The human kinome comprises 538 kinases playing essential functions by catalyzing protein phosphorylation. Annotation of subcellular distribution of the kinome greatly facilitates investigation of normal and disease mechanisms. Here, we present Kinome Atlas (KA), an image-based map of the kinome annotated to 10 cellular compartments. 456 epitope-tagged kinases, representing 85% of the human kinome, were expressed in HeLa cells and imaged by immunofluorescent microscopy under a similar condition. KA revealed kinase family-enriched subcellular localizations, and discovered a collection of new kinase localizations at mitochondria, plasma membrane, extracellular space, and other structures. Furthermore, KA demonstrated the role of liquid-liquid phase separation in formation of kinase condensates. Identification of MOK as a mitochondrial kinase revealed its function in cristae dynamics, respiration, and oxidative stress response. Although limited by possible mislocalization due to overexpression or epitope tagging, this subcellular map of the kinome can be used to refine regulatory mechanisms involving protein phosphorylation.

Using the three-dimensional galaxy local density in a comoving sphere with a radius of the distance to the fifth nearest galaxy for each galaxy, we construct two samples at both extremes of density from the volumelimited Main galaxy sample of the Sixth Data Release of the Sloan Digital Sky Survey (SDSS DR6). It is found that the sample at low density has a higher proportion of faint, blue, and late-type galaxies and a lower proportion of luminous, red, and early-type galaxies than the sample at high density. We also measure the projected local density P 5 , which is computed from the distance to the fifth nearest neighbor within a redshift slice AE1000 km s À1 of each galaxy, and come to the same conclusions. In addition, we note that there is no significant difference between the mean luminosity and the mean colors of two samples (< 1 σ), which is consistent with the conclusion obtained by Deng and colleagues in 2007.

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'} <p>Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse grained and atomistic simulations of transcription factor-DNA recognition, in order to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs μs-timescale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA, and in the presence of both specific and non-specific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and non-specific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to non-specific complexes), that may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.</p>

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