1,721,371 research outputs found
Predicting slow structural transitions in macromolecular systems: Conformational flooding.
Get PDFWe present a method to predict complex structural (conformational) transitions in irregular or disordered macromolecular systems, such as proteins or glasses, at the atomic level. Our method aims at rare events, which currently cannot be predicted with traditional molecular dynamics (MD) simulations, since these currently are limited to time scales shorter than a few nanoseconds. Given an initial conformation of the system, our method identifies one or more product states, which may be separated from the initial state by free energy barriers that are large on the scale of thermal energy. It also provides an approximate reaction path, which can be used to determine barrier heights or reaction rates with the usual techniques. The method employs an artificial potential that destabilizes the initial conformation and, thereby, lowers free energy barriers of structural transitions. As a result, transitions are accelerated and may be observed in MD simulations. An analytical estimate for the acceleration factor is given. The method is applied to two test systems, an argon microcluster and a simplified protein model. By these studies we demonstrated that our method is capable of shortening mean transition times from 0.5 μs (argon cluster) and 1.4 ns (protein model) to a few picoseconds. These results suggest that our method is particularly well suited to study biochemically relevant conformational motions in proteins at a microsecond time scale
Dynamic Force Spectroscopy of Molecular Adhesion Bonds
No full textRecent advances in atomic force microscopy, biomembrane force probe experiments, and optical tweezers allow one to measure the response of single molecules to mechanical stress with high precision. Such experiments, due to limited spatial resolution, typically access only one single force value in a continuous force profile that characterizes the molecular response along a reaction coordinate. We develop a theory that allows one to reconstruct force profiles from force spectra obtained from measurements at varying loading rates, without requiring increased resolution. We show that spectra obtained from measurements with different spring constants contain complementary information
Bayesian electron density determination from sparse and noisy single-molecule X-ray scattering images
No full textSingle molecule X-ray scattering experiments using free electron lasers hold
the potential to resolve both single structures and structural ensembles of
biomolecules. However, molecular electron density determination has so far not
been achieved due to low photon counts, high noise levels and low hit rates.
Most analysis approaches therefore focus on large specimen like entire viruses,
which scatter substantially more photons per image, such that it becomes
possible to determine the molecular orientation for each image. In contrast,
for small specimen like proteins, the molecular orientation cannot be
determined for each image, and must be considered random and unknown.
Here we developed and tested a rigorous Bayesian approach to overcome these
limitations, and also taking into account intensity fluctuations, beam
polarization, irregular detector shapes, incoherent scattering and background
scattering. We demonstrate using synthetic scattering images that it is
possible to determine electron densities of small proteins in this extreme high
noise Poisson regime. Tests on published experimental data from the coliphage
PR772 achieved the detector-limited resolution of , using only
of the available photons per image
Bayesian electron density determination from sparse and noisy single-molecule X-ray scattering images
No full textSingle molecule X-ray scattering experiments using free electron lasers hold
the potential to resolve both single structures and structural ensembles of
biomolecules. However, molecular electron density determination has so far not
been achieved due to low photon counts, high noise levels and low hit rates.
Most analysis approaches therefore focus on large specimen like entire viruses,
which scatter substantially more photons per image, such that it becomes
possible to determine the molecular orientation for each image. In contrast,
for small specimen like proteins, the molecular orientation cannot be
determined for each image, and must be considered random and unknown.
Here we developed and tested a rigorous Bayesian approach to overcome these
limitations, and also taking into account intensity fluctuations, beam
polarization, irregular detector shapes, incoherent scattering and background
scattering. We demonstrate using synthetic scattering images that it is
possible to determine electron densities of small proteins in this extreme high
noise Poisson regime. Tests on published experimental data from the coliphage
PR772 achieved the detector-limited resolution of , using only
of the available photons per image
Kraftspektroskopie von einzelnen Biomolekülen: Biologische Makromoleküle besser begreifen - mit Einzelmolekül-Kraftmessungen und Computersimulationen
No full textPraktisch alle Stoffwechselvorgänge im Körper werden durch hochspezialisierte Proteine bewirkt oder gesteuert – man kann sie mit gutem Recht als die biochemischen „Nano‐Maschinen”︁ der Zelle bezeichnen. Jüngste Fortschritte, besonders bei Einzelmolekülexperimenten und deren Simulation mithilfe von Hochleistungscomputern, erlauben es, einigen dieser „Nano‐Maschinen”︁ bei der Arbeit zuzusehen. Dabei treten erstaunliche Mechanismen zutage: Man beobachtet z. B. fein abgestimmte Bewegungen der Bindungstasche eines Rezeptor‐Proteins bei der Erkennung eines Ligandenmoleküls oder die Entfaltung von Titin, das als molekularer Stoßabsorber Muskelzellen schützt. Gegenwärtig sind wir aber außerstande, solche Präzisionsfeinmechaniken zu konstruieren – wir beginnen gerade, deren Mechanismen zu verstehen und die Eigenschaften ihrer Funktion zu berechnen und vorherzusagen
Computer Aided Distance Reconstruction in Single Molecule FRET Experiments through Combination with Dye Dynamics from Molecular Dynamics Simulations
No full textMultiple time step algorithms for molecular dynamics simulations of proteins: How good are they?
No full textWe evaluate several multiple time step (MTS) molecular dynamics (MD) methods with respect to their suitability for protein dynamics simulations. In contrast to the usual check of conservation of total energy or comparisons of trajectory details, we chose a problem‐oriented approach and selected a set of relevant observables computed from extended test simulations. We define relevance of observables with respect to their role in the description of protein function. Accordingly, the use of quantities that exhibit chaotic behavior, like trajectory details, is shown to be inappropriate for the sake of the evaluation of methods. The accuracy of a cutoff method and of six MTS methods is evaluated, which differ in their treatment of the computationally crucial long‐ranged Coulomb interactions. For each of the observables considered, the size of purely statistical fluctuations is determined to allow identification of algorithmic artifacts. The obtained ranking of the considered MD methods differs significantly from that obtained by the usual measures of algorithmic accuracy. One particular distance class method, DC‐1d, is shown to be clearly superior in that no algorithmic artifacts were detected
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