Publications by authors named "Hongmao Sun"

46 Publications

Human GPR17 missense variants identified in metabolic disease patients have distinct downstream signaling profiles.

J Biol Chem 2021 Jun 16;297(1):100881. Epub 2021 Jun 16.

Herman B. Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA; Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Pharmacology & Toxicology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, Indiana, USA. Electronic address:

GPR17 is a G-protein-coupled receptor (GPCR) implicated in the regulation of glucose metabolism and energy homeostasis. Such evidence is primarily drawn from mouse knockout studies and suggests GPR17 as a potential novel therapeutic target for the treatment of metabolic diseases. However, links between human GPR17 genetic variants, downstream cellular signaling, and metabolic diseases have yet to be reported. Here, we analyzed GPR17 coding sequences from control and disease cohorts consisting of individuals with adverse clinical metabolic deficits including severe insulin resistance, hypercholesterolemia, and obesity. We identified 18 nonsynonymous GPR17 variants, including eight variants that were exclusive to the disease cohort. We characterized the protein expression levels, membrane localization, and downstream signaling profiles of nine GPR17 variants (F43L, V96M, V103M, D105N, A131T, G136S, R248Q, R301H, and G354V). These nine GPR17 variants had similar protein expression and subcellular localization as wild-type GPR17; however, they showed diverse downstream signaling profiles. GPR17-G136S lost the capacity for agonist-mediated cAMP, Ca, and β-arrestin signaling. GPR17-V96M retained cAMP inhibition similar to GPR17-WT, but showed impaired Ca and β-arrestin signaling. GPR17-D105N displayed impaired cAMP and Ca signaling, but unaffected agonist-stimulated β-arrestin recruitment. The identification and functional profiling of naturally occurring human GPR17 variants from individuals with metabolic diseases revealed receptor variants with diverse signaling profiles, including differential signaling perturbations that resulted in GPCR signaling bias. Our findings provide a framework for structure-function relationship studies of GPR17 signaling and metabolic disease.
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http://dx.doi.org/10.1016/j.jbc.2021.100881DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8267566PMC
June 2021

Retro Drug Design: From Target Properties to Molecular Structures.

bioRxiv 2021 May 12. Epub 2021 May 12.

To generate drug molecules of desired properties with computational methods is the holy grail in pharmaceutical research. Here we describe an AI strategy, retro drug design, or RDD, to generate novel small molecule drugs from scratch to meet predefined requirements, including but not limited to biological activity against a drug target, and optimal range of physicochemical and ADMET properties. Traditional predictive models were first trained over experimental data for the target properties, using an atom typing based molecular descriptor system, ATP. Monte Carlo sampling algorithm was then utilized to find the solutions in the ATP space defined by the target properties, and the deep learning model of Seq2Seq was employed to decode molecular structures from the solutions. To test feasibility of the algorithm, we challenged RDD to generate novel drugs that can activate μ opioid receptor (MOR) and penetrate blood brain barrier (BBB). Starting from vectors of random numbers, RDD generated 180,000 chemical structures, of which 78% were chemically valid. About 42,000 (31%) of the valid structures fell into the property space defined by MOR activity and BBB permeability. Out of the 42,000 structures, only 267 chemicals were commercially available, indicating a high extent of novelty of the AI-generated compounds. We purchased and assayed 96 compounds, and 25 of which were found to be MOR agonists. These compounds also have excellent BBB scores. The results presented in this paper illustrate that RDD has potential to revolutionize the current drug discovery process and create novel structures with multiple desired properties, including biological functions and ADMET properties. Availability of an AI-enabled fast track in drug discovery is essential to cope with emergent public health threat, such as pandemic of COVID-19.
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http://dx.doi.org/10.1101/2021.05.11.442656DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132216PMC
May 2021

Identification of SARS-CoV-2 viral entry inhibitors using machine learning and cell-based pseudotyped particle assay.

Bioorg Med Chem 2021 05 26;38:116119. Epub 2021 Mar 26.

National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Dr., Rockville, MD 20850, USA. Electronic address:

In response to the pandemic caused by SARS-CoV-2, we constructed a hybrid support vector machine (SVM) classification model using a set of publicly posted SARS-CoV-2 pseudotyped particle (PP) entry assay repurposing screen data to identify novel potent compounds as a starting point for drug development to treat COVID-19 patients. Two different molecular descriptor systems, atom typing descriptors and 3D fingerprints (FPs), were employed to construct the SVM classification models. Both models achieved reasonable performance, with the area under the curve of receiver operating characteristic (AUC-ROC) of 0.84 and 0.82, respectively. The consensus prediction outperformed the two individual models with significantly improved AUC-ROC of 0.91, where the compounds with inconsistent classifications were excluded. The consensus model was then used to screen the 173,898 compounds in the NCATS annotated and diverse chemical libraries. Of the 255 compounds selected for experimental confirmation, 116 compounds exhibited inhibitory activities in the SARS-CoV-2 PP entry assay with IC values ranged between 0.17 µM and 62.2 µM, representing an enrichment factor of 3.2. These 116 active compounds with diverse and novel structures could potentially serve as starting points for chemistry optimization for COVID-19 drug discovery.
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http://dx.doi.org/10.1016/j.bmc.2021.116119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997310PMC
May 2021

Chemoprotective antimalarials identified through quantitative high-throughput screening of Plasmodium blood and liver stage parasites.

Sci Rep 2021 Jan 22;11(1):2121. Epub 2021 Jan 22.

Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, 10032, USA.

The spread of Plasmodium falciparum parasites resistant to most first-line antimalarials creates an imperative to enrich the drug discovery pipeline, preferably with curative compounds that can also act prophylactically. We report a phenotypic quantitative high-throughput screen (qHTS), based on concentration-response curves, which was designed to identify compounds active against Plasmodium liver and asexual blood stage parasites. Our qHTS screened over 450,000 compounds, tested across a range of 5 to 11 concentrations, for activity against Plasmodium falciparum asexual blood stages. Active compounds were then filtered for unique structures and drug-like properties and subsequently screened in a P. berghei liver stage assay to identify novel dual-active antiplasmodial chemotypes. Hits from thiadiazine and pyrimidine azepine chemotypes were subsequently prioritized for resistance selection studies, yielding distinct mutations in P. falciparum cytochrome b, a validated antimalarial drug target. The thiadiazine chemotype was subjected to an initial medicinal chemistry campaign, yielding a metabolically stable analog with sub-micromolar potency. Our qHTS methodology and resulting dataset provides a large-scale resource to investigate Plasmodium liver and asexual blood stage parasite biology and inform further research to develop novel chemotypes as causal prophylactic antimalarials.
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http://dx.doi.org/10.1038/s41598-021-81486-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822874PMC
January 2021

Deep Graph Learning with Property Augmentation for Predicting Drug-Induced Liver Injury.

Chem Res Toxicol 2021 Feb 21;34(2):495-506. Epub 2020 Dec 21.

Department of Computer Science, University of Texas at Arlington, Arlington, Texas 76013, United States.

Drug-induced liver injury (DILI) is a crucial factor in determining the qualification of potential drugs. However, the DILI property is excessively difficult to obtain due to the complex testing process. Consequently, an screening in the early stage of drug discovery would help to reduce the total development cost by filtering those drug candidates with a high risk to cause DILI. To serve the screening goal, we apply several computational techniques to predict the DILI property, including traditional machine learning methods and graph-based deep learning techniques. While deep learning models require large training data to tune huge model parameters, the DILI data set only contains a few hundred annotated molecules. To alleviate the data scarcity problem, we propose a property augmentation strategy to include massive training data with other property information. Extensive experiments demonstrate that our proposed method significantly outperforms all existing baselines on the DILI data set by obtaining a 81.4% accuracy using cross-validation with random splitting, 78.7% using leave-one-out cross-validation, and 76.5% using cross-validation with scaffold splitting.
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http://dx.doi.org/10.1021/acs.chemrestox.0c00322DOI Listing
February 2021

Predictive models for estimating cytotoxicity on the basis of chemical structures.

Bioorg Med Chem 2020 05 12;28(10):115422. Epub 2020 Mar 12.

National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Dr., Rockville, MD 20850, United States. Electronic address:

Cytotoxicity is a critical property in determining the fate of a small molecule in the drug discovery pipeline. Cytotoxic compounds are identified and triaged in both target-based and cell-based phenotypic approaches due to their off-target toxicity or on-target and on-mechanism toxicity for oncology and neurodegenerative targets. It is critical that chemical-induced cytotoxicity be reliably predicted before drug candidates advance to the late stage of development, or more ideally, before compounds are synthesized. In this study, we assessed the cell-based cytotoxicity of nearly 10,000 compounds in NCATS annotated libraries against four 'normal' cell lines (HEK 293, NIH 3T3, CRL-7250 and HaCat) using CellTiter-Glo (CTG) technology and constructed highly predictive models to estimate cytotoxicity from chemical structures. There are 5,241 non-redundant compounds having unambiguous activities in the four different cell lines, among which 11.8% compounds exhibited cytotoxicity in two or more cell lines and are thus labelled cytotoxic. The support vector classification (SVC) models trained with 80% randomly selected molecules achieved the area under the receiver operating characteristic curve (AUC-ROC) of 0.88 on average for the remaining 20% compounds in the test sets in 10 repeating experiments. Application of under-sampling rebalancing method further improved the averaged AUC-ROC to 0.90. Analysis of structural features shared by cytotoxic compounds may offer medicinal chemists heuristic design ideas to eliminate undesirable cytotoxicity. The profiling of cytotoxicity of drug-like molecules with annotated primary mechanism of action (MOA) will inform on the roles played by different targets or pathways in cellular viability. The predictive models for cytotoxicity (accessible at https://tripod.nih.gov/web_adme/cytotox.html) provide the scientific community a fast yet reliable way to prioritize molecules with little or no cytotoxicity for downstream development.
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http://dx.doi.org/10.1016/j.bmc.2020.115422DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881917PMC
May 2020

Physiologically relevant orthogonal assays for the discovery of small-molecule modulators of WIP1 phosphatase in high-throughput screens.

J Biol Chem 2019 11 3;294(46):17654-17668. Epub 2019 Sep 3.

