TY - JOUR A1 - Weber, Marcus A1 - Fackeldey, Konstantin T1 - Local Refinements in Classical Molecular Dynamics Simulations JF - J. Phys. Conf. Ser. Y1 - 2014 VL - 490 SP - 012016 ER - TY - JOUR A1 - Andrae, Karsten A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Scharkoi, Olga A1 - Weber, Marcus T1 - Medizin aus dem Computer JF - Der Anaesthesist Y1 - 2013 U6 - https://doi.org/10.1007/s00101-013-2202-x VL - 62 IS - 7 SP - 561 EP - 557 PB - Springer 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 - GEN A1 - Fackeldey, Konstantin T1 - Challenges in Atomistic-to-Continuum Coupling T2 - ZIB Report N2 - This paper is concerned with the design, analysis, and implementation of concurrent coupling approaches where different (atomic and continuous) models are used simultaneously within a single simulation process. Thereby, several problems or pitfalls can happen, for example, the reflection of molecular movements at the “boundary” between the atomic and continuum regions which leads to an unphysical increase in energy in the atomic model. We investigate the problems with the aim of giving an introduction into this field and preventing errors for scientists starting their research towards multiscale methods. Y1 - 2010 U6 - https://doi.org/10.1155/2015/834517 VL - 2010 ET - 10-12 ER - TY - THES A1 - Fackeldey, Konstantin T1 - Crossing the Scales in Structural Mechanics and Molecular Research Y1 - 2015 ER - 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 - Gorgulla, Christoph A1 - Çınaroğlu, Süleyman A1 - Fischer, Patrick D. A1 - Fackeldey, Konstantin A1 - Wagner, Gerhard A1 - Arthanari, Haribabu T1 - VirtualFlow Ants—Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization JF - Special Issue Artificial Intelligence & Deep Learning Approaches for Structural Bioinformatics N2 - The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.3390/ijms22115807 VL - 22 IS - 11 SP - 5807 ER - TY - JOUR A1 - Fackeldey, Konstantin A1 - Gorgulla, Christoph A1 - Weber, Marcus T1 - Neue Medikamente dank Supercomputern JF - Spektrum der Wissenschaft N2 - Die aktuelle Pandemie verdeutlicht, wie wichtig es ist, rasch geeignete Arzneimittel zu finden. In Computer­simulationen gelingt das erheblich schneller als im Labor. Gegen das Coronavirus ließen sich auf diese Weise bereits Wirkstoffkandidaten identifizieren. Y1 - 2021 IS - 11 SP - 40 EP - 46 ER - TY - JOUR A1 - Birk, Ralph A1 - Raharinirina, N. Alexia A1 - Fackeldey, Konstantin A1 - Richter, Tonio Sebastian A1 - Weber, Marcus T1 - Inferring cultural and social processes based on patterns of statistical relationships between Synodal texts N2 - In this paper, we explore the relationship patterns between Ancient Egyptian texts of the corpus ``Synodal decrees'', which are originating between 243 and 185 BCE, during the Ptolemaic period. Particularly, we are interested in analyzing the grammatical features of the different texts. Conventional data analysis methods such as correspondence Analysis are very useful to explore the patterns of statistical interdependence between categories of variables. However, it is based on a PCA-like dimension-reduction method and turned out to be unsuitable for our dataset due to the high dimensionality of our data representations. Additionally, the similarity between pairs of texts and pairs of grammatical features is observed through the distance between their representation, but the degree of association between a particular grammatical feature and a text is not. Here, we applied a qualitative Euclidean embedding method that provides a new Euclidean representation of the categories of variables. This new representation of the categories is constructed in such a way that all the patterns of statistical interdependence, similarity, and association, are seen through the Euclidean distance between them. Nevertheless, the PCA-like dimension-reduction method also performed poorly on our new representation. Therefore, we obtained a two-dimensional visualization using non-linear methods such UMAP or t-SNE. Although these dimension-reduction methods reduced the interpretability of interpoint distances, we were still able to identify important similarity patterns between the Synodal text as well as their association patterns with the grammatical features. Y1 - 2021 ER - TY - JOUR A1 - Gorgulla, Christoph A1 - Nigam, AkshatKumar A1 - Koop, Matt A1 - Selim Çınaroğlu, Süleyman A1 - Secker, Christopher A1 - Haddadnia, Mohammad A1 - Kumar, Abhishek A1 - Malets, Yehor A1 - Hasson, Alexander A1 - Li, Minkai A1 - Tang, Ming A1 - Levin-Konigsberg, Roni A1 - Radchenko, Dmitry A1 - Kumar, Aditya A1 - Gehev, Minko A1 - Aquilanti, Pierre-Yves A1 - Gabb, Henry A1 - Alhossary, Amr A1 - Wagner, Gerhard A1 - Aspuru-Guzik, Alán A1 - Moroz, Yurii S. A1 - Fackeldey, Konstantin A1 - Arthanari, Haribabu T1 - VirtualFlow 2.0 - The Next Generation Drug Discovery Platform Enabling Adaptive Screens of 69 Billion Molecules JF - bioRxiv KW - preprint Y1 - 2023 U6 - https://doi.org/10.1101/2023.04.25.537981 ER - TY - JOUR A1 - Raharinirina, Nomenjanahary Alexia A1 - Sunkara, Vikram A1 - von Kleist, Max A1 - Fackeldey, Konstantin A1 - Weber, Marcus T1 - Multi-Input data ASsembly for joint Analysis (MIASA): A framework for the joint analysis of disjoint sets of variables JF - PLOS ONE Y1 - 2024 U6 - https://doi.org/10.1371/journal.pone.0302425 VL - 19 IS - 5 PB - Public Library of Science ER - TY - JOUR A1 - Coomber, Celvic A1 - Chewle, Surahit A1 - Secker, Christopher A1 - Fackeldey, Konstantin A1 - Weber, Marcus A1 - Winkelmann, Stefanie A1 - Schütte, Christof A1 - Sunkara, Vikram T1 - Investigating Endogenous Opioids Unravels the Mechanisms Behind Opioid-Induced Constipation, a Mathematical Modeling Approach JF - International Journal of Molecular Sciences N2 - Endogenous opioids, such as Endomorphin-2, are not typically associated with severe constipation, unlike pharmaceutical opioids, which induce opioid-induced constipation (OIC) by activating μ-opioid receptors in the gastrointestinal tract. In this study, we present a mathematical model, which integrates the serotonergic and opioid pathways, simulating the interaction between serotonin and opioid signaling within the enteric nervous system (ENS). The model explores the mechanisms underlying OIC, with a focus on the change in adenylyl cyclase (AC) activity, cAMP accumulation, and the distinct functionalities of Endomorphin-2 compared to commonly used pharmaceutical opioids. We study the effects of Morphine, Fentanyl, and Methadone and contrast them with Endomorphin-2. Our findings reveal that opioids do not perturb the signaling of serotonin, but only the activity of AC, suggesting that serotonin levels have no influence on improving opioid-induced constipation. Furthermore, this study reveals that the primary difference between endogenous and pharmaceutical opioids is their degradation rates. This finding shows that modulating opioid degradation rates significantly improves cAMP recovery. In conclusion, our insights steer towards exploring opioid degrading enzymes, localized to the gut, as a strategy for mitigating OIC. Y1 - 2025 U6 - https://doi.org/10.3390/ijms26136207 VL - 26 IS - 13 ER - TY - GEN A1 - Raharinirina, N. Alexia A1 - Weber, Marcus A1 - Birk, Ralph A1 - Fackeldey, Konstantin A1 - Klasse, Sarah M. A1 - Richter, Tonio Sebastian T1 - Different Tools and Results for Correspondence Analysis N2 - This is a list of codes generated from ancient egyptian texts. The codes are used for a correspondence analysis (CA). Codes and CA software are available from the linked webpage. Y1 - 2021 U6 - https://doi.org/10.12752/8257 N1 - A detailed description of the software can be found in the code repository at https://github.com/AlexiaNomena/Correspondence_Analysis_User_Friendly (repository version of CA software might include updates). ER - TY - JOUR A1 - Nitzke, Isabel A1 - Fackeldey, Konstantin A1 - Vrabec, Jadran T1 - Long range corrections for inhomogeneous fluids containing a droplet or a bubble JF - Molecular Simulation N2 - Long range corrections for molecular simulations of inhomogeneous fluids with a spherical interface are presented. Correction terms for potential energy, force and virial are derived for the monatomic Lennard–Jones fluid. The method is generalised to the Mie potential and arbitrary molecular structures, employing a numerically efficient centre of mass cut-off scheme. The results are validated by a series of droplet simulations for one-centre and two-centre Lennard–Jones fluids with different cut-off radii rc. Systems with rc=8σ provide a check of self-consistence. Further, a system containing a bubble is investigated for the one-centre Lennard–Jones fluid. The equilibrium properties are almost completely independent on the cut-off radius. In comparison with vapour–liquid equilibrium data for systems without a curved interface, all properties show the expected behaviour. Simulation data are used to approximate the surface tension, which is in good agreement with the findings for planar interfaces, thus verifying the present corrections. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1080/08927022.2021.1954639 SP - 1 EP - 14 ER - TY - JOUR A1 - Secker, Christopher A1 - Fackeldey, Konstantin A1 - Weber, Marcus A1 - Ray, Sourav A1 - Gorgulla, Christoph A1 - Schütte, Christof T1 - Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists JF - Journal of Cheminformatics N2 - Opioids are essential pharmaceuticals due to their analgesic properties, however, lethal side effects, addiction, and opioid tolerance are extremely challenging. The development of novel molecules targeting the μ-opioid receptor (MOR) in inflamed, but not in healthy tissue, could significantly reduce these unwanted effects. Finding such novel molecules can be achieved by maximizing the binding affinity to the MOR at acidic pH while minimizing it at neutral pH, thus combining two conflicting objectives. Here, this multi-objective optimal affinity approach is presented, together with a virtual drug discovery pipeline for its practical implementation. When applied to finding pH-specific drug candidates, it combines protonation state-dependent structure and ligand preparation with high-throughput virtual screening. We employ this pipeline to characterize a set of MOR agonists identifying a morphine-like opioid derivative with higher predicted binding affinities to the MOR at low pH compared to neutral pH. Our results also confirm existing experimental evidence that NFEPP, a previously described fentanyl derivative with reduced side effects, and recently reported β-fluorofentanyls and -morphines