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ABSTRACT: The spliceosome is a mega-Dalton ribonucleoprotein (RNP) assembly that processes primary RNA transcripts, producing functional mRNA. The electron microscopy structures of the native spliceosome and of several spliceosomal subcomplexes are available; however, the spatial arrangement of the latter within the native spliceosome is not known. We designed a computational procedure to efficiently fit thousands of conformers into the spliceosome envelope. Despite the low resolution limitations, we obtained only one model that complies with the available biochemical data. Our model localizes the five small nuclear RNPs (snRNPs) mostly within the large subunit of the native spliceosome, requiring only minor conformation changes. The remaining free volume presumably accommodates additional spliceosomal components. The constituents of the active core of the spliceosome are juxtaposed, forming a continuous surface deep within the large spliceosomal cavity, which provides a sheltered environment for the splicing reaction.
Structure 05/2012; 20(6):1097-106. · 6.35 Impact Factor
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ABSTRACT: The critical assessment of protein interactions (CAPRI) experiment provides a unique opportunity for unbiased assessment of docking procedures. The recent CAPRI targets T29-T42 entailed docking of bound, unbound, and modeled structures, presenting a wide range of prediction difficulty. We submitted accurate predictions for targets T40, T41, and T42, a good prediction for T32 and acceptable predictions for T29 and T34. The accuracy of our docking results generally matched the prediction difficulty; hence, docking of modeled proteins produced less accurate results. However, there were interesting exceptions: an accurate prediction was submitted for the dimer of modeled tetratricopeptide repeat (T42) and only an acceptable prediction for the bound/unbound case T29. The ensembles of docking models produced in the scans included an acceptable or better prediction for every target. We show here that our recently developed postscan reevaluation procedure, which tests propensity and solvation measures of the whole interface and the interface core, successfully distinguished these predictions from false docking models. For enzyme-inhibitor targets, we show that the distance of the interface from the enzyme's centroid ranked high native like docking models. Also, for one case we demonstrate that docking of an ensemble of conformers produced by normal modes analysis can improve the accuracy of the prediction.
Proteins Structure Function and Bioinformatics 11/2010; 78(15):3174-81. · 3.39 Impact Factor
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ABSTRACT: Studies of the structure and dynamics of macromolecular assemblies often involve comparison of low resolution models obtained using different techniques such as electron microscopy or atomic force microscopy. We present new computational tools for comparing (matching) and docking of low resolution structures, based on shape complementarity. The matched or docked objects are represented by three dimensional grids where the value of each grid point depends on its position with regard to the interior, surface or exterior of the object. The grids are correlated using fast Fourier transformations producing either matches of related objects or docking models depending on the details of the grid representations. The procedures incorporate thickening and smoothing of the surfaces of the objects which effectively compensates for differences in the resolution of the matched/docked objects, circumventing the need for resolution modification. The presented matching tool FitEM2EMin successfully fitted electron microscopy structures obtained at different resolutions, different conformers of the same structure and partial structures, ranking correct matches at the top in every case. The differences between the grid representations of the matched objects can be used to study conformation differences or to characterize the size and shape of substructures. The presented low-to-low docking tool FitEM2EMout ranked the expected models at the top.
PLoS ONE 02/2008; 3(10):e3594. · 4.09 Impact Factor
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ABSTRACT: Three networks of intercellular communication can be associated with cytokine secretion; one limited to cells of the immune system (immune cells), one limited to parenchymal cells of organs and tissues (body cells), and one involving interactions between immune and body cells (immune-body interface). These cytokine connections determine the inflammatory response to injury and subsequent healing as well as the biologic consequences of the adaptive immune response to antigens. We informatically probed the cytokine database to uncover the underlying network architecture of the three networks.
We now report that the three cytokine networks are among the densest of complex networks yet studied, and each features a characteristic profile of specific three-cell motifs. Some legitimate cytokine connections are shunned (anti-motifs). Certain immune cells can be paired by their input-output positions in a cytokine architecture tree of five tiers: macrophages (MPhi) and B cells (BC) comprise the first tier; the second tier is formed by T helper 1 (Th1) and T helper 2 (Th2) cells; the third tier includes dendritic cells (DC), mast cells (MAST), Natural Killer T cells (NK-T) and others; the fourth tier is formed by neutrophils (NEUT) and Natural Killer cells (NK); and the Cytotoxic T cell (CTL) stand alone as a fifth tier. The three-cell cytokine motif architecture of immune system cells places the immune system in a super-family that includes social networks and the World Wide Web. Body cells are less clearly stratified, although cells involved in wound healing and angiogenesis are most highly interconnected with immune cells.
Cytokine network architecture creates an innate cell-communication platform that organizes the biologic outcome of antigen recognition and inflammation. Informatics sheds new light on immune-body systems organization.
This article was reviewed by Neil Greenspan, Matthias von Herrath and Anne Cooke.
Biology Direct 02/2006; 1:32. · 4.02 Impact Factor
