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  1. Book: Cell based assays for high throughput screening

    Clemons, Paul A.

    methods and protocols

    (Methods in molecular biology ; 486 ; Springer protocols)

    2009  

    Title variant Cell-based assays for high-throughput screening
    Author's details ed. by Paul A. Clemons
    Series title Methods in molecular biology ; 486
    Springer protocols
    Collection
    Keywords Drug Discovery ; Biological Assay ; Drug Evaluation, Preclinical ; High throughput screening (Drug development) ; Biological assay
    Subject code 615.19
    Language English
    Size X, 218 S. : ill., graph. Darst., 26cm
    Publisher Humana Press
    Publishing place New York, NY
    Publishing country United States
    Document type Book
    HBZ-ID HT015820019
    ISBN 1-603-27544-4 ; 978-1-603-27544-6 ; 9781603275453 ; 1603275452
    Database Catalogue ZB MED Medicine, Health

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  2. Article ; Online: Computational Analyses Connect Small-Molecule Sensitivity to Cellular Features Using Large Panels of Cancer Cell Lines.

    Rees, Matthew G / Seashore-Ludlow, Brinton / Clemons, Paul A

    Methods in molecular biology (Clifton, N.J.)

    2018  Volume 1888, Page(s) 233–254

    Abstract: We recently pioneered several analyses of small-molecule sensitivity data collected from large-scale perturbation of hundreds of cancer cell lines with hundreds of small molecules, with cell viability measured as a readout of compound sensitivity. We ... ...

    Abstract We recently pioneered several analyses of small-molecule sensitivity data collected from large-scale perturbation of hundreds of cancer cell lines with hundreds of small molecules, with cell viability measured as a readout of compound sensitivity. We performed these studies using cancer cell lines previously annotated with cellular, genomic, and basal gene-expression features. By combining small-molecule sensitivity data with these other datasets, we identified new candidate biomarkers of sensitivity, gained insights into small-molecule mechanisms of action, and proposed candidate hypotheses for cancer dependencies (including candidate combination therapies). Nevertheless, given the size of these datasets, we expect that many connections between cellular features and small-molecule sensitivity remain underexplored. In this chapter, we provide a step-by-step account of foundational data-analysis methods underlying our published studies, including working MATLAB code applied to our own public datasets. These procedures will allow others to repeat analyses of our data with new parameters, in additional contexts, and to adapt our procedures to their own datasets.
    MeSH term(s) Antineoplastic Agents/pharmacology ; Cell Line, Tumor ; Cell Survival/drug effects ; Computational Biology/methods ; Databases, Factual ; Drug Discovery/methods ; Drug Resistance, Neoplasm/drug effects ; Drug Resistance, Neoplasm/genetics ; Humans ; Mutation ; Pharmacogenetics/methods ; Small Molecule Libraries
    Chemical Substances Antineoplastic Agents ; Small Molecule Libraries
    Language English
    Publishing date 2018-12-05
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-4939-8891-4_14
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Machine Learning on DNA-Encoded Library Count Data Using an Uncertainty-Aware Probabilistic Loss Function.

    Lim, Katherine S / Reidenbach, Andrew G / Hua, Bruce K / Mason, Jeremy W / Gerry, Christopher J / Clemons, Paul A / Coley, Connor W

    Journal of chemical information and modeling

    2022  Volume 62, Issue 10, Page(s) 2316–2331

    Abstract: DNA-encoded library (DEL) screening and quantitative structure-activity relationship (QSAR) modeling are two techniques used in drug discovery to find novel small molecules that bind a protein target. Applying QSAR modeling to DEL selection data can ... ...

