Theory—New Methods—Parallel Computation

Three-Photon Correlations
The challenges of single molecule scattering experiments are the unknown random molecule orientation in each shot and the low signal to noise ratio due to the very low expected photon count. We developed a correlation-based approach to determine the molecular structure de novo from as few as three coherently scattered photons per image.
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Atomic force microscopy (AFM), biomembrane force probe experiments, and optical tweezer applications allow to measure the response of single molecules to mechanical stress with high precision. We developed a theory to reconstruct force profiles from AFM spectra at varying loading rates, without requiring increased resolution.
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Intrinsically disordered proteins (IDPs) are notoriously challenging to study both experimentally and computationally. Our findings highlight how IDPs, with their rugged energy landscapes, are highly sensitive test systems that are capable of revealing force field deficiencies and, therefore, contributing to force field development.
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SESCA is a computational method that allows rapid and accurate prediction of CD spectra from three-dimensional protein model structures. Calculations allow a direct comparison between the measured CD spectrum of a target protein and the predicted CD spectra based on model structures or structural ensembles to determine the model quality.

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We present a method for automated refinement of atomistic models into cryo-electron microscopy (cryo-EM) maps at resolution around 3Å. The method rests on a combination of real-space, correlation-based molecular dynamics fitting, a continuous series of simulated maps of increasing resolution, and simulated annealing.
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Atomic-detail simulations of large biomolecular systems can easily occupy a compute cluster for weeks or even months. Continuous efforts are being made to ensure that our computing power is used most efficiently. This includes network fine-tuning and code optimizations to reach the best possible parallel scaling.
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MD simulations as well as most quantum classical QM/MM simulations treat the nuclei of the protein atoms as classical particles. Under physiological conditions (room temperature), quantum effects of the atomic nuclei can largely be neglected. It is only under special conditions, that these effects become important and have to be considered.
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As a project within the DFG Exascale SPP, we target a flexible and portable exascale algorithm for potentials and forces, a prerequisite for exascale applications in particle-based simulations with long-range interactions in general.
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We present a method to predict complex 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 MD simulations, since these currently are limited to time scales shorter than a few nanoseconds.
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The major bottleneck of today's atomistic MD simulations is that due to the enormous computational effort involved only processes at nanoseconds to microseconds time scales or faster can be studied directly. Unfortunately, apart from a few expections, relevant processes, occur at slower time scales and therefore are currently far out of reach.
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Proteins are polypeptides which consist of typically 50 to several 100 amino acids and fold into protein-specific three-dimensional structures. This native structure is determined by the amino acid sequence of a protein, which is genetically encoded.
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Collective coordinates for protein motions, can be extracted from MD simulations with established methods, mainly via calculation of the covariance matrix and subsequent principal component analysis[1]. This established approach, however, relies on quasi-harmonic treatment of the configurational ensemble and, therefore, detects only linearly correlated motions. ...
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The calculation of reaction pathways, energy barriers and rates for chemical reactions of small molecules is a routine task in todays theoretical quantum chemistry. Assuming a given educt state, all estalblished methods require additional knowledge on the reaction pathway, putative transition states or the product state. Here we extend the force fileld based method 'conformational flooding' towards the calculation of chemical reactions.
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We have developed a comprehensive dynamics space for protein dynamics based on 34 observables that can be obtained from MD simulations. Distances in this space serve as a measure for protein dynamics similarity which, in turn, allows to quantify structure-dynamics and dynamics-function relationships.
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Typically, in a MD simulation, the protonation states of ionizable groups of a protein are set in the beginning of the simulation. This prerequisite is not always an obvious task, in particular for histidine, as its pKa is close to the physiological pH. In contrast, in a constant pH MD simulation, the protonation state of an ionizable group of a protein is allowed to change.
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Cutlat determines inter-repeat curvature, twist and lateral bending angles, as well as their full-length sums for multi-repeat unit proteins, including e.g. LRR, Armadillo, HEAT or ankyrin repeat proteins. As the principal axes of repeats are used for the calculation of inter-repeat angles, a prior selection of specific conserved reference groups is not required.
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The molecular-dynamics-based calculation of accurate free energy differences for biomolecular systems is a challenging task. We suggest and assess a new nonequilibrium free energy method, Crooks Gaussian Intersection (CGI), which combines the advantages of existing methods.
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Biomolecular processes are governed by free energy changes and thus depend on a fine-tuned interplay between entropy and enthalpy. To calculate accurate values for entropies from simulations is particularly challenging for the solvation shell of proteins, which contribute crucially to the total entropy of solvated proteins, due to the diffusive motion of the solvent ...
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Correlated motions in biomolecules, in particular proteins, are ubiquitous and often essential for biomolecular function. Correct assessment of correlated motions, both experimentally and from theory and simulations, is therefore crucial for a quantitative understanding of biomolecular function. The accurate characterization of correlated motions would also improve ...
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Interactive Molecular Dynamics (IMD) allows users to monitor and interact with a running Molecular Dynamics (MD) simulation. To achive this with the GROMACS package, we provide a patched version, which allows running of interactive simulations by implementing the interactive molecular dynamics (IMD) protocol into GROMACS. The user then can interact with the simulation by pulling on atoms, residues or fragments with a mouse or force-feedback devices.
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We describe a novel method to enforce rotation of a protein subunit in molecular dynamics (MD) simulations. Our »flexible axis« approach allows flexible adaptions of both the rotating subunit as well as the rotation axis during the simulation. For the example of F1-ATP synthase we show that the flexible method (apart from the rotation itself) imposes minimal constraints ...
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Solvate is a program to construct an atomic solvent environment model for a given atomic macromolecule for the use in an MD simulation. Solvate generates irregularly-shaped solvent volumes, adapted to a given solute's structure. It allows efficient computation of boundary forces as required in molecular dynamics simulations.
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