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Biomedical subjects

G Sagerer

Publications and source records attributed to G Sagerer.

4 recordsLinked to original sources

Estimation and filtering of potential protein-protein docking positions.

MOTIVATION: Software systems predicting automatically whether and how two proteins may interact are highly desirable, both for understanding biological processes and for the rational design of new proteins. As a part of a future complete solution to this problem, a bundle of programs is presented designed (i) to estimate initial docking positions for a given pair of docking candidates, (ii) to adjust them, and (iii) to filter them, thus preparing more detailed computations of free energies. RESULTS: The system is evaluated on a test set of 51 co-crystallized complexes aiming at redocking the subunits. It works completely automatically and the evaluation is performed using one single set of parameters for all complexes in the test set. The number of solutions is fixed to 50 positions with a median CPU time of 26 min. For 30 complexes, these contain a near-correct solution with root mean square deviation ( RMSD ) </=5.0 A, which is ranked first in five cases. For all complexes, the best solution is scored on rank 16 as the worst case, and has a median RMSD of 4.3 A. Alternatively to this initial estimation of docking positions, a global sampling of rotations was tested. Whereas this yields top-ranked solutions with RMSD </=3.0 A for all 51 complexes, the median CPU time increases to 11 h. This shows that this blind sampling is not feasible for most applications. AVAILABILITY: The system and its components are available on request from the authors. CONTACT: friedric@techfak.uni-bielefeld or posch@techfak.uni-bielefeld.de

Algorithms↗

Protein docking combining symbolic descriptions of molecular surfaces and grid-based scoring functions.

With the growing number of known 3D protein structures, computing systems, that can predict where two protein molecules interact with each other is becoming of increasing interest. A system is presented, integrating preprocessing like the computation of molecular surfaces, segmentation, and searching for complementarity in the general framework of a pattern analyzing semantic network (ERNEST). The score of coarse symbolic computations is used by the problem independent control strategy of ERNEST to guide a more detailed analysis considering steric clash and judgements based on grid-based surface representations. Successful examples of the docking system are discussed that compare well with other approaches.

Binding Sites↗

An architecture for distributed visual memory.

The development of autonomous as well as situated robots is one of the great remaining challenges and involves a number of different scientific disciplines. In spite of recent dramatic progress, it remains worthwhile to examine natural systems, because their abilities are still out of reach. Motivated by research work done in the fields of cognitive systems, visual perception, and psychology of memory we designed and implemented a memory architecture for visual tasks. Structural and functional concepts of the memory architecture were modeled on the ones found in natural systems. We present an efficient implementation based on parallel programming techniques. The memory module is integrated into a distributed system for speech and image analysis, which is currently developed in the Sonderforschungsbereich (SFB) 360, Situated Artificial Communicators, where a hybrid vision system combining neural and semantic networks is used.

Animals↗