    Abstract DNA-encoded library (DEL) screening and quantitative structure-activity relationship (QSAR) modeling are two techniques used in drug discovery to find novel small molecules that bind a protein target. Applying QSAR modeling to DEL selection data can facilitate the selection of compounds for off-DNA synthesis and evaluation. Such a combined approach has been done recently by training binary classifiers to learn DEL enrichments of aggregated "disynthons" in order to accommodate the sparse and noisy nature of DEL data. However, a binary classification model cannot distinguish between different levels of enrichment, and information is potentially lost during disynthon aggregation. Here, we demonstrate a regression approach to learning DEL enrichments of individual molecules, using a custom negative-log-likelihood loss function that effectively denoises DEL data and introduces opportunities for visualization of learned structure-activity relationships. Our approach explicitly models the Poisson statistics of the sequencing process used in the DEL experimental workflow under a frequentist view. We illustrate this approach on a DEL dataset of 108,528 compounds screened against carbonic anhydrase (CAIX), and a dataset of 5,655,000 compounds screened against soluble epoxide hydrolase (sEH) and SIRT2. Due to the treatment of uncertainty in the data through the negative-log-likelihood loss used during training, the models can ignore low-confidence outliers. While our approach does not demonstrate a benefit for extrapolation to novel structures, we expect our denoising and visualization pipeline to be useful in identifying structure-activity trends and highly enriched pharmacophores in DEL data. Further, this approach to uncertainty-aware regression modeling is applicable to other sparse or noisy datasets where the nature of stochasticity is known or can be modeled; in particular, the Poisson enrichment ratio metric we use can apply to other settings that compare sequencing count data between two experimental conditions.
    MeSH term(s) DNA/chemistry ; Drug Discovery/methods ; Machine Learning ; Small Molecule Libraries/chemistry ; Small Molecule Libraries/pharmacology ; Uncertainty
    Chemical Substances Small Molecule Libraries ; DNA (9007-49-2)
    Language English
    Publishing date 2022-05-10
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.2c00041
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: DNA Barcoding a Complete Matrix of Stereoisomeric Small Molecules.

    Gerry, Christopher J / Wawer, Mathias J / Clemons, Paul A / Schreiber, Stuart L

    Journal of the American Chemical Society

    2019  Volume 141, Issue 26, Page(s) 10225–10235

    Abstract: It is challenging to incorporate stereochemical diversity and topographic complexity into DNA-encoded libraries (DELs) because DEL syntheses cannot fully exploit the capabilities of modern synthetic organic chemistry. Here, we describe the design, ... ...

    Abstract It is challenging to incorporate stereochemical diversity and topographic complexity into DNA-encoded libraries (DELs) because DEL syntheses cannot fully exploit the capabilities of modern synthetic organic chemistry. Here, we describe the design, construction, and validation of DOS-DEL-1, a library of 107 616 DNA-barcoded chiral 2,3-disubsituted azetidines and pyrrolidines. We used stereospecific C-H arylation chemistry to furnish complex scaffolds primed for DEL synthesis, and we developed an improved on-DNA Suzuki reaction to maximize library quality. We then studied both the structural diversity of the library and the physicochemical properties of individual compounds using Tanimoto multifusion similarity analysis, among other techniques. These analyses revealed not only that most DOS-DEL-1 members have "drug-like" properties, but also that the library more closely resembles compound collections derived from diversity synthesis than those from other sources (e.g., commercial vendors). Finally, we performed validation screens against horseradish peroxidase and carbonic anhydrase IX, and we developed a novel, Poisson-based statistical framework to analyze the results. A set of assay positives were successfully translated into potent carbonic anhydrase inhibitors (IC
    MeSH term(s) Carbonic Anhydrase IX/antagonists & inhibitors ; Carbonic Anhydrase IX/metabolism ; DNA/chemistry ; DNA Barcoding, Taxonomic ; Enzyme Inhibitors/chemical synthesis ; Enzyme Inhibitors/chemistry ; Enzyme Inhibitors/pharmacology ; Horseradish Peroxidase/antagonists & inhibitors ; Horseradish Peroxidase/metabolism ; Molecular Structure ; Small Molecule Libraries/chemical synthesis ; Small Molecule Libraries/chemistry ; Small Molecule Libraries/pharmacology ; Stereoisomerism
    Chemical Substances Enzyme Inhibitors ; Small Molecule Libraries ; DNA (9007-49-2) ; Horseradish Peroxidase (EC 1.11.1.-) ; Carbonic Anhydrase IX (EC 4.2.1.1)
    Language English
    Publishing date 2019-06-25
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 3155-0
    ISSN 1520-5126 ; 0002-7863
    ISSN (online) 1520-5126
    ISSN 0002-7863
    DOI 10.1021/jacs.9b01203
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Predicting compound activity from phenotypic profiles and chemical structures.

