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Prahlad T Ram

Publications and source records attributed to Prahlad T Ram.

8 recordsLinked to original sources
PubMed2006

Hypothesis generation in signaling networks.

Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.

Algorithms↗
PubMed2005

Formation of regulatory patterns during signal propagation in a Mammalian cellular network.

We developed a model of 545 components (nodes) and 1259 interactions representing signaling pathways and cellular machines in the hippocampal CA1 neuron. Using graph theory methods, we analyzed ligand-induced signal flow through the system. Specification of input and output nodes allowed us to identify functional modules. Networking resulted in the emergence of regulatory motifs, such as positive and negative feedback and feedforward loops, that process information. Key regulators of plasticity were highly connected nodes required for the formation of regulatory motifs, indicating the potential importance of such motifs in determining cellular choices between homeostasis and plasticity.

Algorithms↗
PubMed2005

The G alpha(o/i)-coupled cannabinoid receptor-mediated neurite outgrowth involves Rap regulation of Src and Stat3.

The study of the signaling pathways regulating neurite outgrowth in culture is important because of their potential role in neuronal differentiation in vivo. We have previously shown that the G alpha(o/i)-coupled CB1 cannabinoid receptor (CB1R) activates Rap1 to induce neurite outgrowth. G alpha(o/i) also activates the Src-Stat3 pathway. Here, we studied the relationship between the G alpha(o/i)-Rap1 and Src-Stat3 pathways and the role of these signaling pathways in CB1R-mediated neurite outgrowth in Neuro-2A cells. The CB1 agonist HU-210 induced pertussis toxin-sensitive Src and Stat3 phosphorylation. Dominant negative (DN) mutants of Src and Stat3 blocked CB1R-induced neurite outgrowth. Constitutively active Rap 1B and Ral-activated Src and CB1R-induced Src phosphorylation was inhibited by Rap1-DN and Ral-DN, indicating that both Rap1 and Ral mediate downstream signaling from G alpha(o/i) for Src activation. Rap1-activated Ral and Ral-DN blocked Rap-induced Src phosphorylation. G alpha(o)-induced Stat3 activation was blocked by Ral-DN, whereas v-Src-induced Stat3 activation was not inhibited by Ral-DN, indicating that the CB1R, through G alpha(o), mediates the sequential activation of Rap1 to Ral to Src to Stat3 in Neuro-2A cells. Downstream of Src, the CB1R also activated Rac1 and JNK, which enhanced CBR1-mediated Stat3 activation. Rac-DN blocked CB1R-induced activation of JNK. Pharmacological inhibition of JNK blocked Src and CB1R activation of Stat3, indicating that Rac and JNK are also involved in CB1R-mediated neurite outgrowth. Overall, this study demonstrated that G alpha(o/i)-coupled CB1R triggers neurite outgrowth in Neuro-2A through the activation of a signaling network containing two pathways that bifurcate at Src and converge at Stat3.

Animals↗
PubMed2005

Exploiting the PI3K/AKT pathway for cancer drug discovery.

Evolving studies with several different targeted therapeutic agents are demonstrating that patients with genomic alterations of the target, including amplification, translocation and mutation, are more likely to respond to the therapy. Recent studies indicate that numerous components of the phosphatidylinositol-3-kinase (PI3K)/AKT pathway are targeted by amplification, mutation and translocation more frequently than any other pathway in cancer patients, with resultant activation of the pathway. This warrants exploiting the PI3K/AKT pathway for cancer drug discovery.

Animals↗
PubMed2004

Quantitative information management for the biochemical computation of cellular networks.

Understanding complex protein networks within cells requires the ability to develop quantitative models and to numerically compute the properties and behavior of the networks. To carry out such computational analysis, it is necessary to use modeling tools and information management systems (IMSs) where the quantitative data, associated to its biological context, can be stored, curated, and reliably retrieved. We have focused on the biochemical computation of cellular interactions and developed an IMS that stores both quantitative information on the cellular components and their interactions, and the basic reactions governing those interactions. This information can be used to construct pathways and eventually large-scale networks. This system, SigPath, is available on the Internet (http://www.sigpath.org). Key features of the approach include (i) the use of background information (for example, names of molecules, aliases, and accession codes) to ease data submission and link this quantitative database with other qualitative databases, (ii) a strategy to allow refinement of information over time by multiple users, (iii) the development of a data representation that stores both qualitative and quantitative information, and (iv) features to assist contributors and users in assembling custom quantitative models from the information stored in the IMS. Currently, models assembled in SigPath can be automatically exported to several computing environments, such as Kinetikit/Genesis, Virtual Cell, Jarnac/JDesigner, and JSim. We anticipate that, when appropriately populated, such a system will be useful for large-scale quantitative studies of cell-signaling networks and other cellular networks. SigPath is distributed under the GNU General Public License.

Animals↗
PubMed2002

MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network.

Intracellular signaling networks receive and process information to control cellular machines. The mitogen-activated protein kinase (MAPK) 1,2/protein kinase C (PKC) system is one such network that regulates many cellular machines, including the cell cycle machinery and autocrine/paracrine factor synthesizing machinery. We used a combination of computational analysis and experiments in mouse NIH-3T3 fibroblasts to understand the design principles of this controller network. We find that the growth factor-stimulated signaling network containing MAPK 1, 2/PKC can operate with one (monostable) or two (bistable) stable states. At low concentrations of MAPK phosphatase, the system exhibits bistable behavior, such that brief stimulus results in sustained MAPK activation. The MAPK-induced increase in the amounts of MAPK phosphatase eliminates the prolonged response capability and moves the network to a monostable state, in which it behaves as a proportional response system responding acutely to stimulus. Thus, the MAPK 1, 2/PKC controller network is flexibly designed, and MAPK phosphatase may be critical for this flexible response.

3T3 Cells↗
PubMed2002

G protein pathways.

The heterotrimeric guanine nucleotide-binding proteins (G proteins) are signal transducers that communicate signals from many hormones, neurotransmitters, chemokines, and autocrine and paracrine factors. The extracellular signals are received by members of a large superfamily of receptors with seven membrane-spanning regions that activate the G proteins, which route the signals to several distinct intracellular signaling pathways. These pathways interact with one another to form a network that regulates metabolic enzymes, ion channels, transporters, and other components of the cellular machinery controlling a broad range of cellular processes, including transcription, motility, contractility, and secretion. These cellular processes in turn regulate systemic functions such as embryonic development, gonadal development, learning and memory, and organismal homeostasis.

Animals↗