TY - JOUR A1 - Reuter, Bernhard A1 - Fackeldey, Konstantin A1 - Weber, Marcus T1 - Generalized Markov modeling of nonreversible molecular kinetics JF - The Journal of Chemical Physics N2 - Markov state models are to date the gold standard for modeling molecular kinetics since they enable the identification and analysis of metastable states and related kinetics in a very instructive manner. The state-of-the-art Markov state modeling methods and tools are very well developed for the modeling of reversible processes in closed equilibrium systems. On the contrary, they are largely not well suited to deal with nonreversible or even nonautonomous processes of nonequilibrium systems. Thus, we generalized the common Robust Perron Cluster Cluster Analysis (PCCA+) method to enable straightforward modeling of nonequilibrium systems as well. The resulting Generalized PCCA (G-PCCA) method readily handles equilibrium as well as nonequilibrium data by utilizing real Schur vectors instead of eigenvectors. This is implemented in the G-PCCA algorithm that enables the semiautomatic coarse graining of molecular kinetics. G-PCCA is not limited to the detection of metastable states but also enables the identification and modeling of cyclic processes. This is demonstrated by three typical examples of nonreversible systems. Y1 - 2019 U6 - https://doi.org/10.1063/1.5064530 VL - 17 IS - 150 SP - 174103 ER - TY - JOUR A1 - Ernst, Natalia A1 - Fackeldey, Konstantin A1 - Volkamer, Andrea A1 - Opatz, Oliver A1 - Weber, Marcus T1 - Computation of temperature-dependent dissociation rates of metastable protein–ligand complexes JF - Molecular Simulation N2 - Molecular simulations are often used to analyse the stability of protein–ligand complexes. The stability can be characterised by exit rates or using the exit time approach, i.e. by computing the expected holding time of the complex before its dissociation. However determining exit rates by straightforward molecular dynamics methods can be challenging for stochastic processes in which the exit event occurs very rarely. Finding a low variance procedure for collecting rare event statistics is still an open problem. In this work we discuss a novel method for computing exit rates which uses results of Robust Perron Cluster Analysis (PCCA+). This clustering method gives the possibility to define a fuzzy set by a membership function, which provides additional information of the kind ‘the process is being about to leave the set’. Thus, the derived approach is not based on the exit event occurrence and, therefore, is also applicable in case of rare events. The novel method can be used to analyse the temperature effect of protein–ligand systems through the differences in exit rates, and, thus, open up new drug design strategies and therapeutic applications. Y1 - 2019 U6 - https://doi.org/10.1080/08927022.2019.1610949 VL - 45 IS - 11 SP - 904 EP - 911 ER - TY - JOUR A1 - Villatoro, José A1 - Weber, Marcus A1 - Zühlke, Martin A1 - Lehmann, Andreas A1 - Zechiowski, Karl A1 - Riebe, Daniel A1 - Beitz, Toralf A1 - Löhmannsröben, Hans-Gerd A1 - Kreuzer, Oliver T1 - Structural characterization of synthetic peptides using electronspray ion mobility spectrometry and molecular dynamics simulations JF - International Journal of Mass Spectrometry N2 - Electrospray ionization-ion mobility spectrometry was employed for the determination of collision cross sections (CCS) of 25 synthetically produced peptides in the mass range between 540–3310 Da. The experimental measurement of the CCS is complemented by their calculation applying two different methods. One prediction method is the intrinsic size parameter (ISP) method developed by the Clemmer group. The second new method is based on the evaluation of molecular dynamics (MD) simulation trajectories as a whole, resulting in a single, averaged collision cross-section value for a given peptide in the gas phase. A high temperature MD simulation is run in order to scan through the whole conformational space. The lower temperature conformational distribution is obtained through thermodynamic reweighting. In the first part, various correlations, e.g. CCS vs. mass and inverse mobility vs. m/z correlations, are presented. Differences in CCS between peptides are also discussed in terms of their respective mass and m/z differences, as well as their respective structures. In the second part, measured and calculated CCS are compared. The agreement between the prediction results and the experimental values is in the same range for both calculation methods. While the calculation effort of the ISP method is much lower, the MD method comprises several tools providing deeper insights into the conformations of peptides. Advantages and limitations of both methods are discussed. Based on the separation of two pairs of linear and cyclic peptides of virtually the same mass, the influence of the structure on the cross sections is discussed. The shift in cross section differences and peak shape after transition from the linear to the cyclic peptide can be well