ModelFree Fits model-free parameters to relaxation rates.
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data parameter optimize optimize parameters heteronuclear data optimize data

ModelFree Description

Fits model-free parameters to relaxation rates. ModelFree is a program designed to optimize the "Lipari-Szabo model free" parameters to heteronuclear relaxation data.ModelFree is a program to fit the extended model free spectral density function to NMR spin relaxation data. The program can analyze the spin-lattice relaxation rate constant (R1), the spin-spin relaxation rate constant (R2), and the heteronuclear steady-state {1H}-X nuclear Overhauser effect (NOE) for any combination of 13C and 15N spins at up to five static magnetic fields. The algorithm assumes dipolar and chemical shift anisotropy (CSA) relaxation mechanisms for R1, R2 and the NOE and includes an additive term to account for chemical exchange broadening of R2. The exchange broadening parameter is scaled quadratically with respect to the static magnetic field if data for more than one field is available. Descriptions of the main principles utilized in the program for model selection, optimization and error analysis using Monte Carlo simulations have been published previously (Palmer et al., 1991; Mandel et al., 1995).Modelfree incorporates three models for rotational diffusion. Brent's method is used to optimize a single global τm for an isotropic overall diffusion model. Either Powell's method (as implemented by Brent) or a simulated annealing protocol (based on the downhill simplex method) is used to optimize a global rotational diffusion tensor for an axially symmetric diffusion model. A local rotational correlation time, τmi, for each spin can be optimized by non-linear least squares regression. Other internal model free parameters (order parameters, internal correlation times and chemical exchange terms) are optimized by restrained non-linear least squares. Any parameter can be fixed at its input value rather than optimized nd simple bounds can be placed on any parameter. Monte Carlo simulations are used to estimate uncertainties in model-free parameters and to perform statistical model selection based on F-testing. A good introductory discussion of the use of Monte Carlo simulations in error analysis is given by Press et al. (Press et al., 1986). What's New in This Release: · Ended support for SGI platform. Only linux and mac OSX are supported platforms at present. · Fixed termination criteria and simulated distribution of F-statistic error. · A bug identified by Edward d'Auvergne that caused the minimization algorithm to terminate inappropriately after an unsuccessful optimization step has been fixed. · A bug in the test for whether bounded parameters could be returned to the active set has been fixed. · Changed grid search so the exact upper and lower bounds are not grid search points. · Maximum number of residues was increased to 300.

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