Variational Approach to Molecular Kinetics.
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Frank Noé | Feliks Nüske | Bettina G Keller | Antonia S J S Mey | Guillermo Pérez-Hernández | F. Noé | B. Keller | A. Mey | G. Pérez-Hernández | F. Nüske
[1] Albert C. Pan,et al. Building Markov state models along pathways to determine free energies and rates of transitions. , 2008, The Journal of chemical physics.
[2] Thomas J Lane,et al. MSMBuilder2: Modeling Conformational Dynamics at the Picosecond to Millisecond Scale. , 2011, Journal of chemical theory and computation.
[3] Fiete Haack,et al. Adaptive Spectral Clustering for Conformation Analysis , 2010 .
[4] M. Karplus,et al. Hidden complexity of free energy surfaces for peptide (protein) folding. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[5] B. L. de Groot,et al. Essential dynamics of reversible peptide folding: memory-free conformational dynamics governed by internal hydrogen bonds. , 2001, Journal of molecular biology.
[6] V. Pande,et al. Error analysis and efficient sampling in Markovian state models for molecular dynamics. , 2005, The Journal of chemical physics.
[7] Toni Giorgino,et al. Identification of slow molecular order parameters for Markov model construction. , 2013, The Journal of chemical physics.
[8] William Swope,et al. Describing Protein Folding Kinetics by Molecular Dynamics Simulations. 1. Theory , 2004 .
[9] T. Darden,et al. Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems , 1993 .
[10] Wilfred F van Gunsteren,et al. Comparing geometric and kinetic cluster algorithms for molecular simulation data. , 2010, The Journal of chemical physics.
[11] Frank Noé,et al. A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems , 2012, Multiscale Model. Simul..
[12] Vijay S Pande,et al. Simple few-state models reveal hidden complexity in protein folding , 2012, Proceedings of the National Academy of Sciences.
[13] Frank Noé,et al. Markov state models based on milestoning. , 2011, The Journal of chemical physics.
[14] R. Glen,et al. Identifying and correcting non-Markov states in peptide conformational dynamics. , 2010, The Journal of chemical physics.
[15] F. Noé. Probability distributions of molecular observables computed from Markov models. , 2008, The Journal of chemical physics.
[16] R. Dror,et al. Improved side-chain torsion potentials for the Amber ff99SB protein force field , 2010, Proteins.
[17] R. Hegger,et al. Dihedral angle principal component analysis of molecular dynamics simulations. , 2007, The Journal of chemical physics.
[18] Vijay S Pande,et al. Progress and challenges in the automated construction of Markov state models for full protein systems. , 2009, The Journal of chemical physics.
[19] Charles R. MacCluer,et al. The Many Proofs and Applications of Perron's Theorem , 2000, SIAM Rev..
[20] Joshua A. Kritzer,et al. Relationship between side chain structure and 14-helix stability of beta3-peptides in water. , 2005, Journal of the American Chemical Society.
[21] Kyle A. Beauchamp,et al. Markov state model reveals folding and functional dynamics in ultra-long MD trajectories. , 2011, Journal of the American Chemical Society.
[22] Eric Vanden-Eijnden,et al. Markovian milestoning with Voronoi tessellations. , 2009, The Journal of chemical physics.
[23] K. Dill,et al. Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics. , 2007, The Journal of chemical physics.
[24] C. Schütte,et al. Supplementary Information for “ Constructing the Equilibrium Ensemble of Folding Pathways from Short Off-Equilibrium Simulations ” , 2009 .
[25] R. Elber. Simulations of allosteric transitions. , 2011, Current opinion in structural biology.
[26] F. Rao,et al. The protein folding network. , 2004, Journal of molecular biology.
[27] Jeremy C. Smith,et al. Dynamical fingerprints for probing individual relaxation processes in biomolecular dynamics with simulations and kinetic experiments , 2011, Proceedings of the National Academy of Sciences.
[28] Gerhard Reinelt,et al. Computing Best Transition Pathways in High-Dimensional Dynamical Systems: Application to the AlphaL \leftrightharpoons Beta \leftrightharpoons AlphaR Transitions in Octaalanine , 2006, Multiscale Model. Simul..
[29] G. Hummer,et al. Coarse master equations for peptide folding dynamics. , 2008, The journal of physical chemistry. B.
[30] G. de Fabritiis,et al. Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations , 2011, Proceedings of the National Academy of Sciences.
[31] Vijay S Pande,et al. Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9. , 2013, Journal of chemical theory and computation.
[32] Joseph A. Bank,et al. Supporting Online Material Materials and Methods Figs. S1 to S10 Table S1 References Movies S1 to S3 Atomic-level Characterization of the Structural Dynamics of Proteins , 2022 .
