Genstruct Inc.

Cambridge, MA, United States

Genstruct Inc.

Cambridge, MA, United States
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Espelin C.W.,Pfizer | Goldsipe A.,Massachusetts Institute of Technology | Goldsipe A.,MathWorks | Sorger P.K.,Harvard University | And 5 more authors.
Molecular BioSystems | Year: 2010

Rheumatoid arthritis (RA) is a complex, multicellular disease involving a delicate balance between both pro- and anti-inflammatory cytokines which ultimately determines the disease phenotype. The simultaneous presence of multiple signaling molecules, and more specifically their relative levels, potentially influences the efficacy of directed therapies. Using the human U937 monocytic cell line, we generated a self-consistent dataset measuring 50 cytokines and 23 phosphoproteins in the presence of 6 small molecule inhibitors under 15 stimulatory conditions throughout a 24 hour time course. From this dataset, we are able to explore phosphoprotein and cytokine relationships, as well as evaluate the significance of cellular context on the ability of small molecule inhibitors to block inflammatory processes. We show that the ability of a p38 inhibitor to attenuate TNFα production is influenced by local levels of GM-CSF and IL-1β, two cytokines known to be elevated in the joints of RA patients. Within the cell, compensatory mechanisms between signaling pathways are apparent, as selective p38 MAPK inhibition results in the increased phosphorylation of other MAPKs (ERK and JNK) and their downstream substrates (CREB, c-Jun, and ATF-2). Further, we demonstrate that TNFα-neutralizing antibodies have secondary effects on cytokine production, impacting more than just TNFα alone. p38 MAPK inhibition using a small molecule inhibitor also blocks production of anti-inflammatory cytokines including IL-10, IL-1ra and IL-2ra. Collectively, the impact of cell context on TNFα production and unintended blockade of anti-inflammatory cytokines may compromise the efficacy of p38 inhibitors in a clinical setting. The effort described in this work evaluates the effect of inhibitors on multiple endpoints (both intra- and extracellular), under a range of biologically relevant conditions, thus providing a unique means for differentiation of compounds and potential opportunity for improved pharmacological manipulation of disease endpoints in RA. © 2010 The Royal Society of Chemistry.


Robson S.C.,Cancer Research UK Research Institute | Ward L.,University of Warwick | Brown H.,University of Warwick | Turner H.,Pfizer | And 3 more authors.
BMC Genomics | Year: 2011

Background: The transcription factor MYC is a critical regulator of diverse cellular processes, including both replication and apoptosis. Differences in MYC-regulated gene expression responsible for such opposing outcomes in vivo remain obscure. To address this we have examined time-dependent changes in global gene expression in two transgenic mouse models in which MYC activation, in either skin suprabasal keratinocytes or pancreatic islet β-cells, promotes tissue expansion or involution, respectively.Results: Consistent with observed phenotypes, expression of cell cycle genes is increased in both models (albeit enriched in β-cells), as are those involved in cell growth and metabolism, while expression of genes involved in cell differentiation is down-regulated. However, in β-cells, which unlike suprabasal keratinocytes undergo prominent apoptosis from 24 hours, there is up-regulation of genes associated with DNA-damage response and intrinsic apoptotic pathways, including Atr, Arf, Bax and Cycs. In striking contrast, this is not the case for suprabasal keratinocytes, where pro-apoptotic genes such as Noxa are down-regulated and key anti-apoptotic pathways (such as Igf1-Akt) and those promoting angiogenesis are up-regulated. Moreover, dramatic up-regulation of steroid hormone-regulated Kallikrein serine protease family members in suprabasal keratinocytes alone could further enhance local Igf1 actions, such as through proteolysis of Igf1 binding proteins.Conclusions: Activation of MYC causes cell growth, loss of differentiation and cell cycle entry in both β-cells and suprabasal keratinocytes in vivo. Apoptosis, which is confined to β-cells, may involve a combination of a DNA-damage response and downstream activation of pro-apoptotic signalling pathways, including Cdc2a and p19Arf/p53, and downstream targets. Conversely, avoidance of apoptosis in suprabasal keratinocytes may result primarily from the activation of key anti-apoptotic signalling pathways, particularly Igf1-Akt, and induction of an angiogenic response, though intrinsic resistance to induction of p19Arfby MYC in suprabasal keratinocytes may contribute. © 2011 Robson et al; licensee BioMed Central Ltd.


