TY - GEN A1 - Fackeldey, Konstantin A1 - Röblitz, Susanna A1 - Scharkoi, Olga A1 - Weber, Marcus T1 - Soft Versus Hard Metastable Conformations in Molecular Simulations N2 - Particle methods have become indispensible in conformation dynamics to compute transition rates in protein folding, binding processes and molecular design, to mention a few. Conformation dynamics requires at a decomposition of a molecule's position space into metastable conformations. In this paper, we show how this decomposition can be obtained via the design of either ``soft'' or ``hard'' molecular conformations. We show, that the soft approach results in a larger metastabilitiy of the decomposition and is thus more advantegous. This is illustrated by a simulation of Alanine Dipeptide. T3 - ZIB-Report - 11-27 KW - Proteins, Conformation Space, Meshfree Methods Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-13189 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 - JOUR A1 - Röblitz, Susanna A1 - Weber, Marcus T1 - Fuzzy Spectral Clustering by PCCA+ JF - Classification and Clustering: Models, Software and Applications Y1 - 2009 UR - http://www.wias-berlin.de/publications/wias-publ/run.jsp?template=abstract&type=Report&year=2009&number=26 IS - WIAS Report No. 26 SP - 73 EP - 79 ER - TY - JOUR A1 - Röblitz, Susanna A1 - Weber, Marcus T1 - Fuzzy spectral clustering by PCCA+: application to Markov state models and data classification JF - Advances in Data Analysis and Classification Y1 - 2013 U6 - https://doi.org/10.1007/s11634-013-0134-6 VL - 7 IS - 2 SP - 147 EP - 179 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 - 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 - 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 - TY - JOUR A1 - Erlekam, Franziska A1 - Igde, Sinaida A1 - Röblitz, Susanna A1 - Hartmann, Laura A1 - Weber, Marcus T1 - Modeling of Multivalent Ligand-Receptor Binding Measured by kinITC JF - Computation N2 - In addition to the conventional Isothermal Titration Calorimetry (ITC), kinetic ITC (kinITC) not only gains thermodynamic information, but also kinetic data from a biochemical binding process. Moreover, kinITC gives insights into reactions consisting of two separate kinetic steps, such as protein folding or sequential binding processes. The ITC method alone cannot deliver kinetic parameters, especially not for multivalent bindings. This paper describes how to solve the problem using kinITC and an invariant subspace projection. The algorithm is tested for multivalent systems with different valencies. Y1 - 2019 U6 - https://doi.org/10.3390/computation7030046 VL - 7 IS - 3 SP - 46 ER - TY - JOUR A1 - Fackeldey, Konstantin A1 - Röblitz, Susanna A1 - Scharkoi, O. A1 - Weber, Marcus T1 - Soft Versus Hard Metastable Conformations in Molecular Simulations JF - Particle Methods II, Fundamentals and Applications, Barcelona, Spain 26-28 Oct. 2011, E. Onate and D.R.J. Owen (eds.) Y1 - 2011 SP - 899 EP - 909 ER - TY - JOUR A1 - Igde, Sinaida A1 - Röblitz, Susanna A1 - Müller, Anne A1 - Kolbe, Katharina A1 - Boden, Sophia A1 - Fessele, Claudia A1 - Lindhorst, Thisbe A1 - Weber, Marcus A1 - Hartmann, Laura T1 - Linear Precision Glycomacromolecules with Varying Interligand Spacing and Linker Functionalities Binding to Concanavalin A and the Bacterial Lectin FimH JF - Marcomolecular Bioscience Y1 - 2017 U6 - https://doi.org/10.1002/mabi.201700198 VL - 17 IS - 12 SP - 1700198 ER - TY - JOUR A1 - Yousefian, Maryam A1 - Frank, Anne-Simone A1 - Weber, Marcus A1 - Röblitz, Susanna T1 - Efficient construction of Markov state models for stochastic gene regulatory networks by domain decomposition JF - BMC Bioinformatics N2 - The dynamics of many gene regulatory networks (GRNs) is characterized by the occurrence of metastable phenotypes and stochastic phenotype switches. The chemical master equation (CME) is the most accurate description to model such stochastic dynamics, whereby the long-time dynamics of the system is encoded in the spectral properties of the CME operator. Markov State Models (MSMs) provide a general framework for analyzing and visualizing stochastic multistability and state transitions based on these spectral properties. Until now, however, this approach is either limited to low-dimensional systems or requires the use of high-performance computing facilities, thus limiting its usability. Y1 - 2025 U6 - https://doi.org/10.1186/s12859-025-06174-5 VL - 26 IS - 147 ER - TY - CHAP A1 - Yousefian, Maryam A1 - Donati, Luca A1 - Sikorski, Alexander A1 - Weber, Marcus A1 - Röblitz, Susanna T1 - Exploring Metastable Dynamics of Gene Regulatory Networks with ISOKANN T2 - Computational Methods in Systems Biology. CMSB 2025 N2 - Stochastic dynamical systems like gene regulatory networks (GRNs) often exhibit behavior characterized by metastable sets (representing cellular phenotypes), in which trajectories remain for long times, whereas switches between these sets in the phase space are rare events. One way to capture these rare events is to infer the system’s long-term behavior from the spectral characteristics (eigenvalues and eigenvectors) of its Koopman operator. For GRNs, the Koopman operator is based on the chemical master equation (CME), which provides a precise mathematical modeling framework for stochastic GRNs. Since the CME is typically analytically intractable, methods based on discretizing the CME operator have been developed. However, determining the number and location of metastable sets in the phase space as well as the transition rates between them remains computationally challenging, especially for large GRNs with many genes and interactions. A promising alternative method, called ISOKANN (invariant subspaces of Koopman operators with artificial neural networks) has been developed in the context of molecular dynamics. ISOKANN uses a combination of the power iteration and neural networks to learn the basis functions of an invariant subspace of the Koopman operator. In this paper, we extend the application of ISOKANN to the CME operator and apply it to two small GRNs: a genetic toggle switch model and a model for macrophage polarization. Our work opens a new field of application for the ISOKANN algorithm and demonstrates the potential of this algorithm for studying large GRNs. Y1 - 2026 U6 - https://doi.org/10.1007/978-3-032-01436-8_8 VL - 15959 SP - 126 EP - 149 ER -