Variable target function

Figure 5 Optimization of the objective function in Modeller. Optimization of the objective function (curve) starts with a random or distorted model structure. The iteration number is indicated below each sample structure. The first approximately 2000 iterations coiTespond to the variable target function method [82] relying on the conjugate gradients technique. This approach first satisfies sequentially local restraints, then slowly introduces longer range restraints until the complete objective function IS optimized. In the remaining 4750 iterations, molecular dynamics with simulated annealing is used to refine the model [83]. CPU time needed to generate one model is about 2 mm for a 250 residue protein on a medium-sized workstation.

M. Vasquez and H. A. Scheraga, J. Btomol. Struct. Dyn., 5, 757 (1988). Variable-Target-Function and Build-up Procedures for the Calculation of Protein Conformation. Application to Bovine Pancreatic Trypsin Inhibitor Using Limited Simulated Nuclear Magnetic Resonance Data. 

Rather than regarding the force field as a fixed part of the refinement procedure, it may be quite reasonable to adjust force field parameters to make barriers easier to surmount or to use force field parameters as variables that can be altered to implement a refinement method. In one sense, this principle of minimizing on a changing potential surface could be seen as the heart of the variable target function method discussed previously.8... 

Torsion angle space minimization (variable target function method) 242... 

A third popular algorithm is named after its basic principle to circumvent local minima the variable target function algorithm. It was introduced early in the history of NMR structure determination and has been modified several times since. 

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