National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20850

WT P53-Induced Phosphatase 1 (WIP1) is a member of the magnesium-dependent serine/threonine protein phosphatase (PPM) family and is induced by P53 in response to DNA damage. In several human cancers, the WIP1 protein is overexpressed, which is generally associated with a worse prognosis. Although WIP1 is an attractive therapeutic target, no potent, selective, and bioactive small-molecule modulator with favorable pharmacokinetics has been reported. Phosphatase enzymes are among the most challenging targets for small molecules because of the difficulty of achieving both modulator selectivity and bioavailability. Another major obstacle has been the availability of robust and physiologically relevant phosphatase assays that are suitable for high-throughput screening. Here, we describe orthogonal biochemical WIP1 activity assays that utilize phosphopeptides from native WIP1 substrates. We optimized an MS assay to quantify the enzymatically dephosphorylated peptide reaction product in a 384-well format. Additionally, a red-shifted fluorescence assay was optimized in a 1,536-well format to enable real-time WIP1 activity measurements through the detection of the orthogonal reaction product, P We validated these two optimized assays by quantitative high-throughput screening against the National Center for Advancing Translational Sciences (NCATS) Pharmaceutical Collection and used secondary assays to confirm and evaluate inhibitors identified in the primary screen. Five inhibitors were further tested with an orthogonal WIP1 activity assay and surface plasmon resonance binding studies. Our results validate the application of miniaturized physiologically relevant and orthogonal WIP1 activity assays to discover small-molecule modulators from high-throughput screens.
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http://dx.doi.org/10.1074/jbc.RA119.010201DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873202PMC
November 2019

Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.

Bioorg Med Chem 2019 07 27;27(14):3110-3114. Epub 2019 May 27.

National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Dr., Rockville, MD 20850, United States. Electronic address:

Aqueous solubility is one of the most important properties in drug discovery, as it has profound impact on various drug properties, including biological activity, pharmacokinetics (PK), toxicity, and in vivo efficacy. Both kinetic and thermodynamic solubilities are determined during different stages of drug discovery and development. Since kinetic solubility is more relevant in preclinical drug discovery research, especially during the structure optimization process, we have developed predictive models for kinetic solubility with in-house data generated from 11,780 compounds collected from over 200 NCATS intramural research projects. This represents one of the largest kinetic solubility datasets of high quality and integrity. Based on the customized atom type descriptors, the support vector classification (SVC) models were trained on 80% of the whole dataset, and exhibited high predictive performance for estimating the solubility of the remaining 20% compounds within the test set. The values of the area under the receiver operating characteristic curve (AUC-ROC) for the compounds in the test sets reached 0.93 and 0.91, when the threshold for insoluble compounds was set to 10 and 50 μg/mL respectively. The predictive models of aqueous solubility can be used to identify insoluble compounds in drug discovery pipeline, provide design ideas for improving solubility by analyzing the atom types associated with poor solubility and prioritize compound libraries to be purchased or synthesized.
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http://dx.doi.org/10.1016/j.bmc.2019.05.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274818PMC
July 2019

Thymine DNA glycosylase as a novel target for melanoma.

Oncogene 2019 05 23;38(19):3710-3728. Epub 2019 Jan 23.

Cancer Epigenetics Program, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA, 19111, USA.

Melanoma is an aggressive neoplasm with increasing incidence that is classified by the NCI as a recalcitrant cancer, i.e., a cancer with poor prognosis, lacking progress in diagnosis and treatment. In addition to conventional therapy, melanoma treatment is currently based on targeting the BRAF/MEK/ERK signaling pathway and immune checkpoints. As drug resistance remains a major obstacle to treatment success, advanced therapeutic approaches based on novel targets are still urgently needed. We reasoned that the base excision repair enzyme thymine DNA glycosylase (TDG) could be such a target for its dual role in safeguarding the genome and the epigenome, by performing the last of the multiple steps in DNA demethylation. Here we show that TDG knockdown in melanoma cell lines causes cell cycle arrest, senescence, and death by mitotic alterations; alters the transcriptome and methylome; and impairs xenograft tumor formation. Importantly, untransformed melanocytes are minimally affected by TDG knockdown, and adult mice with conditional knockout of Tdg are viable. Candidate TDG inhibitors, identified through a high-throughput fluorescence-based screen, reduced viability and clonogenic capacity of melanoma cell lines and increased cellular levels of 5-carboxylcytosine, the last intermediate in DNA demethylation, indicating successful on-target activity. These findings suggest that TDG may provide critical functions specific to cancer cells that make it a highly suitable anti-melanoma drug target. By potentially disrupting both DNA repair and the epigenetic state, targeting TDG may represent a completely new approach to melanoma therapy.
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http://dx.doi.org/10.1038/s41388-018-0640-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563616PMC
May 2019

Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing.

Oncotarget 2018 Jan 19;9(4):4758-4772. Epub 2017 Dec 19.

National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA.

Drug repurposing approaches have the potential advantage of facilitating rapid and cost-effective development of new therapies. Particularly, the repurposing of drugs with known safety profiles in children could bypass or streamline toxicity studies. We employed a phenotypic screening paradigm on a panel of well-characterized cell lines derived from pediatric solid tumors against a collection of ∼3,800 compounds spanning approved drugs and investigational agents. Specifically, we employed titration-based screening where compounds were tested at multiple concentrations for their effect on cell viability. Molecular and cellular target enrichment analysis indicated that numerous agents across different therapeutic categories and modes of action had an antiproliferative effect, notably antiparasitic/protozoal drugs with non-classic antineoplastic activity. Focusing on active compounds with dosing and safety information in children according to the Children's Pharmacy Collaborative database, we identified compounds with therapeutic potential through further validation using 3D tumor spheroid models. Moreover, we show that antiparasitic agents induce cell death apoptosis induction. This study demonstrates that our screening platform enables the identification of chemical agents with cytotoxic activity in pediatric cancer cell lines of which many have known safety/toxicity profiles in children. These agents constitute attractive candidates for efficacy studies in pre-clinical models of pediatric solid tumors.
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http://dx.doi.org/10.18632/oncotarget.23462DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797010PMC
January 2018

Highly predictive and interpretable models for PAMPA permeability.

