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Abdullah Kahraman

Publications and source records attributed to Abdullah Kahraman.

2 recordsLinked to original sources

Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons.

MOTIVATION: An increasing number of protein structures are being determined for which no biochemical characterization is available. The analysis of protein structure and function assignment is becoming an unexpected challenge and a major bottleneck towards the goal of well-annotated genomes. As shape plays a crucial role in biomolecular recognition and function, the examination and development of shape description and comparison techniques is likely to be of prime importance for understanding protein structure-function relationships. RESULTS: A novel technique is presented for the comparison of protein binding pockets. The method uses the coefficients of a real spherical harmonics expansion to describe the shape of a protein's binding pocket. Shape similarity is computed as the L2 distance in coefficient space. Such comparisons in several thousands per second can be carried out on a standard linux PC. Other properties such as the electrostatic potential fit seamlessly into the same framework. The method can also be used directly for describing the shape of proteins and other molecules. AVAILABILITY: A limited version of the software for the real spherical harmonics expansion of a set of points in PDB format is freely available upon request from the authors. Binding pocket comparisons and ligand prediction will be made available through the protein structure annotation pipeline Profunc (written by Roman Laskowski) which will be accessible from the EBI website shortly.

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PhenomicDB: a multi-species genotype/phenotype database for comparative phenomics.

UNLABELLED: We have created PhenomicDB, a multi-species genotype/phenotype database by merging public genotype/phenotype data from a wide range of model organisms and Homo sapiens. Until now these data were available in distinct organism-specific databases (e.g. WormBase, OMIM, FlyBase and MGI). We compiled this wealth of data into a single integrated resource by coarse-grained semantic mapping of the phenotypic data fields, by including common gene indices (NCBI Gene), and by the use of associated orthology relationships. With its use-case-oriented user interface, PhenomicDB allows scientists to compare and browse known phenotypes for a given gene or a set of genes from different organisms simultaneously. AVAILABILITY: PhenomicDB has been implemented at Schering AG as described below. A PhenomicDB implementation differing in some technical details has been set up for the public at Metalife AG http://www.phenomicDB.de SUPPLEMENTARY INFORMATION: database model, semantic mapping table.

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