1,721,022 research outputs found
Selbstorganisation von Assoziativspeichern und Musterklassifikatoren: Rekurrente Signalverarbeitung auf topologischen Merkmalskarten
No full textSelbstorganisation von Assoziativspeichern und Musterklassifikatoren: Rekurrente Signalverarbeitung auf topologischen Merkmalskarten
No full textSimulation eines molekularen Erkennungsvorgangs
No full textViele biochemische Prozesse werden durch hochspezifische Bindungen zwischen exakt aufeinander abgestimmten molekularen Partnern vermittelt. Gestützt auf kraftmikroskopische Experimente konnten wir mit Computersimulationen Einblicke in den atomaren Mechanismus solcher selektiven Wechselwirkungen gewinnen
Simulation eines molekularen Erkennungsvorgangs
No full textViele biochemische Prozesse werden durch hochspezifische Bindungen zwischen exakt aufeinander abgestimmten molekularen Partnern vermittelt. Gestützt auf kraftmikroskopische Experimente konnten wir mit Computersimulationen Einblicke in den atomaren Mechanismus solcher selektiven Wechselwirkungen gewinnen
Self-organization of associative memory and pattern classification: recurrent signal processing on topological feature maps.
Full text linkWe extend the neural concepts of topological feature maps towards self-organization of auto-associative memory and hierarchical pattern classification. As is well-known, topological maps for statistical data sets store information on the associated probability densities. To extract that information we introduce a recurrent dynamics of signal processing. We show that the dynamics converts a topological map into an auto-associative memory for real-valued feature vectors which is capable to perform a cluster analysis. The neural network scheme thus developed represents a generalization of non-linear matrix-type associative memories. The results naturally lead to the concept of a feature atlas and an associated scheme of self-organized, hierarchical pattern classification
Ligand binding: Molecular mechanics calculation of the streptavidin-biotin rupture force.
Full text linkThe force required to rupture the streptavidin-biotin complex was calculated here by computer simulations. The computed force agrees well with that obtained by recent single molecule atomic force microscope experiments. These simulations suggest a detailed multiple-pathway rupture mechanism involving five major unbinding steps. Binding forces and specificity are attributed to a hydrogen bond network between the biotin ligand and residues within the binding pocket of streptavidin. During rupture, additional water bridges substantially enhance the stability of the complex and even dominate the binding interactions. In contrast, steric restraints do not appear to contribute to the binding forces, although conformational motions were observed
FAMUSAMM: An algorithm for rapid evaluation of electrostatic interactions in molecular dynamics simulations
No full textWithin molecular dynamics simulations of protein–solvent systems the exact evaluation of long‐range Coulomb interactions is computationally demanding and becomes prohibitive for large systems. Conventional truncation methods circumvent that computational problem, but are hampered by serious artifacts concerning structure and dynamics of the simulated systems. To avoid these artifacts we have developed an efficient and yet sufficiently accurate approximation scheme which combines the structure‐adapted multipole method (SAMM) [C. Niedermeier and P. Tavan, J. Chem. Phys., 101, 734 (1994)] with a multiple‐time‐step method. The computational effort for MD simulations required within our fast multiple‐time‐step structure‐adapted multipole method (FAMUSAMM) scales linearly with the number of particles. For a system with 36,000 atoms we achieve a computational speed‐up by a factor of 60 as compared with the exact evaluation of the Coulomb forces. Extended test simulations show that the applied approximations do not seriously affect structural or dynamical properties of the simulated systems
Conformational dynamics of proteins: beyond the nanosecond time scale
No full textProtein motions and functional processes in proteins occur on a wide range of time scales. The fastest atomic motions take place on a femtosecond time scale. Fast biochemical reactions like the primary steps in photosynthesis last few picoseconds. Most biochemical reactions like enzymatic processes take much longer — microseconds or even few milliseconds. They are often accompanied by larger structural rearrangements in the protein, called conformational transitions[l], which are characterized by transition times of nanoseconds or much longer. A prominent example for an extremely slow conformational transition, with a transition time of many years, is the one which is believed to be responsible for the pathogenic effect of prions[2]. Often, conformational transitions constitute functional important motions, as for the gating of channel proteins or in protein folding
BR at work: a computeranimation for the 13-14-cis-model of the photochemical cycle of bacter10rhodopsin
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