Bioorg Med Chem 2017 02 31;25(3):1266-1276. Epub 2016 Dec 31.

National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Bethesda, MD 20892, USA. Electronic address:

Cell membrane permeability is an important determinant for oral absorption and bioavailability of a drug molecule. An in silico model predicting drug permeability is described, which is built based on a large permeability dataset of 7488 compound entries or 5435 structurally unique molecules measured by the same lab using parallel artificial membrane permeability assay (PAMPA). On the basis of customized molecular descriptors, the support vector regression (SVR) model trained with 4071 compounds with quantitative data is able to predict the remaining 1364 compounds with the qualitative data with an area under the curve of receiver operating characteristic (AUC-ROC) of 0.90. The support vector classification (SVC) model trained with half of the whole dataset comprised of both the quantitative and the qualitative data produced accurate predictions to the remaining data with the AUC-ROC of 0.88. The results suggest that the developed SVR model is highly predictive and provides medicinal chemists a useful in silico tool to facilitate design and synthesis of novel compounds with optimal drug-like properties, and thus accelerate the lead optimization in drug discovery.
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http://dx.doi.org/10.1016/j.bmc.2016.12.049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291813PMC
February 2017

Prediction of hERG Liability - Using SVM Classification, Bootstrapping and Jackknifing.

Mol Inform 2017 04 21;36(4). Epub 2016 Dec 21.

National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Bethesda, MD 20892, USA.

Drug-induced QT prolongation leads to life-threatening cardiotoxicity, mostly through blockage of the human ether-à-go-go-related gene (hERG) encoded potassium ion (K ) channels. The hERG channel is one of the most important antitargets to be addressed in the early stage of drug discovery process, in order to avoid more costly failures in the development phase. Using a thallium flux assay, 4,323 molecules were screened for hERG channel inhibition in a quantitative high throughput screening (qHTS) format. Here, we present support vector classification (SVC) models of hERG channel inhibition with the averaged area under the receiver operator characteristics curve (AUC-ROC) of 0.93 for the tested compounds. Both Jackknifing and bootstrapping have been employed to rebalance the heavily biased training datasets, and the impact of these two under-sampling rebalance methods on the performance of the predictive models is discussed. Our results indicated that the rebalancing techniques did not enhance the predictive power of the resulting models; instead, adoption of optimal cutoffs could restore the desirable balance of sensitivity and specificity of the binary classifiers. In an external validation set of 66 drug molecules, the SVC model exhibited an AUC-ROC of 0.86, further demonstrating the utility of this modeling approach to predict hERG liabilities.
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http://dx.doi.org/10.1002/minf.201600126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382096PMC
April 2017

A High-Throughput Screen Identifies 2,9-Diazaspiro[5.5]Undecanes as Inducers of the Endoplasmic Reticulum Stress Response with Cytotoxic Activity in 3D Glioma Cell Models.

PLoS One 2016 29;11(8):e0161486. Epub 2016 Aug 29.

National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161486PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5003374PMC
August 2017

High-throughput matrix screening identifies synergistic and antagonistic antimalarial drug combinations.

Sci Rep 2015 Sep 25;5:13891. Epub 2015 Sep 25.

Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD.

Drug resistance in Plasmodium parasites is a constant threat. Novel therapeutics, especially new drug combinations, must be identified at a faster rate. In response to the urgent need for new antimalarial drug combinations we screened a large collection of approved and investigational drugs, tested 13,910 drug pairs, and identified many promising antimalarial drug combinations. The activity of known antimalarial drug regimens was confirmed and a myriad of new classes of positively interacting drug pairings were discovered. Network and clustering analyses reinforced established mechanistic relationships for known drug combinations and identified several novel mechanistic hypotheses. From eleven screens comprising >4,600 combinations per parasite strain (including duplicates) we further investigated interactions between approved antimalarials, calcium homeostasis modulators, and inhibitors of phosphatidylinositide 3-kinases (PI3K) and the mammalian target of rapamycin (mTOR). These studies highlight important targets and pathways and provide promising leads for clinically actionable antimalarial therapy.
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http://dx.doi.org/10.1038/srep13891DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585899PMC
September 2015

Discovery of NCT-501, a Potent and Selective Theophylline-Based Inhibitor of Aldehyde Dehydrogenase 1A1 (ALDH1A1).

J Med Chem 2015 Aug 24;58(15):5967-78. Epub 2015 Jul 24.

†National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.

Aldehyde dehydrogenases (ALDHs) metabolize reactive aldehydes and possess important physiological and toxicological functions in areas such as CNS, metabolic disorders, and cancers. Increased ALDH (e.g., ALDH1A1) gene expression and catalytic activity are vital biomarkers in a number of malignancies and cancer stem cells, highlighting the need for the identification and development of small molecule ALDH inhibitors. A new series of theophylline-based analogs as potent ALDH1A1 inhibitors is described. The optimization of hits identified from a quantitative high throughput screening (qHTS) campaign led to analogs with improved potency and early ADME properties. This chemotype exhibits highly selective inhibition against ALDH1A1 over ALDH3A1, ALDH1B1, and ALDH2 isozymes as well as other dehydrogenases such as HPGD and HSD17β4. Moreover, the pharmacokinetic evaluation of selected analog 64 (NCT-501) is also highlighted.
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http://dx.doi.org/10.1021/acs.jmedchem.5b00577DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5185321PMC
August 2015

Synthesis and structure-activity relationship studies of N-benzyl-2-phenylpyrimidin-4-amine derivatives as potent USP1/UAF1 deubiquitinase inhibitors with anticancer activity against nonsmall cell lung cancer.

