Computational Chemistry; Computational Biophysics; Biochemistry; Biological Signalling; Electron transfer; multiscale modelling; G-protein coupled receptors; QM/MM Car-Parrinello/TDDFT
M. Doemer M. Gugliemi P. Athri N.S. Nagornova T.R. Rizzo O.V. Bojarkin I. Tavernelli and U. R (2013), Assessing the Performance of Computational Methods for the Prediction of the Ground State Structure of a Cyclic Decapeptide, in International Journal of Quantum Chemistry
, 113, 808-814.
M. Scarongella A. Lationov U. Rothlisberger and N. Banerji (2013), Charge Transfer Relaxation in Donor-Acceptor Type Conjugated Materials, in Advanced Functional Materials
, 1, 2308-2319.
W.F. Kellett E. Brunk B.J. Desai A. A. Fedorov S.C. Almo J.A. Gerlt U. Rothlisberger and N.G. (2013), Computational, Structural, and Kinetic Evidence that Vibrio Vulnificus FrsA is not a Cofactor-Independent Decarboxylase, in Biochemistry
, 52, 18420-1844.
M. Doemer I. Tavernelli and U. Rothlisberger (2013), Intricacies of Describing Weak Interactions Involving Halogen Atoms within, in Journal of Chemical Theory and Computation
, 9, 955-964.
E. Brunk B. Mollwitz and U. Rothlisberger (2013), Mechanism to Trigger Unfolding in O6-Alkylguanine-DNA Alkyltransferase, in ChemBioChem
, 14, 703-710.
M. Guglielmi M. Doemer I. Tavernelli and U. Rothlisberger (2013), Photodynamics of Lys+ - Trp Protein Motifs: Hydrogen Bonds Ensure Photostability, in Faraday Discussions
, 163, 189-203.
O. Valsson P. Campomanes I. Tavernelli U. Rothlisberger and C. Filippi (2013), Rhodopsin Absorption From First-Principles: Bypassing Common Pitfalls, in Journal of Chemical Theory and Computation
, 9, 2441-2454.
Thomas Penfold Ivano Tavernelli Manuel Doemer Ursula Rothlisberger and Majed Chergui (2013), Solvent rearrangements during the transition from hydrophilic to hydrophobic solvation, in Chemical Physics
, 410, 25-30.
B.F.E. Curchod U. Rothlisberger and I. Tavernelli (2013), Trajectory-Based Nonadiabatic Dynamics with Time-Dependent Density, in ChemPhysChem Reviews
, 14, 1314-1340.
J. Garrec I. Tavernelli and U. Rothlisberger (2013), Two Misfolding Routes for the Prion Protein at pH 4.5, in PLOS Computational Biology
, 9(5), e1003057.
G. Palermo P. Campomanes M. Nero D. Piomelli A. Cavalli U Rothlisberger and M. DeVivo (2013), Wagging the Tail: Essential Role of Substrate Flexibility in FAAH Catalysi, in Journal of Chemical Theory and Computation
, 9, 1202-1213.
S. Vanni and U. Rothlisberger (2012), A closer look into G protein coupled receptor activation: x-ray crystallography and long-scale molecular dynamics simulations, in Current Medicinal Chemistry
, 19(8), 1135-1145.
Birgit Mollwitz Elizabeth Brunk Simone Schmitt Florence Pojer Michael Bannwarth Marc Schiltz, Ursula Rothlisberger Kai Johnsson (2012), Directed Evolution of the Suicide Protein O6-Alkylguanine-DNA Alkyltransferase for Increased Reactivity Results in an Alkylated Protein with Exceptional Stability, in Biochemistry
, 51, 986-994.
P. Baillod J. Garrec M.C. Colombo I. Tavernelli and U. Rothlisberger (2012), Enhanced Sampling Molecular Dynamics Identifies PrPSc Structural Models Harboring a C-Terminal B-core, in Biochemistry
, 49, 9891-9899.
Basile F. E. Curchod Ursula Rothlisberger Ivano Tavernelli (2012), Excited State Dynamics with Quantum Trajectories, in Chimia
, 66(4), 174-177.
E. Brunk M. Neri I. Tavernelli V. Hatzimanikatis and U. Rothlisberger (2012), Integrating Computational Methods to Retrofit Enzymes to Synthetic Pathways, in Biotechnoloy and Bioengineering
, 109, 572-582.
Elizabeth Brunk J. Samuel Arey Ursula Rothlisberger (2012), Role of Environment for Catalysis of the DNA Repair Enzyme MutY, in Journal of the American Chemical Society
, 134, 8608-8616.
