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Herbert Edelsbrunner

Publications and source records attributed to Herbert Edelsbrunner.

5 recordsLinked to original sources
PubMed2006

Evaluating the quality of NMR structures by local density of protons.

Evaluating the quality of experimentally determined protein structural models is an essential step toward identifying potential errors and guiding further structural refinement. Herein, we report the use of proton local density as a sensitive measure to assess the quality of nuclear magnetic resonance (NMR) structures. Using 256 high-resolution crystal structures with protons added and optimized, we show that the local density of different proton types display distinct distributions. These distributions can be characterized by statistical moments and are used to establish local density Z-scores for evaluating both global and local packing for individual protons. Analysis of 546 crystal structures at various resolutions shows that the local density Z-scores increase as the structural resolution decreases and correlate well with the ClashScore (Word et al. J Mol Biol 1999;285(4):1711-1733) generated by all atom contact analysis. Local density Z-scores for NMR structures exhibit a significantly wider range of values than for X-ray structures and demonstrate a combination of potentially problematic inflation and compression. Water-refined NMR structures show improved packing quality. Our analysis of a high-quality structural ensemble of ubiquitin refined against order parameters shows proton density distributions that correlate nearly perfectly with our standards derived from crystal structures, further validating our approach. We present an automated analysis and visualization tool for proton packing to evaluate the quality of NMR structures.

Crystallography, X-Ray↗
PubMed2005

Experimental validation of the docking orientation of Cdc25 with its Cdk2-CycA protein substrate.

Cdc25 phosphatases are key activators of the eukaryotic cell cycle and compelling anticancer targets because their overexpression has been associated with numerous cancers. However, drug discovery targeting these phosphatases has been hampered by the lack of structural information about how Cdc25s interact with their native protein substrates, the cyclin-dependent kinases. Herein, we predict a docked orientation for Cdc25B with its Cdk2-pTpY-CycA protein substrate by a rigid-body docking method and refine the docked models with full-scale molecular dynamics simulations and minimization. We validate the stable ensemble structure experimentally by a variety of in vitro and in vivo techniques. Specifically, we compare our model with a crystal structure of the substrate-trapping mutant of Cdc25B. We identify and validate in vivo a novel hot-spot residue on Cdc25B (Arg492) that plays a central role in protein substrate recognition. We identify a hot-spot residue on the substrate Cdk2 (Asp206) and confirm its interaction with hot-spot residues on Cdc25 using hot-spot swapping and double mutant cycles to derive interaction energies. Our experimentally validated model is consistent with previous studies of Cdk2 and its interaction partners and initiates the opportunity for drug discovery of inhibitors that target the remote binding sites of this protein-protein interaction.

Binding Sites↗
PubMed2003

The weighted-volume derivative of a space-filling diagram.

Computing the volume occupied by individual atoms in macromolecular structures has been the subject of research for several decades. This interest has grown in the recent years, because weighted volumes are widely used in implicit solvent models. Applications of the latter in molecular mechanics simulations require that the derivatives of these weighted volumes be known. In this article, we give a formula for the volume derivative of a molecule modeled as a space-filling diagram made up of balls in motion. The formula is given in terms of the weights, radii, and distances between the centers as well as the sizes of the facets of the power diagram restricted to the space-filling diagram. Special attention is given to the detection and treatment of singularities as well as discontinuities of the derivative.

Biophysical Phenomena↗
PubMedDate not supplied

Simplification of three-dimensional density maps.

We consider scientific data sets that describe density functions over three-dimensional geometric domains. Such data sets are often large and coarsened representations are needed for visualization and analysis. Assuming a tetrahedral mesh representation, we construct such representations with a simplification algorithm that combines three goals: the approximation of the function, the preservation of the mesh topology, and the improvement of the mesh quality. The third goal is achieved with a novel extension of the well-known quadric error metric. We perform a number of computational experiments to understand the effect of mesh quality improvement on the density map approximation. In addition, we study the effect of geometric simplification on the topological features of the function by monitoring its critical points.

Algorithms↗