J Med Chem 2014 Oct 17;57(19):8099-110. Epub 2014 Sep 17.

National Center for Advancing Translational Sciences, National Institutes of Health , 9800 Medical Center Drive, Rockville, Maryland 20850, United States.

Deregulation of ubiquitin conjugation or deconjugation has been implicated in the pathogenesis of many human diseases including cancer. The deubiquitinating enzyme USP1 (ubiquitin-specific protease 1), in association with UAF1 (USP1-associated factor 1), is a known regulator of DNA damage response and has been shown as a promising anticancer target. To further evaluate USP1/UAF1 as a therapeutic target, we conducted a quantitative high throughput screen of >400000 compounds and subsequent medicinal chemistry optimization of small molecules that inhibit the deubiquitinating activity of USP1/UAF1. Ultimately, these efforts led to the identification of ML323 (70) and related N-benzyl-2-phenylpyrimidin-4-amine derivatives, which possess nanomolar USP1/UAF1 inhibitory potency. Moreover, we demonstrate a strong correlation between compound IC50 values for USP1/UAF1 inhibition and activity in nonsmall cell lung cancer cells, specifically increased monoubiquitinated PCNA (Ub-PCNA) levels and decreased cell survival. Our results establish the druggability of the USP1/UAF1 deubiquitinase complex and its potential as a molecular target for anticancer therapies.
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http://dx.doi.org/10.1021/jm5010495DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191588PMC
October 2014

Genomic and protein expression analysis reveals flap endonuclease 1 (FEN1) as a key biomarker in breast and ovarian cancer.

Mol Oncol 2014 Oct 13;8(7):1326-38. Epub 2014 May 13.

Department of Oncology, Nottingham University Hospitals, Nottingham NG51PB, UK; Academic Unit of Oncology, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham NG51PB, UK. Electronic address:

FEN1 has key roles in Okazaki fragment maturation during replication, long patch base excision repair, rescue of stalled replication forks, maintenance of telomere stability and apoptosis. FEN1 may be dysregulated in breast and ovarian cancers and have clinicopathological significance in patients. We comprehensively investigated FEN1 mRNA expression in multiple cohorts of breast cancer [training set (128), test set (249), external validation (1952)]. FEN1 protein expression was evaluated in 568 oestrogen receptor (ER) negative breast cancers, 894 ER positive breast cancers and 156 ovarian epithelial cancers. FEN1 mRNA overexpression was highly significantly associated with high grade (p = 4.89 × 10(-57)), high mitotic index (p = 5.25 × 10(-28)), pleomorphism (p = 6.31 × 10(-19)), ER negative (p = 9.02 × 10(-35)), PR negative (p = 9.24 × 10(-24)), triple negative phenotype (p = 6.67 × 10(-21)), PAM50.Her2 (p = 5.19 × 10(-13)), PAM50. Basal (p = 2.7 × 10(-41)), PAM50.LumB (p = 1.56 × 10(-26)), integrative molecular cluster 1 (intClust.1) (p = 7.47 × 10(-12)), intClust.5 (p = 4.05 × 10(-12)) and intClust. 10 (p = 7.59 × 10(-38)) breast cancers. FEN1 mRNA overexpression is associated with poor breast cancer specific survival in univariate (p = 4.4 × 10(-16)) and multivariate analysis (p = 9.19 × 10(-7)). At the protein level, in ER positive tumours, FEN1 overexpression remains significantly linked to high grade, high mitotic index and pleomorphism (ps < 0.01). In ER negative tumours, high FEN1 is significantly associated with pleomorphism, tumour type, lymphovascular invasion, triple negative phenotype, EGFR and HER2 expression (ps < 0.05). In ER positive as well as in ER negative tumours, FEN1 protein overexpression is associated with poor survival in univariate and multivariate analysis (ps < 0.01). In ovarian epithelial cancers, similarly, FEN1 overexpression is associated with high grade, high stage and poor survival (ps < 0.05). We conclude that FEN1 is a promising biomarker in breast and ovarian epithelial cancer.
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http://dx.doi.org/10.1016/j.molonc.2014.04.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4690463PMC
October 2014

Inhibition of HERG potassium channels by domiphen bromide and didecyl dimethylammonium bromide.

Eur J Pharmacol 2014 Aug 15;737:202-9. Epub 2014 May 15.