I-C. Lin A.P. Seitsonen I. Tavernelli V. and U. Rothlisberger (2012), Structure and Dynamics of Liquid Water from Ab Initio Molecular Dynamics – Comparison of BLYP, PBE and revPBE functionals with and without van der Waals corrections, in Journal of Chemical Theory and Computation
, 8, 3902-3910.
Julian Garrec Chandan Patel Ursula Rothlisberger Elise Dumont (2011), Insights into Intrastrand Cross-Link Lesions of DNA from QM/MM Molecular Dynamics Simulations, in Journal of the American Chemical Society
, 134, 2111-2119.
As we have detailed in our previous proposal, the understanding of biological signaling pathways is of primordial importance both from fundamental and practical points of view. Via a complex network of specifically designed signaling pathways, organisms can sense and react to stimuli in their environment and disturbances in the signaling cascades are involved in a wide range of diseases such as cancer, diabetes and immunodeficiences, to name only a few. In spite of this pivotal role, the molecular details of the signaling events are largely unknown and often experimentally difficult to access. During the last decades, computer simulations have evolved to powerful tools for the atomistic characterization of complex biological systems and as such constitute a valuable alternative to gain insights in the intricate molecular mechanisms involved in biological signaling. However, computational investigations of signaling cascades represent formidable challenges also on the theoretical side.Biological signaling events span many orders of length and time scales, from the electronic/atomic level to the mesoscopic/microscopic domain with accompanying time windows that range from femtoseconds to milliseconds and seconds typical for the full activation of a cascade. A theoretical modeling is thus challenging and necessitates a truly multiscale approach where methods of different fields (quantum mechanical electronic structure calculations, atomistic classical molecular dynamics simulations, coarse grain models and systems biology approaches) have to be combined to gain a comprehensive and realistic picture.In our previous SNF grant 20020-116294, we have focused on early electronically triggered signaling events that encompass characteristic length scales from the electronic level to systems of few tens to hundred thousands of atoms in the femtoseconds to microsecond time range. To capture also nonadiabatic events, we have developed real-time real-space propagation implementation of time-dependent density functional theory (P-TDDFT) and a TDDFT based formulation of the Tully’s fewest switches surface hopping scheme. Both methods been combined with our quantum mechanical/ molecular mechanical (QM/MM) code (P-TDDFT/QMMM, SH/QMMM). We have applied adiabatic and nonadiabatic QM/MM dynamics as well as classical molecular dynamics for a multiscale modeling of electronically driven biological signaling in three prototype cases. We have studied the transmission of an electronic signal and the concomitant nuclear rearrangements for the textbook electron transfer protein azurin, the putative redox signaling in metal-loaded prion protein, and the early steps of the signal transduction pathway in the prototypical G-protein coupled receptor rhodopsin.The current proposal is a natural continuation of our previous SNF grant 200020-116294 which itself was a continuation of SNF grants 21-57250.99, 200020-100502, and 20020-108063 in which we developed a mixed quantum mechanical/ molecular mechanical Car-Parrinello approach for ground and excited state dynamics and prepared and tested the computational machinery for the simulations of adiabatic and non-adiabatic electron transfer reactions.In the current proposal, which involves four 4 PhD positions over a period of three years, we want to push forward the current frontiers of multiscale modeling approaches by improving the accuracy of the electronic part and by further extending the accessible length and time scales. Specifically, we want to work on the development of improved functionals for DFT and TDDFT, extend our TDDFT-based surface hopping approach with the inclusion of nuclear quantum effects. We also propose the development of a new force-matching procedure for the on-the-fly parameterization of semiempirical electronic structure methods based on DFT/MM reference data that will allow sampling of several orders of magnitude longer time scales in the sampling of the QM region while maintaining essentially DFT accuracy. We will also continue our development in enhanced sampling methods, in particular via the development and testing of a Hamiltonian based replica exchange approach. Furthermore, we will combine the QM/MM and classical simulations with coarse grain models for the simulation of multiprotein aggregates. With the ultimate goal of connecting electronic/atomistic information with the systems level, we are will start the development of a framework for the simulation of entire biological networks. These developments will allow us to investigate electron transfer mediated processes in DNA repair. Furthermore, they will enable us to study the later intermediates of the activation cycle of G protein coupled receptors and the interaction of the activated form with the G proteinsThe application of this diverse set of multiscale modelling techniques to electronically triggered biological signaling events will yield a wealth of detailed information about the electronic, atomistic and large scale conformational changes involved in biological signaling and thus greatly further the fundamental understanding of these crucial processes. In addition, we want to make use of the gained information in an active way to develop how specific systems can be manipulated in desired ways, e.g. through the interaction with suitably chosen inhibitors. To this end, we propose here to initiate the development of a general method for the rational design of molecules and materials with tailored properties.