@misc{BaumeisterCordes2004, author = {Baumeister, Timm and Cordes, Frank}, title = {A new Model for the Free Energy of Solvation and its Application in Protein Ligand Scoring}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8265}, number = {04-51}, year = {2004}, abstract = {A new and time efficient model to evaluate the free energy of solvation has been developed. The solvation free energy is separated into an electrostatic term, a hydrogen bond term, and a rest-term, combining both entropic and van der Waals effects. The electrostatic contribution is evaluated with a simplified boundary element method using the partial charges of the MMFF94 force field. The number of hydrogen bonds and the solvent excluded surface area over the surface atoms are used in a linear model to estimate the non-electrostatic contribution. This model is applied to a set of 213 small and mostly organic molecules, yielding an rmsd of 0.87kcal/mol and a correlation with experimental data of r=0.951. The model is applied as a supplementary component of the free energy of binding to estimate binding constants of protein ligand complexes. The intermolecular interaction energy is evaluated by using the MMFF94 force field.}, language = {en} } @article{HuisingaBestCordesetal.1999, author = {Huisinga, Wilhelm and Best, Christoph and Cordes, Frank and Roitzsch, Rainer and Sch{\"u}tte, Christof}, title = {Identification of Molecular Conformations via Statistical Analysis of Simulation Data}, volume = {20}, journal = {Comp. Chem.}, pages = {1760 -- 1774}, year = {1999}, language = {en} } @inproceedings{WendeCordesSteinke2012, author = {Wende, Florian and Cordes, Frank and Steinke, Thomas}, title = {On Improving the Performance of Multi-threaded CUDA Applications with Concurrent Kernel Execution by Kernel Reordering}, booktitle = {Application Accelerators in High Performance Computing (SAAHPC), 2012 Symposium on}, doi = {10.1109/SAAHPC.2012.12}, pages = {74 -- 83}, year = {2012}, language = {en} } @article{GuerlerMollWeberetal.2008, author = {Guerler, A. and Moll, Sebastian and Weber, Marcus and Meyer, Holger and Cordes, Frank}, title = {Selection and flexible optimization of binding modes from conformation ensembles}, volume = {92}, journal = {Biosystems}, number = {1}, doi = {DOI: 10.1016/j.biosystems.2007.11.004}, pages = {42 -- 48}, year = {2008}, language = {en} } @article{HuisingaBestRoitzschetal.1999, author = {Huisinga, Wilhelm and Best, Christoph and Roitzsch, Rainer and Sch{\"u}tte, Christof and Cordes, Frank}, title = {From Simulation Data to Conformational Ensembles}, volume = {20}, journal = {J. Comp. Chem.}, number = {16}, pages = {1760 -- 1774}, year = {1999}, language = {en} } @inproceedings{GalliatDeuflhardRoitzschetal.2002, author = {Galliat, Tobias and Deuflhard, Peter and Roitzsch, Rainer and Cordes, Frank}, title = {Automatic Identification of Metastable Conformations via Self-Organized Neural Networks}, booktitle = {Computational Methods for Macromolecules}, number = {24}, editor = {Schlick, T. and Gan, H.}, publisher = {Springer}, year = {2002}, language = {en} } @inproceedings{GalliatDeuflhardRoitzschetal.2002, author = {Galliat, Tobias and Deuflhard, Peter and Roitzsch, Rainer and Cordes, Frank}, title = {Automatic identification of metastable conformations via self-organized neural networks}, booktitle = {Proceedings of the 3rd International Workshop on Algorithms for Macromolecular Modelling}, year = {2002}, language = {en} } @article{FischerCordesSchuette1998, author = {Fischer, Alexander and Cordes, Frank and Sch{\"u}tte, Christof}, title = {Hybrid Monte Carlo with Adaptive Temperature in Mixed-Canonical Ensemble: Efficient conformational analysis of RNA}, volume = {19}, journal = {J. Comp. Chem.}, number = {15}, doi = {10.1002/(SICI)1096-987X(19981130)19:15<1689::AID-JCC2>3.0.CO;2-J}, pages = {1689 -- 1697}, year = {1998}, language = {en} } @inproceedings{FischerSchuetteDeuflhardetal.2002, author = {Fischer, Alexander and Sch{\"u}tte, Christof and Deuflhard, Peter and Cordes, Frank}, title = {Hierarchical Uncoupling-Coupling of Metastable Conformations}, booktitle = {Computational Methods for Macromolecules}, number = {24}, editor = {Schlick, T. and Gan, H.}, publisher = {Springer}, pages = {235 -- 259}, year = {2002}, language = {en} } @article{GuerlerMollWeberetal.2007, author = {G{\"u}rler, A. and Moll, Sebastian and Weber, Marcus and Meyer, Holger and Cordes, Frank}, title = {Selection and flexible optimization of binding modes from conformation ensembles}, journal = {Biosystems}, year = {2007}, language = {en} } @article{FoersterBrauerFuersteetal.2007, author = {F{\"o}rster, C. and Brauer, Arnd B. E. and F{\"u}rste, J. and Betzel, C. and Weber, Marcus and Cordes, Frank and Erdmann, V.