Key Laboratory of Regenerative Biology, Guangzhou Institute of Biomedicine and Health, Chinese Academy of Sciences, Kaiyuan Road 190, Guangzhou Science Park, Guangzhou 510530, China. Electronic address:

Domiphen bromide and didecyl dimethylammonium bromide were widely used environmental chemicals with potent activity on blockade of human ether-a-go-go related gene (HERG) channels. But the mechanism of their action is not clear. The kinetics of block of HERG channels by domiphen bromide and didecyl dimethylammonium bromide was studied in order to characterize the inhibition of HERG currents by these quaternary ammonium compounds (QACs). Domiphen bromide and didecyl dimethylammonium bromide inhibited HERG channel currents in a dose-dependent manner with IC50 values of 9nM and 5nM, respectively. Block of HERG channel by domiphen bromide and didecyl dimethylammonium bromide was voltage-dependent and use-dependent. Domiphen bromide and didecyl dimethylammonium bromide caused substantial negative shift of the activation curves, accelerated activated process, but had no effects on the deactivation and reactivation processes. The docking models implied that these two compounds bound to PAS domain of HERG channels and inhibited its function. Our data demonstrated that domiphen bromide and didecyl dimethylammonium bromide blocked the HERG channel with a preference for the activated channel state.
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http://dx.doi.org/10.1016/j.ejphar.2014.05.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4527083PMC
August 2014

Identification of novel PARP inhibitors using a cell-based TDP1 inhibitory assay in a quantitative high-throughput screening platform.

DNA Repair (Amst) 2014 Sep 29;21:177-82. Epub 2014 Apr 29.

Developmental Therapeutics Branch, Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States. Electronic address:

Anti-cancer topoisomerase I (Top1) inhibitors (camptothecin and its derivatives irinotecan and topotecan, and indenoisoquinolines) induce lethal DNA lesions by stabilizing Top1-DNA cleavage complex (Top1cc). These lesions are repaired by parallel repair pathways including the tyrosyl-DNA phosphodiesterase 1 (TDP1)-related pathway and homologous recombination. As TDP1-deficient cells in vertebrates are hypersensitive to Top1 inhibitors, small molecules inhibiting TDP1 should augment the cytotoxicity of Top1 inhibitors. We developed a cell-based high-throughput screening assay for the discovery of inhibitors for human TDP1 using a TDP1-deficient chicken DT40 cell line (TDP1-/-) complemented with human TDP1 (hTDP1). Any compounds showing a synergistic effect with the Top1 inhibitor camptothecin (CPT) in hTDP1 cells should either be a TDP1-related pathway inhibitor or an inhibitor of alternate repair pathways for Top1cc. We screened the 400,000-compound Small Molecule Library Repository (SMLR, NIH Molecular Libraries) against hTDP1 cells in the absence or presence of CPT. After confirmation in a secondary screen using both hTDP1 and TDP1-/- cells in the absence or presence of CPT, five compounds were confirmed as potential TDP1 pathway inhibitors. All five compounds showed synergistic effect with CPT in hTDP1 cells, but not in TDP1-/- cells, indicating that the compounds inhibited a TDP1-related repair pathway. Yet, in vitro gel-based assay revealed that the five compounds did not inhibit TDP1 catalytic activity directly. We tested the compounds for their ability to inhibit poly(ADP-ribose)polymerase (PARP) because PARP inhibitors are known to potentiate the cytotoxicity of CPT by inhibiting the recruitment of TDP1 to Top1cc. Accordingly, we found that the five compounds inhibit catalytic activity of PARP by ELISA and Western blotting. We identified the most potent compound (Cpd1) that offers characteristic close to veliparib, a leading clinical PARP inhibitor. Cpd1 may represent a new scaffold for the development of PARP inhibitors.
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http://dx.doi.org/10.1016/j.dnarep.2014.03.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125495PMC
September 2014

A selective USP1-UAF1 inhibitor links deubiquitination to DNA damage responses.

Nat Chem Biol 2014 Apr 16;10(4):298-304. Epub 2014 Feb 16.

Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, USA.

Protein ubiquitination and deubiquitination are central to the control of a large number of cellular pathways and signaling networks in eukaryotes. Although the essential roles of ubiquitination have been established in the eukaryotic DNA damage response, the deubiquitination process remains poorly defined. Chemical probes that perturb the activity of deubiquitinases (DUBs) are needed to characterize the cellular function of deubiquitination. Here we report ML323 (2), a highly potent inhibitor of the USP1-UAF1 deubiquitinase complex with excellent selectivity against human DUBs, deSUMOylase, deneddylase and unrelated proteases. Using ML323, we interrogated deubiquitination in the cellular response to UV- and cisplatin-induced DNA damage and revealed new insights into the requirement of deubiquitination in the DNA translesion synthesis and Fanconi anemia pathways. Moreover, ML323 potentiates cisplatin cytotoxicity in non-small cell lung cancer and osteosarcoma cells. Our findings point to USP1-UAF1 as a key regulator of the DNA damage response and a target for overcoming resistance to the platinum-based anticancer drugs.
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http://dx.doi.org/10.1038/nchembio.1455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4144829PMC
April 2014

Pyrido[2,3-d]pyrimidines: discovery and preliminary SAR of a novel series of DYRK1B and DYRK1A inhibitors.

Bioorg Med Chem Lett 2013 Dec 1;23(24):6610-5. Epub 2013 Nov 1.

Discovery Chemistry, Hoffmann-La Roche Inc., pRED, Pharma Research & Early Development, 340 Kingsland Street, Nutley, NJ 07110, USA.

DYRK1B is a kinase over-expressed in certain cancer cells (including colon, ovarian, pancreatic, etc.). Recent publications have demonstrated inhibition of DYRK1B could be an attractive target for cancer therapy. From a data-mining effort, the team has discovered analogues of pyrido[2,3-d]pyrimidines as potent enantio-selective inhibitors of DYRK1B. Cells treated with a tool compound from this series showed the same cellular effects as down regulation of DYRK1B with siRNA. Such effects are consistent with the proposed mechanism of action. Progress of the SAR study is presented.
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http://dx.doi.org/10.1016/j.bmcl.2013.10.055DOI Listing
December 2013

Disrupting malaria parasite AMA1-RON2 interaction with a small molecule prevents erythrocyte invasion.