understood by applying different MD tools, e.g. the root-mean-square deviation (RMSD) and the root mean square fluctuation (RMSF). Y1 - 2019 U6 - https://doi.org/10.1016/j.ijms.2018.10.036 VL - 436 SP - 108 EP - 117 ER - TY - JOUR A1 - Donati, Luca A1 - Heida, Martin A1 - Keller, Bettina G. A1 - Weber, Marcus T1 - Estimation of the infinitesimal generator by square-root approximation JF - J. Phys.: Condens. Matter N2 - In recent years, for the analysis of molecular processes, the estimation of time-scales and transition rates has become fundamental. Estimating the transition rates between molecular conformations is—from a mathematical point of view—an invariant subspace projection problem. We present a method to project the infinitesimal generator acting on function space to a low-dimensional rate matrix. This projection can be performed in two steps. First, we discretize the conformational space in a Voronoi tessellation, then the transition rates between adjacent cells is approximated by the geometric average of the Boltzmann weights of the Voronoi cells. This method demonstrates that there is a direct relation between the potential energy surface of molecular structures and the transition rates of conformational changes. We will show also that this approximation is correct and converges to the generator of the Smoluchowski equation in the limit of infinitely small Voronoi cells. We present results for a two dimensional diffusion process and alanine dipeptide as a high-dimensional system. Y1 - 2018 U6 - https://doi.org/10.1088/1361-648X/aadfc8 VL - 30 IS - 42 SP - 425201 EP - 425201 ER - TY - JOUR A1 - Reidelbach, Marco A1 - Weber, Marcus A1 - Imhof, Petra T1 - Prediction of perturbed proton transfer networks JF - PLoS ONE N2 - The transfer of protons through proton translocating channels is a complex process, for which direct samplings of different protonation states and side chain conformations in a transition network calculation provide an efficient, bias-free description. In principle, a new transition network calculation is required for every unsampled change in the system of interest, e.g. an unsampled protonation state change, which is associated with significant computational costs. Transition networks void of or including an unsampled change are termed unperturbed or perturbed, respectively. Here, we present a prediction method, which is based on an extensive coarse-graining of the underlying transition networks to speed up the calculations. It uses the minimum spanning tree and a corresponding sensitivity analysis of an unperturbed transition network as initial guess and refinement parameter for the determination of an unknown, perturbed transition network. Thereby, the minimum spanning tree defines a sub-network connecting all nodes without cycles and minimal edge weight sum, while the sensitivity analysis analyzes the stability of the minimum spanning tree towards individual edge weight reductions. Using the prediction method, we are able to reduce the calculation costs in a model system by up to 80%, while important network properties are maintained in most predictions. Y1 - 2018 U6 - https://doi.org/https://doi.org/10.1371/journal.pone.0207718 VL - 13 IS - 12 SP - e0207718 EP - e0207718 ER - TY - GEN A1 - Fackeldey, Konstantin A1 - Sikorski, Alexander A1 - Weber, Marcus T1 - Spectral Clustering for Non-reversible Markov Chains N2 - Spectral clustering methods are based on solving eigenvalue problems for the identification of clusters, e.g. the identification of metastable subsets of a Markov chain. Usually, real-valued eigenvectors are mandatory for this type of algorithms. The Perron Cluster Analysis (PCCA+) is a well-known spectral clustering method of Markov chains. It is applicable for reversible Markov chains, because reversibility implies a real-valued spectrum. We also extend this spectral clustering method to non-reversible Markov chains and give some illustrative examples. The main idea is to replace the eigenvalue problem by a real-valued Schur decomposition. By this extension non-reversible Markov chains can be analyzed. Furthermore, the chains do not need to have a positive stationary distribution. In addition to metastabilities, dominant cycles and sinks can also be identified. This novel method is called GenPCCA (i.e. Generalized PCCA), since it includes the case of non reversible processes. We also apply the method to real world eye tracking data. T3 - ZIB-Report - 18-48 KW - spectral clustering KW - Markov chain KW - Schur decomposition KW - non-reversible Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-70218 SN - 1438-0064 ER - TY - JOUR A1 - Fackeldey, Konstantin A1 - Sikorski, Alexander A1 - Weber, Marcus T1 - Spectral Clustering for Non-Reversible Markov Chains JF - Computational and Applied Mathematics N2 - Spectral clustering methods are based on solving eigenvalue problems for the identification of clusters, e.g., the identification of metastable subsets of a Markov chain. Usually, real-valued eigenvectors are mandatory for this type of algorithms. The