data mining text mining, e.g.: structures at specific resolution structures by negative staining...

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Data Mining Text mining, e.g.: • Structures at specific resolution • Structures by negative staining • Structures by vitrification Mining structural data, e.g.: • Segmentation • 3D shape recognition • Secondary structure recognition • Fold modules recognition

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Data Mining

Text mining, e.g.: • Structures at specific resolution• Structures by negative staining• Structures by vitrification

Mining structural data, e.g.: • Segmentation• 3D shape recognition• Secondary structure recognition• Fold modules recognition

Goals

• Atomic scale model of a cell• Atomic models of interacting complexes• Conformational dynamics

Difficulties

• Range of size• Range of resolution• Range of complexity

Towards the atomic model of a cell

Wolfgang Baumeister

Segmentation

Niels Volkmann

Actin mesh & aldolase

Volkmann, 2002, JSB 138:123

Atomic models of complexes

15 Å 10 Å 5 Å

Helix-hunter

Situs Wah Chiu

sheetsHelix orientation

SCOP: 1.65 released December 2003.CATH: 2.5.1: Released January 2004

If no structure available:

Atomic models of complexes

Alasdair Steven

10 Å structure of HBV

Fitting of FAB

Helix orientation: the fold

3D cryo EM4.5 Å resolution

Mitsuoka et al. J. Struct. Biol. (1999)

QuickTime™ and aVideo decompressor

are needed to see this picture.

De Groot et al., J. Mol. Biol (2000)

The directionality of the helices was determined by collecting the best-ftting orientations resulting from a search through the 3D experimental map for a large number of -helical fragments.

How to describe protein motion without sequence and atomic

coordinatesThe 3D continuous object is decomposed into a set of Voronoi cells that approximate its shape and density distribution. The anisotropic elastic network theory allows the thermal fluctuations to be predicted. Ming et al. PNAS (2002) 99: 8620-25Tama et al. J. Mol. Biol. (2002) 321: 297–305

Scheuring et al. E. Biophys J, 2001