@article{ReidelbachWeberImhof2018, author = {Reidelbach, Marco and Weber, Marcus and Imhof, Petra}, title = {Prediction of perturbed proton transfer networks}, volume = {13}, journal = {PLoS ONE}, number = {12}, doi = {https://doi.org/10.1371/journal.pone.0207718}, pages = {e0207718 -- e0207718}, year = {2018}, abstract = {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.}, language = {en} } @article{SpahnDelVecchioLabuzetal.2017, author = {Spahn, Viola and Del Vecchio, Giovanna and Labuz, Dominika and Rodriguez-Gaztelumendi, Antonio and Massaly, N. and Temp, Julia and Durmaz, Vedat and Sabri, P. and Reidelbach, Marco and Machelska, Halina and Weber, Marcus and Stein, Christoph}, title = {A nontoxic pain killer designed by modeling of pathological receptor conformations}, volume = {355}, journal = {Science}, number = {6328}, doi = {10.1126/science.aai8636}, pages = {966 -- 969}, year = {2017}, language = {en} } @inproceedings{IgdeWoelkRoeblitzetal.2015, author = {Igde, Sinaida and W{\"o}lk, Hendrik and R{\"o}blitz, Susanna and Reidelbach, Marco and Weber, Marcus and Hartmann, Laura}, title = {Identifying Multivalent Binding Kinetics of Precision Glycomacromolecules: A Kinetic Study Using kinITC}, booktitle = {M{\"u}nster Symposium on Cooperative Effects 2015 - SFB 858, at Westf{\"a}lische Wilhelms-Universit{\"a}t M{\"u}nster, 2015}, year = {2015}, abstract = {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.}, language = {en} } @article{SpahnDelVecchioRodriguezGaztelumendietal.2018, author = {Spahn, Viola and Del Vecchio, Giovanna and Rodriguez-Gaztelumendi, Antonio and Temp, Julia and Labuz, Dominika and Kloner, Michael and Reidelbach, Marco and Machelska, Halina and Weber, Marcus and Stein, Christoph}, title = {Opioid receptor signaling, analgesic and side effects induced by a computationally designed pH-dependent agonist}, volume = {8}, journal = {Scientific Reports}, publisher = {Springer Nature}, pages = {8965}, year = {2018}, abstract = {Novel pain killers without adverse effects are urgently needed.}, language = {en} } @phdthesis{Reidelbach2019, author = {Reidelbach, Marco}, title = {Optimal Network Generation for the Simulation of Proton Transfer Processes}, year = {2019}, language = {en} } @misc{WeberDurmazSabrietal.2017, author = {Weber, Marcus and Durmaz, Vedat and Sabri, Peggy and Reidelbach, Marco}, title = {Supplementary simulation data for Science Manuscript ai8636}, doi = {10.12752/5.MWB.1.0}, year = {2017}, abstract = {The simulation data has been produced by Vedat Durmaz, Peggy Sabri and Marco Reidelbach inside the "Computational Molecular Design" Group headed by Marcus Weber at Zuse-Institut Berlin, Takustr. 7, D-14195 Berlin, Germany. The file contains classical simulation data for different fentanyl derivates in the MOR binding pocket at different pHs. It also includes instruction files for quantum-chemical pKa-value estimations and a description of how we derived the pKa-values from the Gaussian09 log-files.}, language = {en} } @article{MarcoMarcus2025, author = {Marco, Reidelbach and Marcus, Weber}, title = {From Documentation to Discovery - MaRDMO and the MaRDI Ecosystem}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16735889}, year = {2025}, language = {en} } @article{FischerGerberKopruckietal.2025, author = {Fischer, Kristina and Gerber, Anja and Koprucki, Thomas and Noback, Andres and Reidelbach, Marco and Schrade, Torsten and Thiery, Florian}, title = {Windows on Data: Federating Research Data with FAIR Digital Objects and Linked Open Data}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16736222}, year = {2025}, language = {en} } @article{BiernackaCastroFritzschetal.2025, author = {Biernacka, Katarzyna and Castro, Leyla Jael and Fritzsch, Bernadette and Grossmann, Yves Vincent and Reidelbach, Marco and Struck, Alexander and Lanza, Giacomo and Walter, David and Ulusoy, Inga}, title = {From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16735302}, year = {2025}, language = {en} } @inproceedings{SchemberaWuebbelingKleikampetal.2025, author = {Schembera, Bj{\"o}rn and W{\"u}bbeling, Frank and Kleikamp, Hendrik and Schmidt, Burkhard and Shehu, Aurela and Reidelbach, Marco and Biedinger, Christine and Fiedler, Jochen and Koprucki, Thomas and Iglezakis, Dorothea and G{\"o}ddeke, Dominik}, title = {Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics}, volume = {2331}, booktitle = {Metadata and Semantic Research. MTSR 2024}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031819735}, issn = {1865-0929}, doi = {10.1007/978-3-031-81974-2_8}, pages = {95 -- 109}, year = {2025}, abstract = {Mathematical models and algorithms are an essential part of mathematical research data, as they are epistemically grounding numerical data. To make this research data FAIR, we present how two previously distinct ontologies, MathAlgoDB for algorithms and MathModDB for models, were merged and extended into a living knowledge graph as the key outcome. This was achieved by connecting the ontologies through computational tasks that correspond to algorithmic tasks. Moreover, we show how models and algorithms can be enriched with subject-specific metadata, such as matrix symmetry or model linearity, essential for defining workflows and determining suitable algorithms. Additionally, we propose controlled vocabularies to be added, along with a new class that differentiates base quantities from specific use case quantities. We illustrate the capabilities of the developed knowledge graph using two detailed examples from different application areas of applied mathematics, having already integrated over 250 research assets into the knowledge graph.}, language = {en} }