@misc{WeberBeckerKoeppenetal.2007, author = {Weber, Marcus and Becker, Roland and K{\"o}ppen, Robert and Durmaz, Vedat}, title = {Classical hybrid Monte-Carlo simulations of the interconversion of hexabromocyclododecane}, organization = {Zuse-Institut Berlin}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10308}, number = {07-31}, year = {2007}, abstract = {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.}, 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} } @incollection{DurmazFackeldeyWeber2011, author = {Durmaz, Vedat and Fackeldey, Konstantin and Weber, Marcus}, title = {A rapidly Mixing Monte Carlo Method for the Simulation of Slow Molecular Processes}, booktitle = {Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science}, editor = {Mode, Ch.}, publisher = {InTech}, year = {2011}, language = {en} } @article{WeberBeckerKoeppenetal.2008, author = {Weber, Marcus and Becker, Roland and K{\"o}ppen, Robert and Durmaz, Vedat}, title = {Classical hybrid Monte-Carlo simulations of the interconversion of hexabromocyclododecane}, volume = {34}, journal = {Journal of Molecular Simulation}, number = {7}, pages = {727 -- 736}, year = {2008}, language = {en} } @article{KoeppenRiedelProskeetal.2012, author = {K{\"o}ppen, Robert and Riedel, Juliane and Proske, Matthias and Drzymala, Sarah and Rasenko, Tatjana and Durmaz, Vedat and Weber, Marcus and Koch, Matthias}, title = {Photochemical trans-/cis-isomerization and quantification of zearalenone in edible oils}, volume = {60}, journal = {J. Agric. Food Chem.}, doi = {10.1021/jf3037775}, pages = {11733 -- 11740}, year = {2012}, language = {en} } @article{DurmazWeberBecker2012, author = {Durmaz, Vedat and Weber, Marcus and Becker, Roland}, title = {How to Simulate Affinities for Host-Guest Systems Lacking Binding Mode Information: application to the liquid chromatographic separation of hexabromocyclododecane stereoisomers}, volume = {18}, journal = {Journal of Molecular Modeling}, doi = {10.1007/s00894-011-1239-5}, pages = {2399 -- 2408}, year = {2012}, language = {en} } @article{KoeppenBeckerWeberetal.2009, author = {K{\"o}ppen, Robert and Becker, Roland and Weber, Marcus and Durmaz, Vedat and Nehls, Irene}, title = {HBCD stereoisimers: Thermal interconversion and enantiospecific trace analysis in biota}, volume = {70}, journal = {Organohalogen Compounds}, pages = {910 -- 913}, year = {2009}, language = {en} } @article{WeberDurmazBeckeretal.2009, author = {Weber, Marcus and Durmaz, Vedat and Becker, Roland and Esslinger, Susanne}, title = {Predictive Identification of Pentabromocyclododecane (PBCD) Isomers with high Binding Affinity to hTTR}, volume = {71}, journal = {Organohalogen Compounds}, pages = {247 -- 252}, year = {2009}, language = {en} } @misc{Durmaz2009, type = {Master Thesis}, author = {Durmaz, Vedat}, title = {Theoretical Investigations on HBCD and PBCD}, year = {2009}, language = {en} } @article{GorgullaDasLeighetal.2021, author = {Gorgulla, Christoph and Das, Krishna M. Padmanabha and Leigh, Kendra E and Cespugli, Marco and Fischer, Patrick D. and Wang, Zi-Fu and Tesseyre, Guilhem and Pandita, Shreya and Shnapir, Alex and Calderaio, Anthony and Hutcheson, Colin and Gechev, Minko and Rose, Alexander and Lewis, Noam and Yaffe, Erez and Luxenburg, Roni and Herce, Henry D. and Durmaz, Vedat and Halazonetis, Thanos D. and Fackeldey, Konstantin and Patten, Justin J. and Chuprina, Alexander and Dziuba, Igor and Plekhova, Alla and Moroz, Yurii and Radchenko, Dmytro and Tarkhanova, Olga and Yavnyuk, Irina and Gruber, Christian C. and Yust, Ryan and Payne, Dave and N{\"a}{\"a}r, Anders M. and Namchuk, Mark N. and Davey, Robert A. and Wagner, Gerhard and Kinney, Jamie and Arthanari, Haribabu}, title = {A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening}, volume = {24}, journal = {iScience}, number = {2}, publisher = {CellPress}, doi = {10.26434/chemrxiv.12682316}, pages = {102021}, year = {2021}, abstract = {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.}, language = {en} }