%------------------- LineShapeKin MODEL_SETUP ----------------------------- %-- version 3.0 % % 3/11/08 % Written by Evgenii Kovrigin, Medical College of Wisconsin % % This file contains model-specific parameters. You edit this file if you % want to change your fitting model. % % X_columns is a structure that % specifies column positions of protein concentration, ligand/protein % ratio, relaxation rates, peak positions, temperature etc. % % B_vector % is a structure that specifies positions of variable for fitting such % as Koff, scale_factor, Kd, activation energy etc. % % Model_description % is a structure that contains additional information on the fitting % model % % This file sets these variables global so for fitting functions to access % them. global YES NO X_columns B_vector Model; %% Definition of the 'Xcomposite' array of experimental data X_columns.number= 8; %-- Enter here total number of columns used in % 'Xcomposite' matrix of % experimental conditions (see % prepare_residue_data.m) %-- Enter here positions the specific data columns appear in the 'Xcomposite' vector X_columns.Ptotal =1; X_columns.LPratio=2; X_columns.Xtotal = 3; X_columns.R2A = 4; X_columns.R2B = 5; X_columns.wA = 6; X_columns.wB = 7; X_columns.Temp= 8; %% Model description Model.name = 'Two-site exchange (fixed Kd)'; % Starting and fixed parameters of the fitting model %-- list corresponding Kds here (if determined individually or one global % value times number of residues). If the model does fitting of Kd then % this number is used as a starting parameter. If the grid search % (below) is requested for the parameter then its value here is % disregarded and taken from B_vector.grid_values Model.Kd = 1.40 ; %-- [M] %- if Kd is variable set these Model.Kd_min=0; Model.Kd_max=10e10; %-- list corresponding koffs here to be used as a starting parameter. Model.Koff = 100 ; %-- [M] Model.Koff_min=0; Model.Koff_max=10e10; %--- correction factor for intensity of spectra (to compensate for % imprecise normalization) Model.scale_factor = 1.0; Model.scale_factor_min = 0; Model.scale_factor_max = 1e9; %% Definition of the 'beta' vector: variable parameters in the model to % fit. %-- Generate starting 'beta' vector beta0 = [ Model.Koff, Model.scale_factor ]; beta0_min = [ Model.Koff_min, Model.scale_factor_min ]; beta0_max = [ Model.Koff_max, Model.scale_factor_max ]; %-- Assign here the positions of the fitting parameters in the 'beta' % vector to use in when addressing the vector B_vector.Koff = 1; B_vector.scale_factor = 2; %---- Setting the grid values to start fitting from when searching for global % minimum B_vector.grid_search_parameter=B_vector.Koff; B_vector.grid_values=[ 0.1 100 1e5 ];