TY - GEN A1 - Weber, Marcus A1 - Becker, Roland A1 - Köppen, Robert A1 - Durmaz, Vedat T1 - Classical hybrid Monte-Carlo simulations of the interconversion of hexabromocyclododecane N2 - In this paper, we investigate the interconversion processes of the major flame retardant -- 1,2,5,6,9,10-hexabromocyclododecane (HBCD) -- by the means of statistical thermodynamics based on classical force-fields. Three ideas will be presented. First, the application of classical hybrid Monte-Carlo simulations for quantum mechanical processes will be justified. Second, the problem of insufficient convergence properties of hybrid Monte-Carlo methods for the generation of low temperature canonical ensembles will be solved by an interpolation approach. Furthermore, it will be shown how free energy differences can be used for a rate matrix computation. The results of our numerical simulations will be compared to experimental results. T3 - ZIB-Report - 07-31 KW - Markov process KW - molecular dynamics KW - rate matrix Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-10308 SN - 1438-0064 ER - TY - JOUR A1 - Spahn, Viola A1 - Del Vecchio, Giovanna A1 - Labuz, Dominika A1 - Rodriguez-Gaztelumendi, Antonio A1 - Massaly, N. A1 - Temp, Julia A1 - Durmaz, Vedat A1 - Sabri, P. A1 - Reidelbach, Marco A1 - Machelska, Halina A1 - Weber, Marcus A1 - Stein, Christoph T1 - A nontoxic pain killer designed by modeling of pathological receptor conformations JF - Science Y1 - 2017 U6 - https://doi.org/10.1126/science.aai8636 VL - 355 IS - 6328 SP - 966 EP - 969 ER - TY - CHAP A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Weber, Marcus ED - Mode, Ch. T1 - A rapidly Mixing Monte Carlo Method for the Simulation of Slow Molecular Processes T2 - Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science Y1 - 2011 PB - InTech ER - TY - JOUR A1 - Weber, Marcus A1 - Becker, Roland A1 - Köppen, Robert A1 - Durmaz, Vedat T1 - Classical hybrid Monte-Carlo simulations of the interconversion of hexabromocyclododecane JF - Journal of Molecular Simulation Y1 - 2008 VL - 34 IS - 7 SP - 727 EP - 736 ER - TY - JOUR A1 - Köppen, Robert A1 - Riedel, Juliane A1 - Proske, Matthias A1 - Drzymala, Sarah A1 - Rasenko, Tatjana A1 - Durmaz, Vedat A1 - Weber, Marcus A1 - Koch, Matthias T1 - Photochemical trans-/cis-isomerization and quantification of zearalenone in edible oils JF - J. Agric. Food Chem. Y1 - 2012 U6 - https://doi.org/10.1021/jf3037775 VL - 60 SP - 11733 EP - 11740 ER - TY - JOUR A1 - Durmaz, Vedat A1 - Weber, Marcus A1 - Becker, Roland T1 - How to Simulate Affinities for Host-Guest Systems Lacking Binding Mode Information: application to the liquid chromatographic separation of hexabromocyclododecane stereoisomers JF - Journal of Molecular Modeling Y1 - 2012 U6 - https://doi.org/10.1007/s00894-011-1239-5 VL - 18 SP - 2399 EP - 2408 ER - TY - JOUR A1 - Köppen, Robert A1 - Becker, Roland A1 - Weber, Marcus A1 - Durmaz, Vedat A1 - Nehls, Irene T1 - HBCD stereoisimers: Thermal interconversion and enantiospecific trace analysis in biota JF - Organohalogen Compounds Y1 - 2009 VL - 70 SP - 910 EP - 913 ER - TY - JOUR A1 - Weber, Marcus A1 - Durmaz, Vedat A1 - Becker, Roland A1 - Esslinger, Susanne T1 - Predictive Identification of Pentabromocyclododecane (PBCD) Isomers with high Binding Affinity to hTTR JF - Organohalogen Compounds Y1 - 2009 VL - 71 SP - 247 EP - 252 ER - TY - THES A1 - Durmaz, Vedat T1 - Theoretical Investigations on HBCD and PBCD Y1 - 2009 ER - TY - JOUR A1 - Gorgulla, Christoph A1 - Das, Krishna M. Padmanabha A1 - Leigh, Kendra E A1 - Cespugli, Marco