    Moshkov, Nikita / Becker, Tim / Yang, Kevin / Horvath, Peter / Dancik, Vlado / Wagner, Bridget K / Clemons, Paul A / Singh, Shantanu / Carpenter, Anne E / Caicedo, Juan C

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 1967

    Abstract: Predicting assay results for compounds virtually using chemical structures and phenotypic profiles has the potential to reduce the time and resources of screens for drug discovery. Here, we evaluate the relative strength of three high-throughput data ... ...

    Abstract Predicting assay results for compounds virtually using chemical structures and phenotypic profiles has the potential to reduce the time and resources of screens for drug discovery. Here, we evaluate the relative strength of three high-throughput data sources-chemical structures, imaging (Cell Painting), and gene-expression profiles (L1000)-to predict compound bioactivity using a historical collection of 16,170 compounds tested in 270 assays for a total of 585,439 readouts. All three data modalities can predict compound activity for 6-10% of assays, and in combination they predict 21% of assays with high accuracy, which is a 2 to 3 times higher success rate than using a single modality alone. In practice, the accuracy of predictors could be lower and still be useful, increasing the assays that can be predicted from 37% with chemical structures alone up to 64% when combined with phenotypic data. Our study shows that unbiased phenotypic profiling can be leveraged to enhance compound bioactivity prediction to accelerate the early stages of the drug-discovery process.
    MeSH term(s) Drug Discovery/methods ; Transcriptome ; Biological Assay ; High-Throughput Screening Assays/methods
    Language English
    Publishing date 2023-04-08
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-37570-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells.

    Athanasiadis, Paschalis / Ravikumar, Balaguru / Elliott, Richard J R / Dawson, John C / Carragher, Neil O / Clemons, Paul A / Johanssen, Timothy / Ebner, Daniel / Aittokallio, Tero

    iScience

    2023  Volume 26, Issue 7, Page(s) 107209

    Abstract: Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for ...

    Abstract Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjusted for library size, cellular activity, chemical diversity and availability, and target selectivity. The resulting compound collections cover a wide range of protein targets and biological pathways implicated in various cancers, making them widely applicable to precision oncology. We characterized the compound and target spaces of the virtual libraries, in comparison with a minimal screening library of 1,211 compounds for targeting 1,386 anticancer proteins. In a pilot screening study, we identified patient-specific vulnerabilities by imaging glioma stem cells from patients with glioblastoma (GBM), using a physical library of 789 compounds that cover 1,320 of the anticancer targets. The cell survival profiling revealed highly heterogeneous phenotypic responses across the patients and GBM subtypes.
    Language English
    Publishing date 2023-06-25
    Publishing country United States
    Document type Journal Article
    ISSN 2589-0042
    ISSN (online) 2589-0042
    DOI 10.1016/j.isci.2023.107209
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: DNA Barcoding a Complete Matrix of Stereoisomeric Small Molecules

    Gerry, Christopher J / Wawer, Mathias J / Clemons, Paul A / Schreiber, Stuart L

    Journal of the American Chemical Society. 2019 June 11, v. 141, no. 26

    2019  

    Abstract: It is challenging to incorporate stereochemical diversity and topographic complexity into DNA-encoded libraries (DELs) because DEL syntheses cannot fully exploit the capabilities of modern synthetic organic chemistry. Here, we describe the design, ... ...

