TY - GEN A1 - Fackeldey, Konstantin A1 - Koltai, Péter A1 - Névir, Peter A1 - Rust, Henning A1 - Schild, Axel A1 - Weber, Marcus T1 - From Metastable to Coherent Sets - time-discretization schemes N2 - Given a time-dependent stochastic process with trajectories x(t) in a space $\Omega$, there may be sets such that the corresponding trajectories only very rarely cross the boundaries of these sets. We can analyze such a process in terms of metastability or coherence. Metastable sets M are defined in space $M\subset\Omega$, coherent sets $M(t)\subset\Omega$ are defined in space and time. Hence, if we extend the space by the time-variable t, coherent sets are metastable sets in $\Omega\times[0,\infty]$. This relation can be exploited, because there already exist spectral algorithms for the identification of metastable sets. In this article we show that these well-established spectral algorithms (like PCCA+) also identify coherent sets of non-autonomous dynamical systems. For the identification of coherent sets, one has to compute a discretization (a matrix T) of the transfer operator of the process using a space-timediscretization scheme. The article gives an overview about different time-discretization schemes and shows their applicability in two different fields of application. T3 - ZIB-Report - 17-74 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-66074 SN - 1438-0064 ER - TY - JOUR A1 - Villatoro, Jose A1 - Zühlke, Martin A1 - Riebe, Daniel A1 - Riedel, Jens A1 - Beitz, Toralf A1 - Löhmannsröben, Hans-Gerd T1 - IR-MALDI ion mobility spectrometry JF - Analytical and Bioanalytical Chemistry Y1 - 2016 U6 - https://doi.org/10.1007/s00216-016-9739-x VL - 408 IS - 23 SP - 6259 EP - 6268 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 - GEN A1 - Kube, Susanna A1 - Lasser, Caroline A1 - Weber, Marcus T1 - Monte Carlo sampling of Wigner functions and surface hopping quantum dynamics N2 - Wigner transformation provides a one-to-one correspondence between functions on position space (wave functions) and functions on phase space (Wigner functions). Weighted integrals of Wigner functions yield quadratic quantities of wave functions like position and momentum densities or expectation values. For molecular quantum systems, suitably modified classical transport of Wigner functions provides an asymptotic approximation of the dynamics in the high energy regime. The article addresses the computation of Wigner functions by Monte Carlo quadrature. An ad aption of the Metropolis algorithm for the approximation of signed measures with disconnected support is systematically tested in combination with a surface hopping algorithm for non-adiabatic quantum dynamics. The numerical experiments give expectation values and level populations with an error of two to three percent, which agrees with the theoretically expected accuracy. T3 - ZIB-Report - 07-17 KW - Metropolis Monte Carlo KW - approximation KW - quadrature KW - oscillating functions Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-9604 ER - TY - JOUR A1 - Thies, Arne A1 - Sunkara, Vikram A1 - Ray, Sourav A1 - Wulkow, Hanna A1 - Celik, M. Özgür A1 - Yergöz, Fatih A1 - Schütte, Christof A1 - Stein, Christoph A1 - Weber, Marcus A1 - Winkelmann, Stefanie T1 - Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design JF - Scientific Reports N2 - We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. The design process of NFEPP was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present an additional and novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels and their dependence on parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for the ligands NFEPP and fentanyl at different pH values and radical concentrations. We observe markedly reduced binding affinity and calcium channel inhibition for NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl. For increasing radical concentrations, we find enhanced constitutive G-protein activation but reduced ligand binding affinity. Assessing the different effects, the results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account. Y1 - 2023 U6 - https://doi.org/10.1038/s41598-023-27699-w VL - 13 IS - 607 ER - TY - JOUR A1 - Prasad, Anup K. A1 - Tiwari, Chandni A1 - Ray, Sourav A1 - Holden, Stephanie A1 - Armstrong, David A. A1 - Rosengren, K. Johan A1 - Rodger, Alison A1 - Panwar, Ajay S. A1 - Martin, Lisandra L. T1 - Secondary Structure Transitions for a Family of Amyloidogenic, Antimircobial