A1 - Fischer, Patrick D. A1 - Wang, Zi-Fu A1 - Tesseyre, Guilhem A1 - Pandita, Shreya A1 - Shnapir, Alex A1 - Calderaio, Anthony A1 - Hutcheson, Colin A1 - Gechev, Minko A1 - Rose, Alexander A1 - Lewis, Noam A1 - Yaffe, Erez A1 - Luxenburg, Roni A1 - Herce, Henry D. A1 - Durmaz, Vedat A1 - Halazonetis, Thanos D. A1 - Fackeldey, Konstantin A1 - Patten, Justin J. A1 - Chuprina, Alexander A1 - Dziuba, Igor A1 - Plekhova, Alla A1 - Moroz, Yurii A1 - Radchenko, Dmytro A1 - Tarkhanova, Olga A1 - Yavnyuk, Irina A1 - Gruber, Christian C. A1 - Yust, Ryan A1 - Payne, Dave A1 - Näär, Anders M. A1 - Namchuk, Mark N. A1 - Davey, Robert A. A1 - Wagner, Gerhard A1 - Kinney, Jamie A1 - Arthanari, Haribabu T1 - A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening JF - iScience N2 - Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed in silico screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 in silico hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development. Y1 - 2021 U6 - https://doi.org/10.26434/chemrxiv.12682316 VL - 24 IS - 2 SP - 102021 PB - CellPress ER - TY - THES A1 - Durmaz, Vedat T1 - Atomistic Binding Free Energy Estimations for Biological Host–Guest Systems N2 - Accurate quantifications of protein–ligand binding affinities by means of in silico methods increasingly gain importance in various scientific branches including toxicology and pharmacology. In silico techniques not only are generally less demanding than laboratory experiments regarding time as well as cost, in particular, if binding assays or synthesis protocols need to be developed in advance. At times, they also provide the only access to risk assessments on novel chemical compounds arising from biotic or abiotic degradation of anthropogenic substances. However, despite the continuous technological and algorithmic progress over the past decades, binding free energy estimations through molecular dynamics simulations still pose an enormous computational challenge owed to the mathematical complexity of solvated macromolecular systems often consisting of hundreds of thousands of atoms. The goals of this thesis can roughly be divided into two categories dealing with different aspects of host–guest binding quantification. On the one side algorithmic strategies for a comprehensive exploration and decomposition of conformational space in conjunction with an automated selection of representative molecular geometries and binding poses have been elaborated providing initial structures for free energy calculations. In light of the dreaded trapping problem typically associated with molecular dynamics simulations, the focus was laid on a particularly systematic generation of representatives covering a broad range of physically accessible molecular conformations and interaction modes. On the other side and ensuing from these input geometries, binding affinity models based on the linear interaction energy (LIE) method have been developed for a couple of (bio)molecular systems. The applications included a successful prediction of the liquid-chromatographic elution order as well as retention times of highly similar hexabromocyclododecane (HBCD) stereoisomers, a novel empirical LIE–QSAR hybrid binding affinity model related to the human estrogen receptor α (ERα), and, finally, the (eco)toxicological prioritization of transformation products originating from the antibiotic sulfamethoxazole with respect to their binding affinities to the bacterial enzyme dihydropteroate synthase. Altogether, a fully automated approach to binding mode and affinity estimation has