Protein folding optimization methods

J. Kostrowicki and H.A. Scheraga, Application of the diffusion equation method for global optimization to oligopeptides, J. Phys. Chem. 96 (1992), 7442-7449. M. Levitt, A simplified representation of protein confomations for rapid simulation of protein folding, J. Mol. Biol. 104 (1976), 59-107. 

Finding the minimum of the hybrid energy function is very complex. