Biomedical subjects

Stephen J Haggarty

Publications and source records attributed to Stephen J Haggarty.

13 recordsLinked to original sources

PubMed2024

Dissecting OGT's TPR domain to identify determinants of cellular function.

O-GlcNAc transferase (OGT) is an essential mammalian enzyme that glycosylates myriad intracellular proteins and cleaves the transcriptional coregulator Host Cell Factor 1 to regulate cell cycle processes. Via these catalytic activities as well as noncatalytic protein-protein interactions, OGT maintains cell homeostasis. OGT's tetratricopeptide repeat (TPR) domain is important in substrate recognition, but there is little information on how changing the TPR domain impacts its cellular functions. Here, we investigate how altering OGT's TPR domain impacts cell growth after the endogenous enzyme is deleted. We find that disrupting the TPR residues required for OGT dimerization leads to faster cell growth, whereas truncating the TPR domain slows cell growth. We also find that OGT requires eight of its 13 TPRs to sustain cell viability. OGT-8, like the nonviable shorter OGT variants, is mislocalized and has reduced Ser/Thr glycosylation activity; moreover, its interactions with most of wild-type OGT's binding partners are broadly attenuated. Therefore, although OGT's five N-terminal TPRs are not essential for cell viability, they are required for proper subcellular localization and for mediating many of OGT's protein-protein interactions. Because the viable OGT truncation variant we have identified preserves OGT's essential functions, it may facilitate their identification.

N-Acetylglucosaminyltransferases↗

PubMed2006

The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease.

To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this "Connectivity Map" resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project.

Alzheimer Disease↗

PubMed2006

Revealing complex traits with small molecules and naturally recombinant yeast strains.

Here we demonstrate that natural variants of the yeast Saccharomyces cerevisiae are a model system for the systematic study of complex traits, specifically the response to small molecules. As a complement to artificial knockout collections of S. cerevisiae widely used to study individual gene function, we used 314- and 1932-member libraries of mutant strains generated by meiotic recombination to study the cumulative, quantitative effects of natural mutations on phenotypes induced by 23 small-molecule perturbagens (SMPs). This approach reveals synthetic lethality between SMPs, and genetic mapping studies confirm the involvement of multiple quantitative trait loci in the response to two SMPs that affect respiratory processes. The systematic combination of natural variants of yeast and small molecules that modulate evolutionarily conserved cellular processes can enable a better understanding of the general features of complex traits.

Biosensing Techniques↗

PubMed2005

SpectralNET--an application for spectral graph analysis and visualization.

BACKGROUND: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. RESULTS: Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). CONCLUSION: SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

Algorithms↗

PubMed2005

The principle of complementarity: chemical versus biological space.

Chemical genomics aims to systematically explore the interactions between small molecules and biological systems. These efforts aim to annotate genomes using the language of chemistry, and to provide information-rich profiles of chemical and biological systems. Here, I describe recent conceptual and experimental advances toward the goal of mapping multidimensional chemical and biological descriptor spaces. In doing so, I will focus on the complementary nature of these efforts, the importance of recognizing the distinction between computed versus observed descriptors, and highlight recent 'landmark' examples of small molecules discovered using phenotypic screens. Future computation and experimental advances will be needed to fully realize the goals of chemical genomics. For those willing to consider both local and global properties of chemical and biological space, and to venture into uncharted territory, there promises to be new vistas and principles to be discovered.

Combinatorial Chemistry Techniques↗

PubMed2004

Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips.

The TOR (target of rapamycin) proteins play important roles in nutrient signaling in eukaryotic cells. Rapamycin treatment induces a state reminiscent of the nutrient starvation response, often resulting in growth inhibition. Using a chemical genetic modifier screen, we identified two classes of small molecules, small-molecule inhibitors of rapamycin (SMIRs) and small-molecule enhancers of rapamycin (SMERs), that suppress and augment, respectively, rapamycin's effect in the yeast Saccharomyces cerevisiae. Probing proteome chips with biotinylated SMIRs revealed putative intracellular target proteins, including Tep1p, a homolog of the mammalian PTEN (phosphatase and tensin homologue deleted on chromosome 10) tumor suppressor, and Ybr077cp (Nir1p), a protein of previously unknown function that we show to be a component of the TOR signaling network. Both SMIR target proteins are associated with PI(3,4)P2, suggesting a mechanism of regulation of the TOR pathway involving phosphatidylinositides. Our results illustrate the combined use of chemical genetics and proteomics in biological discovery and map a path for creating useful therapeutics for treating human diseases involving the TOR pathway, such as diabetes and cancer.

Humans↗

PubMed2004

Chemical genomics: probing protein function using small molecules.

Chemical genomics is concerned with the effects of both genetic variation and chemical perturbation on the cellular effects of small molecules. Chemical genomics relies on selecting biological networks for study, such as those represented by different cell types or disease models, in order to build the desired specificity into the experimental design. The most relevant network property for such experiments is the global connectivity of all cellular proteins comprising the functional ensemble, as illustrated by case studies of the evolution of cyclooxygenase inhibitors and heat-shock protein modulators. Recent examples of chemical genomic profiling, particularly of different cell types, highlight the power of carefully planned experimental approaches in chemical genomics. These new approaches demonstrate the use of the genome to find new targets or new modes of biological interaction.

Animals↗

PubMed2004

Mapping chemical space using molecular descriptors and chemical genetics: deacetylase inhibitors.

An objective of chemical genetics is to understand the relationships between the structures of small molecules and their phenotypic effects in intact living systems. We present here the results of a global analysis of a molecular descriptor space constructed using structural descriptors of an aryl 1,3-dioxane-based diversity-oriented synthesis-derived library containing structural biasing elements directed at inhibiting protein deacetylases. Using principal component analysis and three-dimensional visualization, we generated metric space maps with morphological features contributed by different diversity elements within the library. Filtering these maps using phenotypic descriptors derived from measurements of small-molecule activities in an array of cell-based assays revealed different densities of biological activity within specific subspaces. These results provide evidence that certain structural features may be important for conferring potency and selectivity on deacetylase inhibitors with respect to tubulin and histone acetylation. Moreover, these results highlight an example of the importance of using functional measures to assess molecular diversity. Similar analyses of other chemical spaces and activity classes promise to facilitate the development of chemical genetics.

Amidohydrolases↗

PubMed2003

Chemical genomic profiling of biological networks using graph theory and combinations of small molecule perturbations.

Genome-wide measurements of multiple experimental samples yield rich fingerprints for comparison and interpretation. Here, a two-dimensional matrix of the cellular effects of all possible pairwise combinations of 24 small molecules, each with a different structure and bioactivity, was used to profile otherwise isogenic deletion strains of the yeast Saccharomyces cerevisiae. Using principles from graph theory, we derived a discrete model of the data for each strain by encoding the information in the form of a binary adjacency matrix. This matrix was used to construct a graph composed of nodes representing small molecules and edges connecting combinations that inhibited cell cycle progression. Computation of a set of graph theoretic descriptors for each chemical genetic network provided a topological fingerprint that showed genotype-dependent fluctuations. Because the structure of the genetic network determines the structure of the chemical genetic network, multidimensional chemical genomic profiling can be used for the characterization of perturbations in biological networks or the networks themselves. This application of small molecules could be useful for discerning the molecular basis of highly complex biological phenotypes, including those involved in the susceptibility to or etiology of human disease.

Computer Graphics↗

PubMed2003

Domain-selective small-molecule inhibitor of histone deacetylase 6 (HDAC6)-mediated tubulin deacetylation.

Protein acetylation, especially histone acetylation, is the subject of both research and clinical investigation. At least four small-molecule histone deacetylase inhibitors are currently in clinical trials for the treatment of cancer. These and other inhibitors also affect microtubule acetylation. A multidimensional, chemical genetic screen of 7,392 small molecules was used to discover "tubacin," which inhibits alpha-tubulin deacetylation in mammalian cells. Tubacin does not affect the level of histone acetylation, gene-expression patterns, or cell-cycle progression. We provide evidence that class II histone deacetylase 6 (HDAC6) is the intracellular target of tubacin. Only one of the two catalytic domains of HDAC6 possesses tubulin deacetylase activity, and only this domain is bound by tubacin. Tubacin treatment did not affect the stability of microtubules but did decrease cell motility. HDAC6 overexpression disrupted the localization of p58, a protein that mediates binding of Golgi elements to microtubules. Our results highlight the role of alpha-tubulin acetylation in mediating the localization of microtubule-associated proteins. They also suggest that small molecules that selectively inhibit HDAC6-mediated alpha-tubulin deacetylation, a first example of which is tubacin, might have therapeutic applications as antimetastatic and antiangiogenic agents.

3T3 Cells↗

PubMed2003

Small molecule modulation of the human chromatid decatenation checkpoint.

After chromosome replication, the intertwined sister chromatids are disentangled by topoisomerases. The integrity of this process is monitored by the chromatid decatenation checkpoint. Here, we describe small molecule modulators of the human chromatid decatenation checkpoint identified using a cell-based, chemical genetic modifier screen. Similar to 1,2,7-trimethylyxanthine (caffeine), these small molecules suppress the G(2)-phase arrest caused by ICRF-193, a small molecule inhibitor of the enzymatic activity of topoisomerase II. Analysis of specific suppressors, here named suptopins for suppressor of Topoisomerase II inhibition, revealed distinct effects on cell cycle progression, microtubule stability, nucleocytoplasmic transport of cyclin B1, and no effect on the chromatin deacetylation checkpoint induced by trichostatin A. The suptopins provide new molecular tools for dissecting the role of topoisomerases in maintaining genomic stability and determining whether inhibiting the chromatid decatenation checkpoint sensitizes tumor cells to chemotherapeutics.

Acetylation↗

PubMed2003

Chemical genetic modifier screens: small molecule trichostatin suppressors as probes of intracellular histone and tubulin acetylation.

Histone deacetylase (HDAC) inhibitors are being developed as new clinical agents in cancer therapy, in part because they interrupt cell cycle progression in transformed cell lines. To examine cell cycle arrest induced by HDAC inhibitor trichostatin A (TSA), a cytoblot cell-based screen was used to identify small molecule suppressors of this process. TSA suppressors (ITSAs) counteract TSA-induced cell cycle arrest, histone acetylation, and transcriptional activation. Hydroxamic acid-based HDAC inhibitors like TSA and suberoylanilide hydroxamic acid (SAHA) promote acetylation of cytoplasmic alpha-tubulin as well as histones, a modification also suppressed by ITSAs. Although tubulin acetylation appears irrelevant to cell cycle progression and transcription, it may play a role in other cellular processes. Small molecule suppressors such as the ITSAs, available from chemical genetic suppressor screens, may prove to be valuable probes of many biological processes.

Acetylation↗

PubMed2003

Multidimensional chemical genetic analysis of diversity-oriented synthesis-derived deacetylase inhibitors using cell-based assays.

Systematic chemical genetics aims to explore the space representing interactions between small molecules and biological systems. Beyond measuring binding interactions and enzyme inhibition, measuring changes in the activity of proteins in intact signaling networks is necessary. Toward this end, we are partitioning chemical space into regions with different biological activities using a panel of cell-based assays and small molecule "chemical genetic modifiers." Herein, we report on the use of this methodology for the discovery of 617 small molecule inhibitors of histone deacetylases from a multidimensional screen of an encoded, diversity-oriented synthesis library. Following decoding of chemical tags and resynthesis, we demonstrate the selectivity of one inhibitory molecule (tubacin) toward alpha-tubulin deacetylation and another (histacin) toward histone deacetylation. These small molecules will facilitate dissecting the role of acetylation in a variety of cell biological processes.

Acetylation↗