    Abstract It is challenging to incorporate stereochemical diversity and topographic complexity into DNA-encoded libraries (DELs) because DEL syntheses cannot fully exploit the capabilities of modern synthetic organic chemistry. Here, we describe the design, construction, and validation of DOS-DEL-1, a library of 107 616 DNA-barcoded chiral 2,3-disubsituted azetidines and pyrrolidines. We used stereospecific C–H arylation chemistry to furnish complex scaffolds primed for DEL synthesis, and we developed an improved on-DNA Suzuki reaction to maximize library quality. We then studied both the structural diversity of the library and the physicochemical properties of individual compounds using Tanimoto multifusion similarity analysis, among other techniques. These analyses revealed not only that most DOS-DEL-1 members have “drug-like” properties, but also that the library more closely resembles compound collections derived from diversity synthesis than those from other sources (e.g., commercial vendors). Finally, we performed validation screens against horseradish peroxidase and carbonic anhydrase IX, and we developed a novel, Poisson-based statistical framework to analyze the results. A set of assay positives were successfully translated into potent carbonic anhydrase inhibitors (IC50 = 20.1–68.7 nM), which confirmed the success of the synthesis and screening procedures. These results establish a strategy to synthesize DELs with scaffold-based stereochemical diversity and complexity that does not require the development of novel DNA-compatible chemistry.
    Keywords DNA barcoding ; Suzuki reaction ; arylation ; carbon-hydrogen bond activation ; carbonate dehydratase ; enzyme inhibitors ; inhibitory concentration 50 ; organic chemistry ; peroxidase ; physicochemical properties ; pyrrolidines ; screening ; stereochemistry ; stereospecificity ; topography
    Language English
    Dates of publication 2019-0611
    Size p. 10225-10235.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 3155-0
    ISSN 1520-5126 ; 0002-7863
    ISSN (online) 1520-5126
    ISSN 0002-7863
    DOI 10.1021/jacs.9b01203
    Database NAL-Catalogue (AGRICOLA)

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  8. Article ; Online: The Use of Informer Sets in Screening: Perspectives on an Efficient Strategy to Identify New Probes.

    Clemons, Paul A / Bittker, Joshua A / Wagner, Florence F / Hands, Allison / Dančík, Vlado / Schreiber, Stuart L / Choudhary, Amit / Wagner, Bridget K

    SLAS discovery : advancing life sciences R & D

    2021  Volume 26, Issue 7, Page(s) 855–861

    Abstract: Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds ... ...

    Abstract Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds tested. Further, low hit rates can make the process inefficient. Sparse coverage of chemical structure or biological activity space can lead to limited success in a primary screen and represents a missed opportunity by virtue of selecting the "wrong" compounds to test. Thus, the choice of screening collections becomes of paramount importance. In this perspective, we discuss the utility of generating "informer sets" for small-molecule discovery, and how this strategy can be leveraged to prioritize probe candidates. While many researchers may assume that informer sets are focused on particular targets (e.g., kinases) or processes (e.g., autophagy), efforts to assemble informer sets based on historical bioactivity or successful human exposure (e.g., repurposing collections) have shown promise as well. Another method for generating informer sets is based on chemical structure, particularly when the compounds have unknown activities and targets. We describe our efforts to screen an informer set representing a collection of 100,000 small molecules synthesized through diversity-oriented synthesis (DOS). This process enables researchers to identify activity early and more extensively screen only a few chemical scaffolds, rather than the entire collection. This elegant and economic outcome is a goal of the informer set approach. Here, we aim not only to shed light on this process, but also to promote the use of informer sets more widely in small-molecule discovery projects.
    MeSH term(s) Drug Discovery/methods ; Drug Evaluation, Preclinical/methods ; Humans ; Small Molecule Libraries ; Structure-Activity Relationship
    Chemical Substances Small Molecule Libraries
    Language English
    Publishing date 2021-06-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2885123-7
    ISSN 2472-5560 ; 2472-5552
    ISSN (online) 2472-5560
    ISSN 2472-5552
    DOI 10.1177/24725552211019410
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Mapping the landscape of genetic dependencies in chordoma.

    Sharifnia, Tanaz / Wawer, Mathias J / Goodale, Amy / Lee, Yenarae / Kazachkova, Mariya / Dempster, Joshua M / Muller, Sandrine / Levy, Joan / Freed, Daniel M / Sommer, Josh / Kalfon, Jérémie / Vazquez, Francisca / Hahn, William C / Root, David E / Clemons, Paul A / Schreiber, Stuart L

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 1933

    Abstract: Identifying the spectrum of genes required for cancer cell survival can reveal essential cancer circuitry and therapeutic targets, but such a map remains incomplete for many cancer types. We apply genome-scale CRISPR-Cas9 loss-of-function screens to map ... ...

