molecule ALDH inhibitors. Herein, a newly designed series of quinoline-based analogs of ALDH1A1 inhibitors is described. Extensive medicinal chemistry optimization and biological characterization led to the identification of analogs with significantly improved enzymatic and cellular ALDH inhibition. Selected analogs, e.g., 86 (NCT-505) and 91 (NCT-506), demonstrated target engagement in a cellular thermal shift assay (CETSA), inhibited the formation of 3D spheroid cultures of OV-90 cancer cells, and potentiated the cytotoxicity of paclitaxel in SKOV-3-TR, a paclitaxel resistant ovarian cancer cell line. Lead compounds also exhibit high specificity over other ALDH isozymes and unrelated dehydrogenases. The in vitro ADME profiles and pharmacokinetic evaluation of selected analogs are also highlighted.

Proliferating cells, including cancer cells, obtain serine both exogenously and via the metabolism of glucose. By catalyzing the first, rate-limiting step in the synthesis of serine from glucose, phosphoglycerate dehydrogenase (PHGDH) controls flux through the biosynthetic pathway for this important amino acid and represents a putative target in oncology. To discover inhibitors of PHGDH, a coupled biochemical assay was developed and optimized to enable high-throughput screening for inhibitors of human PHGDH. Feedback inhibition was minimized by coupling PHGDH activity to two downstream enzymes (PSAT1 and PSPH), providing a marked improvement in enzymatic turnover. Further coupling of NADH to a diaphorase/resazurin system enabled a red-shifted detection readout, minimizing interference due to compound autofluorescence. With this protocol, over 400,000 small molecules were screened for PHGDH inhibition, and following hit validation and triage work, a piperazine-1-thiourea was identified. Following rounds of medicinal chemistry and SAR exploration, two probes (NCT-502 and NCT-503) were identified. These molecules demonstrated improved target activity and encouraging ADME properties, enabling in vitro assessment of the biological importance of PHGDH, and its role in the fate of serine in PHGDH-dependent cancer cells. This manuscript reports the assay development and medicinal chemistry leading to the development of NCT-502 and -503 reported in Pacold et al. (2016).

The development of novel neuroprotective treatments for acute stroke has been fraught with failures, which supports the view of ischemic brain damage as a highly complex multifactorial process. Post-translational modifications such as small ubiquitin-like modifier (SUMO)ylation have emerged as critical molecular regulatory mechanisms in states of both homeostasis and ischemic stress, as evidenced by our previous work. Accordingly, the clinical significance of the selective control of the global SUMOylation process has become apparent in studies of ischemic pathobiology and pathophysiology. Herein, we describe a process capable of identifying and characterizing small molecules with the potential of targeting the SUMO system through inhibition of SUMO deconjugation in an effort to develop novel stroke therapies.-Bernstock, J. D., Ye, D., Smith, J. A., Lee, Y.-J., Gessler, F. A., Yasgar, A., Kouznetsova, J., Jadhav, A., Wang, Z., Pluchino, S., Zheng, W., Simeonov, A., Hallenbeck, J. M., Yang, W. Quantitative high-throughput screening identifies cytoprotective molecules that enhance SUMO-conjugation via the inhibition of SUMO-specific protease (SENP)2.

We describe the parallel synthesis of novel analogs of GW0742, a peroxisome proliferator-activated receptor δ (PPARδ) agonist. For that purpose, modified reaction conditions were applied, such as a solid-phase palladium-catalyzed Suzuki coupling. In addition, tetrazole-based compounds were generated as a bioisostere for carboxylic acid-containing ligand GW0742. The new compounds were investigated for their ability to activate PPARδ mediated transcription and their cross-reactivity with the vitamin D receptor (VDR), another member of the nuclear receptor superfamily. We identified many potent PPARδ agonists that were less toxic than GW0742, where ∼65 of the compounds synthesized exhibited partial PPARδ activity (23-98%) with EC50 values ranging from 0.007-18.2 μM. Some ligands, such as compound 32, were more potent inhibitors of VDR-mediated transcription with significantly reduced PPARδ activity than GW0742, however, none of the ligands were completely selective for VDR inhibition over PPARδ activation of transcription.

Aldehyde dehydrogenase enzymes (ALDHs) have a broad spectrum of biological activities through the oxidation of both endogenous and exogenous aldehydes. Increased expression of ALDH1A1 has been identified in a wide-range of human cancer stem cells and is associated with cancer relapse and poor prognosis, raising the potential of ALDH1A1 as a therapeutic target. To facilitate quantitative high-throughput screening (qHTS) campaigns for the discovery, characterization and structure-activity-relationship (SAR) studies of small molecule ALDH1A1 inhibitors with cellular activity, we show herein the miniaturization to 1536-well format and automation of a high-content cell-based ALDEFLUOR assay. We demonstrate the utility of this assay by generating dose-response curves on a comprehensive set of prior art inhibitors as well as hundreds of ALDH1A1 inhibitors synthesized in house. Finally, we established a screening paradigm using a pair of cell lines with low and high ALDH1A1 expression, respectively, to uncover novel cell-active ALDH1A1-specific inhibitors from a collection of over 1,000 small molecules.

The endoplasmic reticulum (ER) is involved in Ca2+ signaling and protein folding. ER Ca2+ depletion and accumulation of unfolded proteins activate the molecular chaperone GRP78 (glucose-regulated protein 78) which in turn triggers the ER stress response (ERSR) pathway aimed to restore ER homeostasis. Failure to adapt to stress, however, results in apoptosis. We and others have shown that malignant cells are more susceptible to ERSR-induced apoptosis than their normal counterparts, implicating the ERSR as a potential target for cancer therapeutics. Predicated on these findings, we developed an assay that uses a GRP78 biosensor to identify small molecule activators of ERSR in glioma cells. We performed a quantitative high-throughput screen (qHTS) against a collection of ~425,000 compounds and a comprehensive panel of orthogonal secondary assays was formulated for stringent compound validation. We identified novel activators of ERSR, including a compound with a 2,9-diazaspiro[5.5]undecane core, which depletes intracellular Ca2+ stores and induces apoptosis-mediated cell death in several cancer cell lines, including patient-derived and 3D cultures of glioma cells. This study demonstrates that our screening platform enables the identification and profiling of ERSR inducers with cytotoxic activity and advocates for characterization of these compound in in vivo models.

Enzymes in essential metabolic pathways are attractive targets for the treatment of bacterial diseases, but in many cases, the presence of homologous human enzymes makes them impractical candidates for drug development. Fumarate hydratase, an essential enzyme in the tricarboxylic acid (TCA) cycle, has been identified as one such potential therapeutic target in tuberculosis. We report the discovery of the first small molecule inhibitor, to our knowledge, of the Mycobacterium tuberculosis fumarate hydratase. A crystal structure at 2.0-Å resolution of the compound in complex with the protein establishes the existence of a previously unidentified allosteric regulatory site. This allosteric site allows for selective inhibition with respect to the homologous human enzyme. We observe a unique binding mode in which two inhibitor molecules interact within the allosteric site, driving significant conformational changes that preclude simultaneous substrate and inhibitor binding. Our results demonstrate the selective inhibition of a highly conserved metabolic enzyme that contains identical active site residues in both the host and the pathogen.