J Anthony Wilson

Broad Institute of MIT and Harvard, Cambridge, MA, United States

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Publications (7)43.41 Total impact

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    ABSTRACT: High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.
    Proceedings of the National Academy of Sciences of the United States of America. 07/2014;
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    ABSTRACT: Computational methods for image-based profiling are under active development, but their success hinges on assays that can capture a wide range of phenotypes. We have developed a multiplex cytological profiling assay that "paints the cell" with as many fluorescent markers as possible without compromising our ability to extract rich, quantitative profiles in high throughput. The assay detects seven major cellular components. In a pilot screen of bioactive compounds, the assay detected a range of cellular phenotypes and it clustered compounds with similar annotated protein targets or chemical structure based on cytological profiles. The results demonstrate that the assay captures subtle patterns in the combination of morphological labels, thereby detecting the effects of chemical compounds even though their targets are not stained directly. This image-based assay provides an unbiased approach to characterize compound- and disease-associated cell states to support future probe discovery.
    PLoS ONE 01/2013; 8(12):e80999. · 3.53 Impact Factor
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    ABSTRACT: Using a diverse collection of small molecules we recently found that compound sets from different sources (commercial; academic; natural) have different protein-binding behaviors, and these behaviors correlate with trends in stereochemical complexity for these compound sets. These results lend insight into structural features that synthetic chemists might target when synthesizing screening collections for biological discovery. We report extensive characterization of structural properties and diversity of biological performance for these compounds and expand comparative analyses to include physicochemical properties and three-dimensional shapes of predicted conformers. The results highlight additional similarities and differences between the sets, but also the dependence of such comparisons on the choice of molecular descriptors. Using a protein-binding dataset, we introduce an information-theoretic measure to assess diversity of performance with a constraint on specificity. Rather than relying on finding individual active compounds, this measure allows rational judgment of compound subsets as groups. We also apply this measure to publicly available data from ChemBank for the same compound sets across a diverse group of functional assays. We find that performance diversity of compound sets is relatively stable across a range of property values as judged by this measure, both in protein-binding studies and functional assays. Because building screening collections with improved performance depends on efficient use of synthetic organic chemistry resources, these studies illustrate an important quantitative framework to help prioritize choices made in building such collections.
    Proceedings of the National Academy of Sciences 04/2011; 108(17):6817-22. · 9.81 Impact Factor
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    ABSTRACT: Fragment-based drug discovery (FBDD) has proven to be an effective means of producing high-quality chemical ligands as starting points for drug-discovery pursuits. The increasing number of clinical candidate drugs developed using FBDD approaches is a testament of the efficacy of this approach. The success of fragment-based methods is highly dependent on the identity of the fragment library used for screening. The vast majority of FBDD has centered on the use of sp(2)-rich aromatic compounds. An expanded set of fragments that possess more 3D character would provide access to a larger chemical space of fragments than those currently used. Diversity-oriented synthesis (DOS) aims to efficiently generate a set of molecules diverse in skeletal and stereochemical properties. Molecules derived from DOS have also displayed significant success in the modulation of function of various "difficult" targets. Herein, we describe the application of DOS toward the construction of a unique set of fragments containing highly sp(3)-rich skeletons for fragment-based screening. Using cheminformatic analysis, we quantified the shapes and physical properties of the new 3D fragments and compared them with a database containing known fragment-like molecules.
    Proceedings of the National Academy of Sciences 04/2011; 108(17):6799-804. · 9.81 Impact Factor
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    ABSTRACT: A short and modular synthetic pathway using intramolecular 1,3-dipolar cycloaddition reactions and yielding functionalized isoxazoles, isoxazolines, and isoxazolidines is described. The change in shape of previous compounds and those in this study is quantified and compared using principal moment-of-inertia shape analysis.
    Organic Letters 10/2010; 12(22):5230-3. · 6.14 Impact Factor
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    ABSTRACT: Using a diverse collection of small molecules generated from a variety of sources, we measured protein-binding activities of each individual compound against each of 100 diverse (sequence-unrelated) proteins using small-molecule microarrays. We also analyzed structural features, including complexity, of the small molecules. We found that compounds from different sources (commercial, academic, natural) have different protein-binding behaviors and that these behaviors correlate with general trends in stereochemical and shape descriptors for these compound collections. Increasing the content of sp(3)-hybridized and stereogenic atoms relative to compounds from commercial sources, which comprise the majority of current screening collections, improved binding selectivity and frequency. The results suggest structural features that synthetic chemists can target when synthesizing screening collections for biological discovery. Because binding proteins selectively can be a key feature of high-value probes and drugs, synthesizing compounds having features identified in this study may result in improved performance of screening collections.
    Proceedings of the National Academy of Sciences 10/2010; 107(44):18787-92. · 9.81 Impact Factor
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    ABSTRACT: Despite considerable efforts, description of molecular shape is still largely an unresolved problem. Given the importance of molecular shape in the description of spatial interactions in crystals or ligand-target complexes, this is not a satisfying state. In the current work, we propose a novel application of alpha shapes to the description of the shapes of small molecules. Alpha shapes are parametrized generalizations of the convex hull. For a specific value of alpha, the alpha shape is the geometric dual of the space-filling model of a molecule, with the parameter alpha allowing description of shape in varying degrees of detail. To date, alpha shapes have been used to find macromolecular cavities and to estimate molecular surface areas and volumes. We developed a novel methodology for computing molecular shape characteristics from the alpha shape. In this work, we show that alpha-shape descriptors reveal aspects of molecular shape that are complementary to other shape descriptors and that accord well with chemists' intuition about shape. While our implementation of alpha-shape descriptors is not computationally trivial, we suggest that the additional shape characteristics they provide can be used to improve and complement shape-analysis methods in domains such as crystallography and ligand-target interactions. In this communication, we present a unique methodology for computing molecular shape characteristics from the alpha shape. We first describe details of the alpha-shape calculation, an outline of validation experiments performed, and a discussion of the advantages and challenges we found while implementing this approach. The results show that, relative to known shape calculations, this method provides a high degree of shape resolution with even small changes in atomic coordinates.
    Journal of Chemical Information and Modeling 09/2009; 49(10):2231-41. · 4.30 Impact Factor