Uperin 3 Peptides in Contact with Sodium Dodecyl Sulfate JF - ChemPlusChem Y1 - 2022 U6 - https://doi.org/10.1002/cplu.202100408 VL - 87 SP - e202100408 ER - TY - JOUR A1 - Heida, Martin A1 - Sikorski, Alexander A1 - Weber, Marcus T1 - Consistency and order 1 convergence of cell-centered finite volume discretizations of degenerate elliptic problems in any space dimension JF - SIAM Journal on Numerical Analysis N2 - We study consistency of cell-centered finite difference methods for elliptic equations with degenerate coefficients in any space dimension $d \geq 2$. This results in order of convergence estimates in the natural weighted energy norm and in the weighted discrete $L^2$-norm on admissible meshes. The cells of meshes under consideration may be very irregular in size. We particularly allow the size of certain cells to remain bounded from below even in the asymptotic limit. For uniform meshes we show that the order of convergence is at least 1 in the energy semi-norm, provided the discrete and continuous solutions exist and the continuous solution has $H^2$ regularity. Y1 - 2022 U6 - https://doi.org/10.20347/WIAS.PREPRINT.2913 ER - TY - JOUR A1 - Sechi, Renata A1 - Weber, Marcus A1 - Heyne, Karsten T1 - MSM building and projection for the analysis of time-resolved spectra JF - Proceedings in Applied Mathematics and Mechanics N2 - Understanding the kinetics between the components of time-resolved spectra is a crucial step in the study of photo-activatedprocesses. However, modeling the kinetics requires usually some a priori knowledge about the system. In our approach, webuild a Markov State Model (MSM) from the spectral data, and obtain a Koopman transition matrix K(t). With genPCCA,an invariant subspace projection, we project the process into its metastable components. The result of the application of gen-PCCA is a transition matrix Kc(t), from which we can read the transition probability between the metastable components of the reaction. We discuss the application of this analysis method to the transient absorption spectrum of brominated Al-corrole Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?https://onlinelibrary.wiley.com/doi/10.1002/pamm.202100102 IS - 21 SP - e202100102 ER - TY - JOUR A1 - Trepte, Philipp A1 - Secker, Christopher A1 - Olivet, Julien A1 - Blavier, Jeremy A1 - Kostova, Simona A1 - Maseko, Sibusiso B A1 - Minia, Igor A1 - Silva Ramos, Eduardo A1 - Cassonnet, Patricia A1 - Golusik, Sabrina A1 - Zenkner, Martina A1 - Beetz, Stephanie A1 - Liebich, Mara J A1 - Scharek, Nadine A1 - Schütz, Anja A1 - Sperling, Marcel A1 - Lisurek, Michael A1 - Wang, Yang A1 - Spirohn, Kerstin A1 - Hao, Tong A1 - Calderwood, Michael A A1 - Hill, David E A1 - Landthaler, Markus A1 - Choi, Soon Gang A1 - Twizere, Jean-Claude A1 - Vidal, Marc A1 - Wanker, Erich E T1 - AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor JF - Molecular Systems Biology N2 - Protein–protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways. KW - Applied Mathematics KW - Computational Theory and Mathematics KW - General Agricultural and Biological Sciences KW - General Immunology and Microbiology KW - General Biochemistry, Genetics and Molecular Biology KW - Information Systems Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1038/s44320-024-00019-8 SN - 1744-4292 VL - 20 IS - 4 SP - 428 EP - 457 PB - Springer Science and Business Media LLC ER - TY - JOUR A1 - Bauer, Wolfgang A1 - Weber, Marcus A1 - Diehl-Wiesenecker, Eva A1 - Galtung, Noa A1 - Prpic, Monika A1 - Somasundaram, Rajan A1 - Tauber, Rudolf A1 - Schwenk, Jochen A1 - Micke, Patrick A1 - Kappert, Kai T1 - Plasma Proteome Fingerprints Reveal Distinctiveness and Clinical Outcome of SARS-CoV-2 Infection JF - Viruses N2 - We evaluated how plasma proteomic signatures in patients with suspected COVID-19 can unravel the pathophysiology, and determine kinetics and clinical outcome of the infection. We identified distinct plasma proteins linked to the presence and course of COVID-19. These plasma proteomic findings may translate to a protein fingerprint, helping to assist clinical management decisions. Y1 - 2021 U6 - https://doi.org/10.3390/v13122456 VL - 13 IS - 12 SP - 2456 ER - TY - GEN A1 - Witzig, Jakob A1 - Beckenbach, Isabel A1 - Eifler, Leon A1 - Fackeldey, Konstantin A1 - Gleixner, Ambros A1 - Grever, Andreas A1 - Weber, Marcus T1 - Mixed-Integer Programming for Cycle Detection in Non-reversible Markov Processes N2 - In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations representing non-reversible biological processes, in particular molecular simulations. Here, the discrete time steps of the simulation are often very small compared to the time scale of interest, i.e., of the whole process. In this setting, the detection of a global cyclic behavior of the process becomes difficult because transitions between individual states may appear almost reversible on the small time scale of the simulation. We address this difficulty using a mixed-integer programming model that allows us to compute a cycle of clusters with maximum net flow, i.e., large forward and small backward probability. For a synthetic genetic regulatory network consisting of a ring-oscillator with three genes, we show that this approach can detect the most productive overall cycle, outperforming classical spectral analysis methods. Our method applies to general non-equilibrium steady state systems such as catalytic reactions, for which the objective value computes the effectiveness of the catalyst. T3 - ZIB-Report - 16-39 KW - Non-reversible Markov Processes KW - NESS KW - Mixed-Integer Programming KW - Markov State Models Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-60353 SN - 1438-0064 ER - TY - JOUR A1 - Witzig, Jakob A1 - Beckenbach, Isabel A1 - Eifler, Leon A1 - Fackeldey, Konstantin A1 - Gleixner, Ambros A1 - Grever, Andreas A1 - Weber, Marcus T1 - Mixed-Integer Programming for Cycle Detection in Non-reversible Markov Processes JF - Multiscale Modeling and Simulation N2 - In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations representing non-reversible biological processes, in particular molecular simulations. Here, the discrete time steps of the simulation are often very small compared to the time scale of interest, i.e., of the whole process. In this setting, the detection of a global cyclic behavior of the process becomes difficult because transitions between individual states may appear almost reversible on the small time scale of the simulation. We address this difficulty using a mixed-integer programming model that allows us to compute a cycle of clusters with maximum net flow, i.e., large forward and small backward probability. For a synthetic genetic regulatory network consisting of a ring-oscillator with three genes, we show that this approach can detect the most productive overall cycle, outperforming classical spectral analysis methods. Our method applies to general non-equilibrium steady state systems such as catalytic reactions, for which the objective value computes the effectiveness of the catalyst. KW - Markov State Models KW - NESS KW - Non-reversible Markov Processes KW - Mixed-Integer Programming Y1 - 2018 U6 - https://doi.org/10.1137/16M1091162 SN - 1438-0064 VL - 16 IS - 1 SP - 248 EP - 265 ER - TY - JOUR A1 - Lelievre, Tony A1 - Stoltz, Gabriel A1 - Zhang, Wei T1 - Multiple projection MCMC algorithms on submanifolds JF - IMA Journal of Numerical Analysis N2 - We propose new Markov Chain Monte Carlo algorithms to sample probability distributions on submanifolds, which generalize previous methods by allowing the use of set-valued maps in the proposal step of the MCMC algorithms. The motivation for this generalization is that the numerical solvers used to project proposed moves to the submanifold of interest may find several solutions. We show that the new algorithms indeed sample the target probability measure correctly, thanks to some carefully enforced reversibility property. We demonstrate the interest of the new MCMC algorithms on illustrative numerical examples. Y1 - 2022 U6 - https://doi.org/10.1093/imanum/drac006 ER - TY - JOUR A1 - Zhang, Wei A1 - Li, Tiejun A1 - Schütte, Christof T1 - Solving eigenvalue PDEs of metastable diffusion processes using artificial neural networks JF - Journal of Computational Physics N2 - In this paper, we consider the eigenvalue PDE problem of the infinitesimal generators of metastable diffusion processes. We propose a numerical algorithm based on training artificial neural networks for solving the leading eigenvalues and eigenfunctions of such high-dimensional eigenvalue problem. The algorithm is useful in understanding the dynamical behaviors of metastable processes on large timescales. We demonstrate the capability of our algorithm on a high-dimensional model problem, and on the simple molecular system alanine dipeptide. Y1 - 2021 U6 - https://doi.org/10.1016/j.jcp.2022.111377 VL - 465 ER -