been presented that is content with an arbitrary geometry of a small molecule under observation and a spatial vector specifying the binding site of a potential target molecule. According to our studies, it is superior to conventional docking and thermodynamic average methods and primarily suggesting binding free energy calculation on the basis of several heavily distinct complex geometries. Both chromatographic retention times of HBCD and binding affinities to ERα yielded squared coefficients of correlation with experimental results significantly higher than 0.8. Approximately 85 % (100 %) of predicted receptor–ligand binding modes deviated less than 1.53 Å (2.05 Å) from available crystallographic structures. KW - molecular modelling KW - molecular dynamics KW - molecular simulation KW - binding affinity KW - prediction KW - free energy KW - receptor ligand KW - retention time KW - liquid chromatography Y1 - 2016 UR - http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000103765 PB - FU Dissertationen Online ER - TY - GEN A1 - Weber, Marcus A1 - Durmaz, Vedat A1 - Sabri, Peggy A1 - Reidelbach, Marco T1 - Supplementary simulation data for Science Manuscript ai8636 N2 - 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. Y1 - 2017 U6 - https://doi.org/10.12752/5.MWB.1.0 N1 - GROMACS trajectories and GAUSSIAN files of MOR and fentanyl derivates ER - TY - JOUR A1 - Koschek, A1 - Durmaz, Vedat A1 - Krylova, A1 - Wieczorek, A1 - Gupta, Pooja A1 - Richter, A1 - Bujotzek, Alexander A1 - Fischer, A1 - Haag, Rainer A1 - Freund, A1 - Weber, Marcus A1 - Rademann, T1 - Peptide polymer ligands for a tandem WW-domain, a soft multivalent protein-protein interaction: lessons on the thermodynamic fitness of flexible ligands JF - Beilstein J. Org. Chem. Y1 - 2015 VL - 11 SP - 837 EP - 847 ER - TY - JOUR A1 - Durmaz, Vedat A1 - Weber, Marcus A1 - Meyer, A1 - Mückter, T1 - Computergestützte Simulationen zur Abschätzung gesundheitlicher Risiken durch anthropogene Spurenstoffe der Wassermatrix JF - KA Korrespondenz Abwasser, Abfall Y1 - 2015 VL - 3/15 SP - 264 EP - 267 ER - TY - JOUR A1 - Andrae, Karsten A1 - Merkel, Stefan A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Köppen, Robert A1 - Weber, Marcus A1 - Koch, Matthias T1 - Investigation of the Ergopeptide Epimerization Process JF - Computation N2 - Ergopeptides, like ergocornine and a-ergocryptine, exist in an S- and in an R-configuration. Kinetic experiments imply that certain configurations are preferred depending on the solvent. The experimental methods are explained in this article. Furthermore, computational methods are used to understand this configurational preference. Standard quantum chemical methods can predict the favored configurations by using minimum energy calculations on the potential energy landscape. However, the explicit role of the solvent is not revealed by this type of methods. In order to better understand its influence, classical mechanical molecular simulations are applied. It appears from our research that “folding” the ergopeptide molecules into an intermediate state (between the S- and the R-configuration) is mechanically hindered for the preferred configurations. Y1 - 2014 U6 - https://doi.org/10.3390/computation2030102 VL - 2 IS - 3 SP - 102 EP - 111 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 - Durmaz, Vedat A1 - Schmidt, Sebastian A1 - Sabri, Peggy A1 - Piechotta, Christian A1 - Weber, Marcus T1 - A hands-off linear interaction energy approach to binding mode and affinity estimation of estrogens JF - Journal of Chemical Information and