Kumar R.,Glaxosmithkline | Blakemore S.J.,Glaxosmithkline | Ellis C.E.,Glaxosmithkline | Petricoin III E.F.,George Mason University | And 5 more authors.
BMC Genomics | Year: 2010

Background: Inappropriate activation of AKT signaling is a relatively common occurrence in human tumors, and can be caused by activation of components of, or by loss or decreased activity of inhibitors of, this signaling pathway. A novel, pan AKT kinase inhibitor, GSK690693, was developed in order to interfere with the inappropriate AKT signaling seen in these human malignancies. Causal network modeling is a systematic computational analysis that identifies upstream changes in gene regulation that can serve as explanations for observed changes in gene expression. In this study, causal network modeling is employed to elucidate mechanisms of action of GSK690693 that contribute to its observed biological effects. The mechanism of action of GSK690693 was evaluated in multiple human tumor cell lines from different tissues in 2-D cultures and xenografts using RNA expression and phosphoproteomics data. Understanding the molecular mechanism of action of novel targeted agents can enhance our understanding of various biological processes regulated by the intended target and facilitate their clinical development.Results: Causal network modeling on transcriptomic and proteomic data identified molecular networks that are comprised of activated or inhibited mechanisms that could explain observed changes in the sensitive cell lines treated with GSK690693. Four networks common to all cell lines and xenografts tested were identified linking GSK690693 inhibition of AKT kinase activity to decreased proliferation. These networks included increased RB1 activity, decreased MYC activity, decreased TFRC activity, and increased FOXO1/FOXO3 activity.Conclusion: AKT is involved in regulating both cell proliferation and apoptotic pathways; however, the primary effect with GSK690693 appears to be anti-proliferative in the cell lines and xenografts evaluated. Furthermore, these results indicate that anti-proliferative responses to GSK690693 in either 2-D culture or xenograft models may share common mechanisms within and across sensitive cell lines. © 2010 Kumar et al; licensee BioMed Central Ltd.


Richon V.M.,Epizyme | Johnston D.,Epizyme | Sneeringer C.J.,Epizyme | Jin L.,Epizyme | And 5 more authors.
Chemical Biology and Drug Design | Year: 2011

A survey of the human genome was performed to understand the constituency of protein methyltransferases (both protein arginine and lysine methyltransferases) and the relatedness of their catalytic domains. We identified 51 protein lysine methyltransferase proteins based on similarity to the canonical Drosophila Su(var)3-9, enhancer of zeste (E(z)), and trithorax (trx) domain. Disruptor of telomeric silencing-1-like, a known protein lysine methyltransferase, did not fit within the protein lysine methyltransferase family, but did group with the protein arginine methyltransferases, along with 44 other proteins, including the METTL and NOP2/Sun domain family proteins. We show that a representative METTL, METTL11A, demonstrates catalytic activity as a histone methyltransferase. We also solved the co-crystal structures of disruptor of telomeric silencing-1-like with S-adenosylmethionine and S-adenosylhomocysteine bound in its active site. The conformation of both ligands is virtually identical to that found in known protein arginine methyltransferases, METTL and NOP2/Sun domain family proteins and is distinct from that seen in the Drosophila Su(var)3-9, enhancer of zeste (E(z)), and trithorax (trx) domain protein lysine methyltransferases. We have developed biochemical assays for 11 members of the protein methyltransferase target class and have profiled the affinity of three ligands for these enzymes: the common methyl-donating substrate S-adenosylmethionine; the common reaction product S-adenosylhomocysteine; and the natural product sinefungin. The affinity of each of these ligands is mapped onto the family trees of the protein lysine methyltransferases and protein arginine methyltransferases to reveal patterns of ligand recognition by these enzymes. Ligand affinity map for the S-adenosylmethionine (SAM) utilization by human protein methyltransferases. The value of SAM K M is inversely proportional to the diameter of the red spheres associated with each enzyme. © 2011 John Wiley & Sons A/S.


Trademark
Selventa and Genstruct Inc. | Date: 2010-09-09

Computer software, namely, database software for use in biological and chemical research, development, validation and testing in the life sciences field, including primarily the fields of biology, genomics, proteomics and pharmaceuticals and for use in drug discovery, design testing and formulation; data mining software for use in biological and chemical research, development, validation and testing in the life sciences field, including primarily the fields of biology, genomics, proteomics and pharmaceuticals and for use in drug discovery, design testing and formulation; computer software, namely, artificial intelligence and artificial reasoning software for analysis, determination and prediction of biological relationships for use in biological and chemical research, development, validation and testing in the life sciences field, including primarily the fields of biology, genomics, proteomics and pharmaceuticals and for use in drug discovery, design testing and formulation. Biological and chemical research in the life sciences field, including primarily the fields of biology, genomics, proteomics and pharmaceuticals; development, validation and testing of research results and related theories in the life sciences field, including primarily the fields of biology, genomics, proteomics and pharmaceuticals; pharmaceutical drug discovery, design, evaluation and formulation for others; computer services, namely, database design and development services for others and design and development of computer products in the fields of artificial intelligence and artificial reasoning; data mining.

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