Perron Cluster Analysis (PCCA+) is a well-known spectral clustering method of Markov chains. It is applicable for reversible Markov chains, because reversibility implies a real-valued spectrum. We also extend this spectral clustering method to non-reversible Markov chains and give some illustrative examples. The main idea is to replace the eigenvalue problem by a real-valued Schur decomposition. By this extension non-reversible Markov chains can be analyzed. Furthermore, the chains do not need to have a positive stationary distribution. In addition to metastabilities, dominant cycles and sinks can also be identified. This novel method is called GenPCCA (i.e., generalized PCCA), since it includes the case of non-reversible processes. We also apply the method to real-world eye-tracking data. KW - Spectral clustering KW - Markov chain KW - Non-reversible KW - Schur decomposition KW - GenPCCA Y1 - 2018 U6 - https://doi.org/https://doi.org/10.1007/s40314-018-0697-0 VL - 37 IS - 5 SP - 6376 EP - 6391 ER - TY - JOUR A1 - Lie, Han Cheng A1 - Fackeldey, Konstantin A1 - Weber, Marcus T1 - A Square Root Approximation of Transition Rates for a Markov State Model JF - SIAM. J. Matrix Anal. Appl. Y1 - 2013 U6 - https://doi.org/10.1137/120899959 VL - 34 IS - 2 SP - 738 EP - 756 ER - TY - JOUR A1 - Scharkoi, Olga A1 - Fackeldey, Konstantin A1 - Merkulow, Igor A1 - Andrae, Karsten A1 - Weber, Marcus A1 - Nehls, Irene T1 - Conformational Analysis of Alternariol on the Quantum Level JF - J. Mol. Model. Y1 - 2013 U6 - https://doi.org/10.1007/s00894-013-1803-2 VL - 19 IS - 6 SP - 2567 EP - 2572 ER - TY - GEN A1 - Bujotzek, Alexander A1 - Schütt, Ole A1 - Nielsen, Adam A1 - Fackeldey, Konstantin A1 - Weber, Marcus T1 - Efficient Conformational Analysis by Partition-of-Unity Coupling T2 - Math Chem N2 - Obtaining a sufficient sampling of conformational space is a common problem in molecular simulation. We present the implementation of an umbrella-like adaptive sampling approach based on function-based meshless discretization of conformational space that is compatible with state of the art molecular dynamics code and that integrates an eigenvector-based clustering approach for conformational analysis and the computation of inter-conformational transition rates. The approach is applied to three example systems, namely n-pentane, alanine dipeptide, and a small synthetic host-guest system, the latter two including explicitly modeled solvent. T3 - ZIB-Report - 13-58 KW - Markov State Models KW - Meshfree KW - Molecular Simulation KW - Partition of Unity Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-42570 SN - 1438-0064 ER - TY - GEN A1 - Quer, Jannes A1 - Donati, Luca A1 - Keller, Bettina A1 - Weber, Marcus T1 - An automatic adaptive importance sampling algorithm for molecular dynamics in reaction coordinates N2 - In this article we propose an adaptive importance sampling scheme for dynamical quantities of high dimensional complex systems which are metastable. The main idea of this article is to combine a method coming from Molecular Dynamics Simulation, Metadynamics, with a theorem from stochastic analysis, Girsanov's theorem. The proposed algorithm has two advantages compared to a standard estimator of dynamic quantities: firstly, it is possible to produce estimators with a lower variance and, secondly, we can speed up the sampling. One of the main problems for building importance sampling schemes for metastable systems is to find the metastable region in order to manipulate the potential accordingly. Our method circumvents this problem by using an assimilated version of the Metadynamics algorithm and thus creates a non-equilibrium dynamics which is used to sample the equilibrium quantities. T3 - ZIB-Report - 17-09 KW - Adaptive Importance Sampling KW - Molecular Dynamics KW - Metastability KW - Variance Reduction KW - Non Equilibrium Sampling KW - Metadynamics KW - Girsanov Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-62075 SN - 1438-0064 ER - TY - JOUR A1 - Spahn, Viola A1 - Del Vecchio, Giovanna A1 - Labuz, Dominika A1 - Rodriguez-Gaztelumendi, Antonio A1 - Massaly, N. A1 - Temp, Julia A1 - Durmaz, Vedat A1 - Sabri, P. A1 - Reidelbach, Marco A1 - Machelska, Halina A1 - Weber, Marcus A1 - Stein, Christoph T1 - A nontoxic pain killer designed by modeling of pathological receptor conformations JF - Science Y1 - 2017 U6 - https://doi.org/10.1126/science.aai8636 VL - 355 IS - 6328 SP - 966 EP - 969 ER - TY - GEN A1 - Weber, Marcus A1 - Fackeldey, Konstantin A1 - Schütte, Christof T1 - Set-free Markov State Building N2 - Molecular dynamics (MD) simulations face challenging problems since the timescales of interest often are much longer than what is possible to simulate and even if sufficiently long simulation are possible the complex nature of the resulting simulation data makes interpretation difficult. Markov State Models (MSMs) help to overcome these problems by making experimentally relevant timescales accessible via coarse grained representations that also allows for convenient