Modeling Y1 - 2013 VL - 53 IS - 10 SP - 2681 EP - 2688 ER - TY - JOUR A1 - Durmaz, Vedat T1 - Markov model-based polymer assembly from force field-parameterized building blocks JF - Journal of Computer-Aided Molecular Design N2 - A conventional by hand construction and parameterization of a polymer model for the purpose of molecular simulations can quickly become very workintensive and time-consuming. Using the example of polyglycerol, I present a polymer decompostion strategy yielding a set of five monomeric residues that are convenient for an instantaneous assembly and subsequent force field simulation of a polyglycerol polymer model. Force field parameters have been developed in accordance with the classical Amber force field. Partial charges of each unit were fitted to the electrostatic potential using quantumchemical methods and slightly modified in order to guarantee a neutral total polymer charge. In contrast to similarly constructed models of amino acid and nucleotide sequences, the glycerol building blocks may yield an arbitrary degree of bifurcations depending on the underlying probabilistic model. The iterative development of the overall structure as well as the relation of linear to branching units is controlled by a simple Markov model which is presented with few algorithmic details. The resulting polymer is highly suitable for classical explicit water molecular dynamics simulations on the atomistic level after a structural relaxation step. Moreover, the decomposition strategy presented here can easily be adopted to many other (co)polymers. Y1 - 2015 U6 - https://doi.org/10.1007/s10822-014-9817-0 VL - 29 SP - 225 EP - 232 ER - TY - JOUR A1 - Heye, Katharina A1 - Becker, Dennis A1 - Lütke-Eversloh, Christian A1 - Durmaz, Vedat A1 - Ternes, Thomas A1 - Oetken, Matthias A1 - Oehlmann, Jörg T1 - Effects of carbamazepine and two of its metabolites on the non-biting midge Chironomus riparius in a sediment full life cycle toxicity test JF - Water Research N2 - The antiepileptic drug carbamazepine (CBZ) and its main metabolites carbamazepine-10,11-epoxide (EP-CBZ) and 10,11-dihydro-10,11-dihydroxy-carbamazepine (DiOH-CBZ) were chosen as test substances to assess chronic toxicity on the non-biting midge Chironomus riparius. All three substances were tested in a 40-day sediment full life cycle test (according to OECD 233) in which mortality, emergence, fertility, and clutch size were evaluated. In addition, these parameters were integrated into the population growth rate to reveal population relevant effects. With an LC50 of 0.203 mg/kg (time-weighted mean), the metabolite EP-CBZ was significantly more toxic than the parent substance CBZ (LC50: 1.11 mg/kg). Especially mortality, emergence, and fertility showed to be sensitive parameters under the exposure to CBZ and EP-CBZ. By using classical molecular dynamics (MD) simulations, the binding of CBZ to the ecdysone receptor was investigated as one possible mode of action but showed to be unlikely. The second metabolite DiOH-CBZ did not show any effects within the tested concentration rage (0.171 – 1.22 mg/kg). Even though CBZ was less toxic compared to EP-CBZ, CBZ is found in the environment at much higher concentrations and causes therefore a higher potential risk for sediment dwelling organisms compared to its metabolites. Nevertheless, the current study illustrates the importance of including commonly found metabolites into the risk assessment of parent substances. Y1 - 2016 VL - 98 SP - 19 EP - 27 ER - TY - JOUR A1 - Schimunek, Johannes A1 - Seidl, Philipp A1 - Elez, Katarina A1 - Hempel, Tim A1 - Le, Tuan A1 - Noé, Frank A1 - Olsson, Simon A1 - Raich, Lluís A1 - Winter, Robin A1 - Gokcan, Hatice A1 - Gusev, Filipp A1 - Gutkin, Evgeny M. A1 - Isayev, Olexandr A1 - Kurnikova, Maria G. A1 - Narangoda, Chamali H. A1 - Zubatyuk, Roman A1 - Bosko, Ivan P. A1 - Furs, Konstantin V. A1 - Karpenko, Anna D. A1 - Kornoushenko, Yury V. A1 - Shuldau, Mikita A1 - Yushkevich, Artsemi A1 - Benabderrahmane, Mohammed B. A1 - Bousquet-Melou, Patrick A1 - Bureau, Ronan A1 - Charton, Beatrice A1 - Cirou, Bertrand C. A1 - Gil, Gérard A1 - Allen, William J. A1 - Sirimulla, Suman A1 - Watowich, Stanley A1 - Antonopoulos, Nick A1 - Epitropakis, Nikolaos A1 - Krasoulis, Agamemnon A1 - Itsikalis, Vassilis A1 - Theodorakis, Stavros A1 - Kozlovskii, Igor A1 - Maliutin, Anton A1 - Medvedev, Alexander A1 - Popov, Petr A1 - Zaretckii, Mark A1 - Eghbal-Zadeh, Hamid A1 - Halmich, Christina A1 - Hochreiter, Sepp A1 - Mayr, Andreas A1 - Ruch, Peter A1 - Widrich, Michael A1 - Berenger, Francois A1 - Kumar, Ashutosh A1 - Yamanishi, Yoshihiro A1 - Zhang, Kam Y. J. A1 - Bengio, Emmanuel A1 - Bengio, Yoshua A1 - Jain, Moksh J. A1 - Korablyov, Maksym A1 - Liu, Cheng-Hao A1 - Marcou, Gilles A1 - Glaab, Enrico A1 - Barnsley, Kelly A1 - Iyengar, Suhasini M. A1 - Ondrechen, Mary Jo A1 - Haupt, V. Joachim A1 - Kaiser, Florian A1 - Schroeder, Michael A1 - Pugliese, Luisa A1 - Albani, Simone A1 - Athanasiou, Christina A1 - Beccari, Andrea A1 - Carloni, Paolo A1 - D’Arrigo, Giulia A1 - Gianquinto, Eleonora A1 - Goßen, Jonas A1 - Hanke, Anton A1 - Joseph, Benjamin P. A1 - Kokh, Daria B. A1 - Kovachka, Sandra A1 - Manelfi, Candida A1 - Mukherjee, Goutam A1 - Muñiz-Chicharro, Abraham A1 - Musiani, Francesco A1 - Nunes-Alves, Ariane A1 - Paiardi, Giulia A1 - Rossetti, Giulia A1 - Sadiq, S. Kashif A1 - Spyrakis, Francesca A1 - Talarico, Carmine A1 - Tsengenes, Alexandros A1 - Wade, Rebecca C. A1 - Copeland, Conner A1 - Gaiser, Jeremiah A1 - Olson, Daniel R. A1 - Roy, Amitava A1 - Venkatraman, Vishwesh A1 - Wheeler, Travis J. A1 - Arthanari, Haribabu A1 - Blaschitz, Klara A1 - Cespugli, Marco A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Fischer, Patrick D. A1 - Gorgulla, Christoph A1 - Gruber, Christian A1 - Gruber, Karl A1 - Hetmann, Michael A1 - Kinney, Jamie E. A1 - Padmanabha Das, Krishna M. A1 - Pandita, Shreya A1 - Singh, Amit A1 - Steinkellner, Georg A1 - Tesseyre, Guilhem A1 - Wagner, Gerhard A1 - Wang, Zi-Fu A1 - Yust, Ryan J. A1 - Druzhilovskiy, Dmitry S. A1 - Filimonov, Dmitry A. A1 - Pogodin, Pavel V. A1 - Poroikov, Vladimir A1 - Rudik, Anastassia V. A1 - Stolbov, Leonid A. A1 - Veselovsky, Alexander V. A1 - De Rosa, Maria A1 - De Simone, Giada A1 - Gulotta, Maria R. A1 - Lombino, Jessica A1 - Mekni, Nedra A1 - Perricone, Ugo A1 - Casini, Arturo A1 - Embree, Amanda A1 - Gordon, D. Benjamin A1 - Lei, David A1 - Pratt, Katelin A1 - Voigt, Christopher A. A1 - Chen, Kuang-Yu A1 - Jacob, Yves A1 - Krischuns, Tim A1 - Lafaye, Pierre A1 - Zettor, Agnès A1 - Rodríguez, M. Luis A1 - White, Kris M. A1 - Fearon, Daren A1 - Von Delft, Frank A1 - Walsh, Martin A. A1 - Horvath, Dragos A1 - Brooks III, Charles L. A1 - Falsafi, Babak A1 - Ford, Bryan A1 - García-Sastre, Adolfo A1 - Yup Lee, Sang A1 - Naffakh, Nadia A1 - Varnek, Alexandre A1 - Klambauer, Günter A1 - Hermans, Thomas M. T1 - A community effort in SARS-CoV-2 drug discovery JF - Molecular Informatics KW - COVID-19 KW - drug discovery KW - machine learning KW - SARS-CoV-2 Y1 - 2023 U6 - https://doi.org/https://doi.org/10.1002/minf.202300262 VL - 43 IS - 1 SP - e202300262 ER -