TY - JOUR A1 - Krause, Dorian A1 - Fackeldey, Konstantin A1 - Krause, Rolf ED - Griebel, Michael T1 - A Parallel Multiscale Simulation Toolbox for Coupling Molecular Dynamics and Finite Elements JF - Singular Phenomena and Scaling in Mathematical Models Y1 - 2014 U6 - https://doi.org/10.1007/978-3-319-00786-1_14 SP - 327 EP - 346 PB - Springer International Publishing ER - TY - JOUR A1 - Scharkoi, Olga A1 - Esslinger, Susanne A1 - Becker, Roland A1 - Weber, Marcus A1 - Nehls, Irene T1 - Predicting sites of cytochrome P450-mediated hydroxylation applied to CYP3A4 and hexabromocyclododecane JF - Molecular Simulation Y1 - 2014 U6 - https://doi.org/10.1080/08927022.2014.898845 ER - TY - JOUR A1 - Haack, Fiete A1 - Fackeldey, Konstantin A1 - Röblitz, Susanna A1 - Scharkoi, Olga A1 - Weber, Marcus A1 - Schmidt, Burkhard T1 - Adaptive spectral clustering with application to tripeptide conformation analysis JF - The Journal of Chemical Physics Y1 - 2013 U6 - https://doi.org/10.1063/1.4830409 VL - 139 SP - 110 EP - 194 ER - TY - THES A1 - Nielsen, Adam T1 - Von Femtosekunden zu Minuten Y1 - 2012 UR - http://www.zib.de/nielsen/Masterarbeit.pdf ER - TY - CHAP A1 - Igde, Sinaida A1 - Wölk, Hendrik A1 - Röblitz, Susanna A1 - Reidelbach, Marco A1 - Weber, Marcus A1 - Hartmann, Laura T1 - Identifying Multivalent Binding Kinetics of Precision Glycomacromolecules: A Kinetic Study Using kinITC T2 - Münster Symposium on Cooperative Effects 2015 - SFB 858, at Westfälische Wilhelms-Universität Münster, 2015 N2 - Multivalent sugar/protein interactions are well-known to proceed through different binding modes 1-5 which in turn can be described by their binding kinetics 3-5. This study provides additional insight into the association and dissociation reaction rates of complex multivalent sugar/protein interactions. Binding kinetics of recently introduced multivalent precision glycomacromolecules 6-8 to Concanavalin A (Con A) were studied by " kinetic Isothermal Titration Calorimetry " (kinITC) 9-11. The effect of multivalency is evaluated by comparing rate constants of glycomacromolecules obtaining the same and different valency of mannose ligands and by variation of the overall backbone properties, such as hydrophilic/ hydrophoboc. In addition, binding kinetics were studied using different conformations of Con A (homodimer vs.-tetramer) and thus a different protein valency. Our results show that precision glycomacromolecule/Con A binding proceeds non-cooperatively. Further, association and dissociation rates are mainly described by intermolecular complex formation. Together with the so-called functional valency, we can discriminate between " bound " and " unbound " states for macroscopic on-and off-rates, even for such complex glycooligomer/protein systems. By comparing e.g. a mono-to a divalent glycomacromolecule for their binding to dimeric Con A, we see a lower dissociation rate for the latter. As both bind monovalently to Con A, this is a strong indication for a statistical rebinding event. Further, there is a strong dependence of multivalent binding kinetics on the ligand density of glycomacromolecules as well as the Con A conformation and thus the overall on-and off-rates. Y1 - 2015 ER - TY - GEN A1 - Nielsen, Adam T1 - The Monte Carlo Computation Error of Transition Probabilities N2 - In many applications one is interested to compute transition probabilities of a Markov chain. This can be achieved by using Monte Carlo methods with local or global sampling points. In this article, we analyze the error by the difference in the $L^2$ norm between the true transition probabilities and the approximation achieved through a Monte Carlo method. We give a formula for the error for Markov chains with locally computed sampling points. Further, in the case of reversible Markov chains, we will deduce a formula for the error when sampling points are computed globally. We will see that in both cases the error itself can be approximated with Monte Carlo methods. As a consequence of the result, we will derive surprising properties of reversible Markov chains. T3 - ZIB-Report - 16-37 KW - Reversible Markov chain KW - Monte Carlo methods KW - Computation error KW - Measurable state space KW - Markov operator Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-59933 SN - 1438-0064 ER - TY - JOUR A1 - Nielsen, Adam T1 - The Monte Carlo Computation Error of Transition Probabilities JF - Statistics & Probability Letters N2 - In many applications one is interested to compute transition probabilities of a Markov chain. This can be achieved by using Monte Carlo methods with local or global sampling points. In this article, we analyze the error by the difference in the $L^2$ norm between the true transition probabilities and the approximation achieved through a Monte Carlo method. We give a formula for the error for Markov chains with locally computed sampling points. Further, in the case of reversible Markov chains, we will deduce a formula for the error when sampling points are computed globally. We will see that in both cases the error itself can be approximated with Monte Carlo methods. As a consequence of the result, we will derive surprising properties of reversible Markov chains. Y1 - 2016 U6 - https://doi.org/10.1016/j.spl.2016.06.011 VL - 118 SP - 163 EP - 170 PB - Elsevier ER - TY - JOUR 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 JF - SIAM Journal on Scientific Computing 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. Y1 - 2018 U6 - https://doi.org/10.1137/17m1124772 VL - 40 IS - 2 SP - A653 EP - A670 ER - TY - JOUR A1 - Weber, Marcus T1 - Transformationsprodukte im Klärwerk: Mathematische Ansätze der Bewertung JF - KA Korrespondenz Abwasser, Abfall Y1 - 2018 ER - TY - THES A1 - Breitbach, Paula T1 - Molecular Binding Kinetics of CYP P450 by Using the Infinitesimal Generator Approach Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-69076 ER - TY - JOUR A1 - Reuter, Bernhard A1 - Weber, Marcus A1 - Fackeldey, Konstantin A1 - Röblitz, Susanna A1 - Garcia, Martin E. T1 - Generalized Markov State Modeling Method for Nonequilibrium Biomolecular Dynamics: Exemplified on Amyloid β Conformational Dynamics Driven by an Oscillating Electric Field JF - Journal of Chemical Theory and Computation N2 - Markov state models (MSMs) have received an unabated increase in popularity in recent years, as they are very well suited for the identification and analysis of metastable states and related kinetics. However, the state-of-the-art Markov state modeling methods and tools enforce the fulfillment of a detailed balance condition, restricting their applicability to equilibrium MSMs. To date, they are unsuitable to deal with general dominant data structures including cyclic processes, which are essentially associated with nonequilibrium systems. To overcome this limitation, we developed a generalization of the common robust Perron Cluster Cluster Analysis (PCCA+) method, termed generalized PCCA (G-PCCA). This method handles equilibrium and nonequilibrium simulation data, utilizing Schur vectors instead of eigenvectors. G-PCCA is not limited to the detection of metastable states but enables the identification of dominant structures in a general sense, unraveling cyclic processes. This is exemplified by application of G-PCCA on nonequilibrium molecular dynamics data of the Amyloid β (1−40) peptide, periodically driven by an oscillating electric field. Y1 - 2018 U6 - https://doi.org/10.1021/acs.jctc.8b00079 VL - 14 IS - 7 SP - 3579 EP - 3594 ER -