@article{ReidelbachWeberImhof, author = {Reidelbach, Marco and Weber, Marcus and Imhof, Petra}, title = {Prediction of perturbed proton transfer networks}, series = {PLoS ONE}, volume = {13}, journal = {PLoS ONE}, number = {12}, doi = {https://doi.org/10.1371/journal.pone.0207718}, pages = {e0207718 -- e0207718}, 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{SpahnDelVecchioRodriguezGaztelumendietal., 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}, series = {Scientific Reports}, volume = {8}, journal = {Scientific Reports}, publisher = {Springer Nature}, pages = {8965}, abstract = {Novel pain killers without adverse effects are urgently needed.}, language = {en} }