interpretation. However, standard set-based MSMs exhibit some caveats limiting their approximation quality and statistical significance. One of the main caveats results from the fact that typical MD trajectories repeatedly re-cross the boundary between the sets used to build the MSM which causes statistical bias in estimating the transition probabilities between these sets. In this article, we present a set-free approach to MSM building utilizing smooth overlapping ansatz functions instead of sets and an adaptive refinement approach. This kind of meshless discretization helps to overcome the recrossing problem and yields an adaptive refinement procedure that allows to improve the quality of the model while exploring state space and inserting new ansatz functions into the MSM. T3 - ZIB-Report - 17-10 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-62167 SN - 1438-0064 ER - TY - GEN A1 - Weber, Marcus T1 - Eigenvalues of non-reversible Markov chains – A case study N2 - Finite reversible Markov chains are characterized by a transition matrix P that has real eigenvalues and pi-orthogonal eigenvectors, where pi is the stationary distribution of P. This means, that a transition matrix with complex eigenvalues corresponds to a non-reversible Markov chain. This observation leads to the question, whether the imaginary part of that eigendecomposition corresponds to or indicates the “pattern” of the nonreversibility. This article shows that the direct relation between imaginary parts of eigendecompositions and the non-reversibility of a transition matrix is not given. It is proposed to apply the Schur decomposition of P instead of the eigendecomposition in order to characterize its nonreversibility. T3 - ZIB-Report - 17-13 KW - non-reversible KW - transition matrix KW - detailed balance Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-62191 SN - 1438-0064 ER - TY - JOUR A1 - Hartmann, Carsten A1 - Schütte, Christof A1 - Weber, Marcus A1 - Zhang, Wei T1 - Importance sampling in path space for diffusion processes with slow-fast variables JF - Probability Theory and Related Fields N2 - Importance sampling is a widely used technique to reduce the variance of a Monte Carlo estimator by an appropriate change of measure. In this work, we study importance sampling in the framework of diffusion process and consider the change of measure which is realized by adding a control force to the original dynamics. For certain exponential type expectation, the corresponding control force of the optimal change of measure leads to a zero-variance estimator and is related to the solution of a Hamilton–Jacobi–Bellmann equation. We focus on certain diffusions with both slow and fast variables, and the main result is that we obtain an upper bound of the relative error for the importance sampling estimators with control obtained from the limiting dynamics. We demonstrate our approximation strategy with an illustrative numerical example. Y1 - 2017 UR - http://rdcu.be/oA51 U6 - https://doi.org/10.1007/s00440-017-0755-3 N1 - If you are not subscribing to the journal please use the http link below as part of the Springer Nature SharedIt initiative SP - 1 EP - 52 ER - TY - JOUR A1 - Villatoro, José A1 - Zühlke, Martin A1 - Riebe, Daniel A1 - Beitz, Toralf A1 - Weber, Marcus A1 - Riedel, Jens A1 - Löhmannsröben, Hans-Gerd T1 - IR-MALDI ion mobility spectrometry: physical source characterization and application as HPLC detector JF - International Journal for Ion Mobility Spectrometry Y1 - 2016 U6 - https://doi.org/10.1007/s12127-016-0208-1 IS - 19/4 SP - 197 EP - 297 ER - TY - JOUR A1 - Guerler, A. A1 - Moll, Sebastian A1 - Weber, Marcus A1 - Meyer, Holger A1 - Cordes, Frank T1 - Selection and flexible optimization of binding modes from conformation ensembles JF - Biosystems Y1 - 2008 UR - http://www.sciencedirect.com/science/article/pii/S0303264707001670 U6 - https://doi.org/DOI: 10.1016/j.biosystems.2007.11.004 VL - 92 IS - 1 SP - 42 EP - 48 ER - TY - JOUR A1 - Haack, Fiete A1 - Röblitz, Susanna A1 - Scharkoi, Olga A1 - Schmidt, Burkhard A1 - Weber, Marcus T1 - Adaptive Spectral Clustering for Conformation Analysis JF - AIP Conference Proceedings Y1 - 2010 UR - http://link.aip.org/link/?APC/1281/1585/1 U6 - https://doi.org/10.1063/1.3498116 VL - 1281 IS - 1 SP - 1585 EP - 1588 PB - AIP ER - TY - CHAP A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Weber, Marcus ED - Mode, Ch. T1 - A rapidly Mixing Monte Carlo Method for the Simulation of Slow Molecular Processes T2 - Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science Y1 - 2011 PB - InTech ER - TY - JOUR A1 - Gürler, A. A1 - Moll, Sebastian A1 - Weber, Marcus A1 - Meyer, Holger A1 - Cordes, Frank T1 - Selection and flexible optimization of binding modes from conformation ensembles JF - Biosystems Y1 - 2007 ER - TY - JOUR A1 - Kube, Susanna A1 - Weber, Marcus T1 - A Coarse Graining Method for the Identification of Transition rates between Molecular Conformations JF - Journal of Chemical Physics Y1 - 2007 U6 - https://doi.org/10.1063/1.2404953 VL - 126 IS - 2 ER -