}, title = {Visualization of the tRNA(Ser) acceptor step binding site in the seryl-tRNA synthetase}, volume = {362}, journal = {BBRC}, number = {2}, pages = {415 -- 418}, year = {2007}, language = {en} } @inproceedings{SchuetteCordes2000, author = {Sch{\"u}tte, Christof and Cordes, Frank}, title = {On Dynamical Transitions between Conformational Ensembles}, booktitle = {Molecular Dynamics on Parallel Computers}, editor = {Esser, R. and Grassberger, P. and Grotendorst, J. and Lewerenz, M.}, publisher = {World Scientific}, doi = {10.1142/9789812793768_0002}, pages = {32 -- 45}, year = {2000}, language = {en} } @article{HuisingaBestRoitzschetal.1999, author = {Huisinga, Wilhelm and Best, Christoph and Roitzsch, Rainer and Sch{\"u}tte, Christof and Cordes, Frank}, title = {From Simulation Data to Conformational Ensembles}, volume = {20}, journal = {J. Comp. Chem.}, number = {16}, doi = {10.1002/(SICI)1096-987X(199912)20:16<1760::AID-JCC8>3.0.CO;2-2}, pages = {1760 -- 1774}, year = {1999}, language = {en} } @article{FischerCordesSchuette1999, author = {Fischer, Alexander and Cordes, Frank and Sch{\"u}tte, Christof}, title = {Hybrid Monte Carlo with adaptive temperature choice}, volume = {121}, journal = {Comp. Phys. Comm.}, doi = {10.1016/S0010-4655(99)00274-X}, pages = {37 -- 39}, year = {1999}, language = {en} } @article{FischerCordesSchuette1998, author = {Fischer, Alexander and Cordes, Frank and Sch{\"u}tte, Christof}, title = {Hybrid Monte Carlo with adaptive temperature in mixed-canonical ensemble}, volume = {19}, journal = {J. Comp. Chem.}, number = {15}, doi = {10.1002/(SICI)1096-987X(19981130)19:15<1689::AID-JCC2>3.0.CO;2-J}, pages = {1689 -- 1697}, year = {1998}, language = {en} } @inproceedings{FischerSchuetteDeuflhardetal.2002, author = {Fischer, Alexander and Sch{\"u}tte, Christof and Deuflhard, Peter and Cordes, Frank}, title = {Hierarchical Uncoupling-Coupling of Metastable Conformations}, volume = {24}, booktitle = {Computational Methods for Macromolecules}, editor = {Schlick, T. and Gan, H.}, publisher = {Springer}, pages = {235 -- 259}, year = {2002}, language = {en} } @misc{FischerCordesSchuette1997, author = {Fischer, Alexander and Cordes, Frank and Sch{\"u}tte, Christof}, title = {Hybrid Monte Carlo with Adaptive Temperature in a Mixed-Canonical Ensemble: Efficient Conformational Analysis of RNA}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-3364}, number = {SC-97-67}, year = {1997}, abstract = {A hybrid Monte Carlo method with adaptive temperature choice is presented, which exactly generates the distribution of a mixed-canonical ensemble composed of two canonical ensembles at low and high temperature. The analysis of resulting Markov chains with the reweighting technique shows an efficient sampling of the canonical distribution at low temperature, whereas the high temperature component facilitates conformational transitions, which allows shorter simulation times. \\The algorithm was tested by comparing analytical and numerical results for the small n-butane molecule before simulations were performed for a triribonucleotide. Sampling the complex multi-minima energy landscape of these small RNA segments, we observed enforced crossing of energy barriers.}, language = {en} } @misc{HuisingaBestCordesetal.1998, author = {Huisinga, Wilhelm and Best, Christoph and Cordes, Frank and Roitzsch, Rainer and Sch{\"u}tte, Christof}, title = {From Simulation Data to Conformational Ensembles: Structure and Dynamics based Methods}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-3797}, number = {SC-98-36}, year = {1998}, abstract = {Statistical methods for analyzing large data sets of molecular configurations within the chemical concept of molecular conformations are described. The strategies are based on dependencies between configurations of a molecular ensemble; the article concentrates on dependencies induces by a) correlations between the molecular degrees of freedom, b) geometrical similarities of configurations, and c) dynamical relations between subsets of configurations. The statistical technique realizing aspect a) is based on an approach suggested by {\sc Amadei et al.