Nat Commun 2013 ;4:2261

Laboratory of Malaria and Vector Research, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20852, USA.

Plasmodium falciparum resistance to artemisinin derivatives, the first-line antimalarial drug, drives the search for new classes of chemotherapeutic agents. Current discovery is primarily directed against the intracellular forms of the parasite. However, late schizont-infected red blood cells (RBCs) may still rupture and cause disease by sequestration; consequently targeting invasion may reduce disease severity. Merozoite invasion of RBCs requires interaction between two parasite proteins AMA1 and RON2. Here we identify the first inhibitor of this interaction that also blocks merozoite invasion in genetically distinct parasites by screening a library of over 21,000 compounds. We demonstrate that this inhibition is mediated by the small molecule binding to AMA1 and blocking the formation of AMA1-RON complex. Electron microscopy confirms that the inhibitor prevents junction formation, a critical step in invasion that results from AMA1-RON2 binding. This study uncovers a strategy that will allow for highly effective combination therapies alongside existing antimalarial drugs.
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http://dx.doi.org/10.1038/ncomms3261DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3755449PMC
February 2014

Are hERG channel blockers also phospholipidosis inducers?

Bioorg Med Chem Lett 2013 Aug 20;23(16):4587-90. Epub 2013 Jun 20.

National Center for Advancing Translational Sciences, National Institutes of Health (NIH), 9800 Medical Center Drive, Bethesda, Rockville, MD 20892, USA.

Both pharmacophore models of the human ether-à-go-go-related gene (hERG) channel blockers and phospholipidosis (PLD) inducers contain a hydrophobic moiety and a hydrophilic motif/positively charged center, so it is interesting to investigate the overlap between the ligand chemical spaces of both targets. We have assayed over 4000 non-redundant drug-like compounds for both their hERG inhibitory activity and PLD inducing potential in a quantitative high throughput screening (qHTS) format. Seventy-seven percent of PLD inducing compounds identified from the screening were also found to be hERG channel blockers, and 96.9% of the dually active compounds were positively charged. Among the 48 compounds that induced PLD without inhibiting hERG channel, 24 compounds (50.0%) carried steroidal structures. According to our results, hERG channel blockers and PLD inducers share a large chemical space. In addition, a positively charged hERG channel blocker will most likely induce PLD, while a steroid PLD inducer is less likely a hERG channel blocker.
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http://dx.doi.org/10.1016/j.bmcl.2013.06.034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3736554PMC
August 2013

Identification of potent Yes1 kinase inhibitors using a library screening approach.

Bioorg Med Chem Lett 2013 Aug 29;23(15):4398-403. Epub 2013 May 29.

Basic Science Program, SAIC-Frederick Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, United States.

Yes1 kinase has been implicated as a potential therapeutic target in a number of cancers including melanomas, breast cancers, and rhabdomyosarcomas. Described here is the development of a robust and miniaturized biochemical assay for Yes1 kinase that was applied in a high throughput screen (HTS) of kinase-focused small molecule libraries. The HTS provided 144 (17% hit rate) small molecule compounds with IC₅₀ values in the sub-micromolar range. Three of the most potent Yes1 inhibitors were then examined in a cell-based assay for inhibition of cell survival in rhabdomyosarcoma cell lines. Homology models of Yes1 were generated in active and inactive conformations, and docking of inhibitors supports binding to the active conformation (DFG-in) of Yes1. This is the first report of a large high throughput enzymatic activity screen for identification of Yes1 kinase inhibitors, thereby elucidating the polypharmacology of a variety of small molecules and clinical candidates.
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http://dx.doi.org/10.1016/j.bmcl.2013.05.072DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3769177PMC
August 2013

Genomic and functional characterizations of phosphodiesterase subtype 4D in human cancers.

Proc Natl Acad Sci U S A 2013 Apr 27;110(15):6109-14. Epub 2013 Mar 27.

Division of Hematology/Oncology, Cedars-Sinai Medical Center, University of California School of Medicine, Los Angeles, CA 90048, USA.

Discovery of cancer genes through interrogation of genomic dosage is one of the major approaches in cancer research. In this study, we report that phosphodiesterase subtype 4D (PDE4D) gene was homozygously deleted in 198 cases of 5,569 primary solid tumors (3.56%), with most being internal microdeletions. Unexpectedly, the microdeletions did not result in loss of their gene products. Screening PDE4D expression in 11 different types of primary tumor samples (n = 165) with immunohistochemistry staining revealed that its protein levels were up-regulated compared with corresponding nontransformed tissues. Importantly, depletion of endogenous PDE4D with three independent shRNAs caused apoptosis and growth inhibition in multiple types of cancer cells, including breast, lung, ovary, endometrium, gastric, and melanoma, which could be rescued by reexpression of PDE4D. We further showed that antitumor events triggered by PDE4D suppression were lineage-dependently associated with Bcl-2 interacting mediator of cell death (BIM) induction and microphthalmia-associated transcription factor (MITF) down-regulation. Furthermore, ectopic expression of the PDE4D short isoform, PDE4D2, enhanced the proliferation of cancer cells both in vitro and in vivo. Moreover, treatment of cancer cells with a unique specific PDE4D inhibitor, 26B, triggered massive cell death and growth retardation. Notably, these antineoplastic effects induced by either shRNAs or small molecule occurred preferentially in cancer cells but not in nonmalignant epithelial cells. These results suggest that although targeted by genomic homozygous microdeletions, PDE4D functions as a tumor-promoting factor and represents a unique targetable enzyme of cancer cells.
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http://dx.doi.org/10.1073/pnas.1218206110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3625360PMC
April 2013

Prediction of Cytochrome P450 Profiles of Environmental Chemicals with QSAR Models Built from Drug-like Molecules.