    Abstract Identifying the spectrum of genes required for cancer cell survival can reveal essential cancer circuitry and therapeutic targets, but such a map remains incomplete for many cancer types. We apply genome-scale CRISPR-Cas9 loss-of-function screens to map the landscape of selectively essential genes in chordoma, a bone cancer with few validated targets. This approach confirms a known chordoma dependency, TBXT (T; brachyury), and identifies a range of additional dependencies, including PTPN11, ADAR, PRKRA, LUC7L2, SRRM2, SLC2A1, SLC7A5, FANCM, and THAP1. CDK6, SOX9, and EGFR, genes previously implicated in chordoma biology, are also recovered. We find genomic and transcriptomic features that predict specific dependencies, including interferon-stimulated gene expression, which correlates with ADAR dependence and is elevated in chordoma. Validating the therapeutic relevance of dependencies, small-molecule inhibitors of SHP2, encoded by PTPN11, have potent preclinical efficacy against chordoma. Our results generate an emerging map of chordoma dependencies to enable biological and therapeutic hypotheses.
    MeSH term(s) Humans ; Chordoma/genetics ; Bone Neoplasms/genetics ; Bone Neoplasms/metabolism ; Genes, Essential ; Gene Expression Profiling ; Transcriptome ; Cell Line, Tumor ; DNA-Binding Proteins/metabolism ; Apoptosis Regulatory Proteins/genetics ; DNA Helicases/metabolism
    Chemical Substances THAP1 protein, human ; DNA-Binding Proteins ; Apoptosis Regulatory Proteins ; FANCM protein, human (EC 3.6.1.-) ; DNA Helicases (EC 3.6.4.-)
    Language English
    Publishing date 2023-04-06
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-37593-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: DNA-encoded library-enabled discovery of proximity-inducing small molecules.

    Mason, Jeremy W / Chow, Yuen Ting / Hudson, Liam / Tutter, Antonin / Michaud, Gregory / Westphal, Matthias V / Shu, Wei / Ma, Xiaolei / Tan, Zher Yin / Coley, Connor W / Clemons, Paul A / Bonazzi, Simone / Berst, Frédéric / Briner, Karin / Liu, Shuang / Zécri, Frédéric J / Schreiber, Stuart L

    Nature chemical biology

    2023  Volume 20, Issue 2, Page(s) 170–179

    Abstract: Small molecules that induce protein-protein associations represent powerful tools to modulate cell circuitry. We sought to develop a platform for the direct discovery of compounds able to induce association of any two preselected proteins, using the E3 ... ...

    Abstract Small molecules that induce protein-protein associations represent powerful tools to modulate cell circuitry. We sought to develop a platform for the direct discovery of compounds able to induce association of any two preselected proteins, using the E3 ligase von Hippel-Lindau (VHL) and bromodomains as test systems. Leveraging the screening power of DNA-encoded libraries (DELs), we synthesized ~1 million DNA-encoded compounds that possess a VHL-targeting ligand, a variety of connectors and a diversity element generated by split-and-pool combinatorial chemistry. By screening our DEL against bromodomains in the presence and absence of VHL, we could identify VHL-bound molecules that simultaneously bind bromodomains. For highly barcode-enriched library members, ternary complex formation leading to bromodomain degradation was confirmed in cells. Furthermore, a ternary complex crystal structure was obtained for our most enriched library member with BRD4
    MeSH term(s) Von Hippel-Lindau Tumor Suppressor Protein/chemistry ; Von Hippel-Lindau Tumor Suppressor Protein/metabolism ; Nuclear Proteins/metabolism ; Transcription Factors ; Ubiquitin-Protein Ligases/metabolism ; DNA
    Chemical Substances Von Hippel-Lindau Tumor Suppressor Protein (EC 2.3.2.27) ; Nuclear Proteins ; Transcription Factors ; Ubiquitin-Protein Ligases (EC 2.3.2.27) ; DNA (9007-49-2)
    Language English
    Publishing date 2023-11-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2202962-X
    ISSN 1552-4469 ; 1552-4450
    ISSN (online) 1552-4469
    ISSN 1552-4450
    DOI 10.1038/s41589-023-01458-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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