} (Proteins, 17 (1993)). It allows to identify essential degrees of freedom of a molecular system and is extended in order to determine single configurations as representatives for the crucial features related to these essential degrees of freedom. Aspects b) and c) are based on statistical cluster methods. They lead to a decomposition of the available simulation data into {\em conformational ensembles} or {\em subsets} with the property that all configurations in one of these subsets share a common chemical property. In contrast to the restriction to single representative conformations, conformational ensembles include information about, e.g., structural flexibility or dynamical connectivity. The conceptual similarities and differences of the three approaches are discussed in detail and are illustrated by application to simulation data originating from a hybrid Monte Carlo sampling of a triribonucleotide.}, language = {en} } @misc{CordesWeberSchmidtEhrenberg2002, author = {Cordes, Frank and Weber, Marcus and Schmidt-Ehrenberg, Johannes}, title = {Metastable Conformations via successive Perron-Cluster Cluster Analysis of dihedrals}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-7074}, number = {02-40}, year = {2002}, abstract = {Decomposition of the high dimensional conformational space of bio-molecules into metastable subsets is used for data reduction of long molecular trajectories in order to facilitate chemical analysis and to improve convergence of simulations within these subsets. The metastability is identified by the Perron-cluster cluster analysis of a Markov process that generates the thermodynamic distribution. A necessary prerequisite of this analysis is the discretization of the conformational space. A combinatorial approach via discretization of each degree of freedom will end in the so called ''curse of dimension''. In the following paper we analyze Hybrid Monte Carlo simulations of small, drug-like biomolecules and focus on the dihedral degrees of freedom as indicators of conformational changes. To avoid the ''curse of dimension'', the projection of the underlying Markov operator on each dihedral is analyzed according to its metastability. In each decomposition step of a recursive procedure, those significant dihedrals, which indicate high metastability, are used for further decomposition. The procedure is introduced as part of a hierarchical protocol of simulations at different temperatures. The convergence of simulations within metastable subsets is used as an ''a posteriori'' criterion for a successful identification of metastability. All results are presented with the visualization program AmiraMol.}, language = {en} } @misc{MayEisenhardtSchmidtEhrenbergetal.2003, author = {May, Andreas and Eisenhardt, Steffen and Schmidt-Ehrenberg, Johannes and Cordes, Frank}, title = {Rigid body docking for Virtual Screening}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-7690}, number = {03-47}, year = {2003}, abstract = {A recently developed algorithm allows Rigid Body Docking of ligands to proteins, regardless of the accessibility and location of the binding site. The Docking procedure is divided into three subsequent optimization phases, two of which utilize rigid body dynamics. The last one is applied with the ligand already positioned inside the binding pocket and accounts for full flexibility. Initially, a combination of geometrical and force-field based methods is used as a Coarse Docking strategy, considering only Lennard-Jones interactions between the target and pharmaceutically relevant atoms or functional groups. The protein is subjected to a Hot Spot Analysis, which reveals points of high affinity in the protein environment towards these groups. The hot spots are distributed into different subsets according to their group affiliation. The ligand is described as a complementary point set, consisting of the same subsets. Both sets are matched in \$\mathrm{I\!R}^{3}\$, by superimposing members of the same subsets. In the first instance, steric inhibition is nearly neglected, preventing the system's trajectory from trapping in local minima and thus from finding false positive solutions. Hence the exact location of the binding site can be determined fast and reliably without any additional information. Subsequently, errors resulting from approximations are minimized via finetuning, this time considering both Lennard-Jones and Coulomb forces. Finally, the potential energy of the whole complex is minimized. In a first evaluation, results are rated by a reduced scoring function considering only noncovalent interaction energies. Exemplary Screening results will be given for specific ligands.}, language = {en} }