Mol Inform 2012 Nov 11;31(11-12):783-792. Epub 2012 Oct 11.

National Center for Advancing Translational Sciences, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA.

The human cytochrome P450 (CYP) enzyme family is involved in the biotransformation of many xenobiotics. As part of the U.S. Tox21 Phase I effort, we profiled the CYP activity of approximately three thousand compounds, primarily those of environmental concern, against human CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4 isoforms in a quantitative high throughput screening (qHTS) format. In order to evaluate the extent to which computational models built from a drug-like library screened in these five CYP assays under the same conditions can accurately predict the outcome of an environmental compound library, five support vector machines (SVM) models built from over 17,000 drug-like compounds were challenged to predict the CYP activities of the Tox21 compound collection. Although a large fraction of the test compounds fall outside of the applicability domain (AD) of the models, as measured by -nearest neighbor (-NN) similarities, the predictions were largely accurate for CYP1A2, CYP2C9, and CYP3A4 ioszymes with area under the receiver operator characteristic curves (AUC-ROC) ranging between 0.82 and 0.84. The lower predictive power of the CYP2C19 model (AUC-ROC = 0.76) is caused by experimental errors and that of the CYP2D6 model (AUC-ROC = 0.76) can be rescued by rebalancing the training data. Our results demonstrate that decomposing molecules into atom types enhanced the coverage of the AD and that computational models built from drug-like molecules can be used to predict the ability of non-drug like compounds to interact with these CYPs.
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http://dx.doi.org/10.1002/minf.201200065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3583379PMC
November 2012

Structure based model for the prediction of phospholipidosis induction potential of small molecules.

J Chem Inf Model 2012 Jul 5;52(7):1798-805. Epub 2012 Jul 5.

National Institutes of Health (NIH) Chemical Genomics Center, NIH, Bethesda, Maryland 20892, United States.

Drug-induced phospholipidosis (PLD), characterized by an intracellular accumulation of phospholipids and formation of concentric lamellar bodies, has raised concerns in the drug discovery community, due to its potential adverse effects. To evaluate the PLD induction potential, 4,161 nonredundant drug-like molecules from the National Institutes of Health Chemical Genomics Center (NCGC) Pharmaceutical Collection (NPC), the Library of Pharmacologically Active Compounds (LOPAC), and the Tocris Biosciences collection were screened in a quantitative high-throughput screening (qHTS) format. The potential of drug-lipid complex formation can be linked directly to the structures of drug molecules, and many PLD inducing drugs were found to share common structural features. Support vector machine (SVM) models were constructed by using customized atom types or Molecular Operating Environment (MOE) 2D descriptors as structural descriptors. Either the compounds from LOPAC or randomly selected from the entire data set were used as the training set. The impact of training data with biased structural features and the impact of molecule descriptors emphasizing whole-molecule properties or detailed functional groups at the atom level on model performance were analyzed and discussed. Rebalancing strategies were applied to improve the predictive power of the SVM models. Using the undersampling method, the consensus model using one-third of the compounds randomly selected from the data set as the training set achieved high accuracy of 0.90 in predicting the remaining two-thirds of the compounds constituting the test set, as measured by the area under the receiver operator characteristic curve (AUC-ROC).
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http://dx.doi.org/10.1021/ci3001875DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3484221PMC
July 2012

Paradigm shift in toxicity testing and modeling.

AAPS J 2012 Sep 20;14(3):473-80. Epub 2012 Apr 20.

Department of Health and Human Services, NIH Chemical Genomics Center, National Institutes of Health, Bethesda, Maryland 20892-3370, USA.

The limitations of traditional toxicity testing characterized by high-cost animal models with low-throughput readouts, inconsistent responses, ethical issues, and extrapolability to humans call for alternative strategies for chemical risk assessment. A new strategy using in vitro human cell-based assays has been designed to identify key toxicity pathways and molecular mechanisms leading to the prediction of an in vivo response. The emergence of quantitative high-throughput screening (qHTS) technology has proved to be an efficient way to decompose complex toxicological end points to specific pathways of targeted organs. In addition, qHTS has made a significant impact on computational toxicology in two aspects. First, the ease of mechanism of action identification brought about by in vitro assays has enhanced the simplicity and effectiveness of machine learning, and second, the high-throughput nature and high reproducibility of qHTS have greatly improved the data quality and increased the quantity of training datasets available for predictive model construction. In this review, the benefits of qHTS routinely used in the US Tox21 program will be highlighted. Quantitative structure-activity relationships models built on traditional in vivo data and new qHTS data will be compared and analyzed. In conjunction with the transition from the pilot phase to the production phase of the Tox21 program, more qHTS data will be made available that will enrich the data pool for predictive toxicology. It is perceivable that new in silico toxicity models based on high-quality qHTS data will achieve unprecedented reliability and robustness, thus becoming a valuable tool for risk assessment and drug discovery.
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http://dx.doi.org/10.1208/s12248-012-9358-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3385826PMC
September 2012
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