[33] Vijay S Pande,et al. Simulating oligomerization at experimental concentrations and long timescales: A Markov state model approach. , 2008, The Journal of chemical physics.
[34] M. Parrinello,et al. Canonical sampling through velocity rescaling. , 2007, The Journal of chemical physics.
[35] Gerrit Groenhof,et al. GROMACS: Fast, flexible, and free , 2005, J. Comput. Chem..
[36] F. Noé,et al. Transition networks for modeling the kinetics of conformational change in macromolecules. , 2008, Current opinion in structural biology.
[37] Jeremy C. Smith,et al. Hierarchical analysis of conformational dynamics in biomolecules: transition networks of metastable states. , 2007, The Journal of chemical physics.
[38] Berk Hess,et al. LINCS: A linear constraint solver for molecular simulations , 1997 .
[39] A. Caflisch,et al. Kinetic analysis of molecular dynamics simulations reveals changes in the denatured state and switch of folding pathways upon single‐point mutation of a β‐sheet miniprotein , 2008, Proteins.
[40] S. Röblitz. Statistical Error Estimation and Grid-free Hierarchical Refinement in Conformation Dynamics , 2009 .
[41] M. N. Jacobi,et al. Identification of metastable states in peptide's dynamics. , 2010, The Journal of chemical physics.
[42] K. Verhey,et al. Kinesin assembly and movement in cells. , 2011, Annual review of biophysics.
[43] W. E,et al. Towards a Theory of Transition Paths , 2006 .
[44] Frank Noé,et al. On the Approximation Quality of Markov State Models , 2010, Multiscale Model. Simul..
[45] Frank Noé,et al. EMMA: A Software Package for Markov Model Building and Analysis. , 2012, Journal of chemical theory and computation.
[46] Paul Tavan,et al. Extracting Markov Models of Peptide Conformational Dynamics from Simulation Data. , 2005, Journal of chemical theory and computation.
[47] P. Deuflhard,et al. A Direct Approach to Conformational Dynamics Based on Hybrid Monte Carlo , 1999 .
[48] Frank Noé,et al. Markov models of molecular kinetics: generation and validation. , 2011, The Journal of chemical physics.
[49] C. Brooks,et al. Statistical clustering techniques for the analysis of long molecular dynamics trajectories: analysis of 2.2-ns trajectories of YPGDV. , 1993, Biochemistry.
[50] Eric J. Deeds,et al. Understanding ensemble protein folding at atomic detail , 2006, Proceedings of the National Academy of Sciences.
[51] R. Dror,et al. How Fast-Folding Proteins Fold , 2011, Science.
[52] J. Chodera,et al. Probability distributions of molecular observables computed from Markov models. II. Uncertainties in observables and their time-evolution. , 2010, The Journal of chemical physics.
[53] Marcus Weber,et al. A coarse graining method for the identification of transition rates between molecular conformations. , 2007, The Journal of chemical physics.
[54] Frank Noé,et al. Markov models and dynamical fingerprints: Unraveling the complexity of molecular kinetics , 2012 .
[55] Vijay S Pande,et al. Protein folded states are kinetic hubs , 2010, Proceedings of the National Academy of Sciences.
[56] Dmitry Nerukh,et al. Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory. , 2008, The Journal of chemical physics.
[57] Jeremy C. Smith,et al. Transition Networks for the Comprehensive Characterization of Complex Conformational Change in Proteins. , 2006, Journal of chemical theory and computation.
[58] Bettina Keller,et al. An Analysis of the Validity of Markov State Models for Emulating the Dynamics of Classical Molecular Systems and Ensembles. , 2011, Journal of chemical theory and computation.
[59] J. Cate,et al. Ribosome structure and dynamics during translocation and termination. , 2010, Annual review of biophysics.
[60] Frank Noé,et al. Kinetic characterization of the critical step in HIV-1 protease maturation , 2012, Proceedings of the National Academy of Sciences.
[61] Hans C Andersen,et al. A Bayesian method for construction of Markov models to describe dynamics on various time-scales. , 2010, The Journal of chemical physics.
[62] P. Deuflhard,et al. Identification of almost invariant aggregates in reversible nearly uncoupled Markov chains , 2000 .
[63] Frank Noé,et al. Dynamic neutron scattering from conformational dynamics. II. Application using molecular dynamics simulation and Markov modeling. , 2013, The Journal of chemical physics.
[64] Frank Noé,et al. Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models. , 2013, The Journal of chemical physics.
[65] Vijay S. Pande,et al. Everything you wanted to know about Markov State Models but were afraid to ask. , 2010, Methods.
[66] P. Deuflhard,et al. Robust Perron cluster analysis in conformation dynamics , 2005 .