show an increased specificity for the MOR at acidic pH when compared to fentanyl and morphine. We further applied our approach to screen a >50K ligand library identifying novel molecules with pH-specific predicted binding affinities to the MOR. The presented differential docking pipeline can be applied to perform multi-objective affinity optimization to identify safer and more specific drug candidates at large scale. Y1 - 2023 U6 - https://doi.org/10.1186/s13321-023-00746-4 VL - 15 ER - TY - JOUR A1 - Gorgulla, Christoph A1 - Jayaraj, Abhilash A1 - Fackeldey, Konstantin A1 - Arthanari, Haribabu T1 - Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches JF - Current Opinion in Chemical Biology N2 - Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein–protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties. Y1 - 2022 U6 - https://doi.org/10.1016/j.cbpa.2022.102156 VL - 69 SP - 102156 EP - 102156-12 ER - TY - JOUR A1 - Sechi, Renata A1 - Fackeldey, Konstantin A1 - Chewle, Surahit A1 - Weber, Marcus T1 - SepFree NMF: A Toolbox for Analyzing the Kinetics of Sequential Spectroscopic Data JF - Algorithms N2 - This work addresses the problem of determining the number of components from sequential spectroscopic data analyzed by non-negative matrix factorization without separability assumption (SepFree NMF). These data are stored in a matrix M of dimension “measured times” versus “measured wavenumbers” and can be decomposed to obtain the spectral fingerprints of the states and their evolution over time. SepFree NMF assumes a memoryless (Markovian) process to underline the dynamics and decomposes M so that M=WH, with W representing the components’ fingerprints and H their kinetics. However, the rank of this decomposition (i.e., the number of physical states in the process) has to be guessed from pre-existing knowledge on the observed process. We propose a measure for determining the number of components with the computation of the minimal memory effect resulting from the decomposition; by quantifying how much the obtained factorization is deviating from the Markovian property, we are able to score factorizations of a different number of components. In this way, we estimate the number of different entities which contribute to the observed system, and we can extract kinetic information without knowing the characteristic spectra of the single components. This manuscript provides the mathematical background as well as an analysis of computer generated and experimental sequentially measured Raman spectra. Y1 - 2022 U6 - https://doi.org/10.3390/a15090297 VL - 15 IS - 9 SP - 297 ER - TY - JOUR A1 - Ray, Sourav A1 - Fackeldey, Konstantin A1 - Stein, Christoph A1 - Weber, Marcus T1 - Coarse Grained MD Simulations of Opioid interactions with the µ-opioid receptor and the surrounding lipid membrane JF - Biophysica N2 - In our previous studies, a new opioid (NFEPP) was developed to only selectively bind to the 𝜇-opoid receptor (MOR) in inflamed tissue and thus avoid the severe side effects of fentanyl. We know that NFEPP has a reduced binding affinity to MOR in healthy tissue. Inspired by the modelling and simulations performed by Sutcliffe et al., we present our own results of coarse-grained molecular dynamics simulations of fentanyl and NFEPP with regards to their interaction with the 𝜇-opioid receptor embedded within the lipid cell membrane. For technical reasons, we have slightly modified Sutcliffe’s parametrisation of opioids. The pH-dependent opioid simulations are of interest because while fentanyl is protonated at the physiological pH, NFEPP is deprotonated due to its lower pKa value than that of fentanyl. Here, we analyse for the first time whether pH changes have an effect on the dynamical behaviour of NFEPP when it is inside the cell membrane. Besides these changes, our analysis shows a possible alternative interaction of NFEPP at pH 7.4 outside the binding region of the MOR. The interaction potential of NFEPP with MOR is also depicted by analysing the provided statistical molecular dynamics simulations with the aid of an eigenvector analysis of a transition rate matrix. In our modelling, we see differences in the XY-diffusion profiles of NFEPP compared with fentanyl in the cell membrane. Y1 - 2023 U6 - https://doi.org/10.3390/biophysica3020017 VL - 3 IS - 2 SP - 263 EP - 275 ER - TY - JOUR A1 - Raharinirina, N. Alexia A1 - Fackeldey, Konstantin A1 - Weber, Marcus T1 - Qualitative Euclidean embedding of Disjoint Sets of Points N2 - We consider two disjoint sets of points with a distance metric, or a proximity function, associated with each set. If each set can be separately embedded into separate Euclidean spaces, then we provide sufficient conditions for the two sets to be jointly embedded in one Euclidean space. In this joint Euclidean embedding, the distances between the points are generated by a specific relation-preserving function. Consequently, the mutual distances between two points of the same set are specific qualitative transformations of their mutual distances in their original space; the pairwise distances between the points of different sets can be constructed from an arbitrary proximity function (might require scaling). Y1 - 2022 UR - https://arxiv.org/abs/2212.00058 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 -