Our single-molecule and ensemble data illuminate the mechanism by which Lis1 alters cytoplasmic dynein's mechanical behavior and assists in its wealth of cellular functions.
The wealth of cellular data accumulated for our hit compounds, HKMTI-1-005 in particular, argue for direct effects on cells at the target H3K27me and H3K9me modifications at doses of drug less than or equivalent to growth inhibitory doses.
Progress in understanding the pathogenesis of TSC was propelled in 2002 by the discovery that the TSC proteins inhibit the mammalian Target of Rapamycin (mTOR), a serine/threonine protein kinase, which regulates a wealth of cellular functions including cell growth and survival (Gao et al, 2002; Jaeschke et al, 2002; Tee et al, 2002).
For example, the wealth of existing cellular data for actin regulators has been obtained from a wide range of different organisms and cell types.
The wealth of molecular and cellular data that has been gathered by different research groups over the last several decades makes it one of the best-characterized systems in biology for the study of single-cell signal transduction and behavior.
Although these data provide a wealth of information about cellular processes, they do not elucidate either how these proteins interact or how they are spatially arranged within a complex.
Constraint-based modeling techniques such as flux balance analysis (FBA) have become central to systems biology [ 1, 2], enabling a wealth of informative simulations of cellular metabolism.
Studies of mice with genetic manipulations of DAT [5], [19], [20], [21] and dopamine (DA) receptors [22], [23], [24], [25] have provided a wealth of information about the cellular, pharmacological, physiological and behavioral consequences of these manipulations.
Technological advances, such as the -omics approaches and advanced imaging, have been a major driver to the wealth of new insights into cellular and molecular mechanisms.
Developments in high-throughput technologies have contributed to answer these questions by generating a wealth of data on different cellular components and processes (e.g., transcriptome, proteome, metabolome, fluxome, and protein-protein interaction data).
High-throughput genetic screens in model systems such as Saccharomyces cerevisiae have yielded a wealth of data on the cellular apparatus and biochemical processes involved in tolerance to environmental stresses (Wuster and Madan Babu, 2008).
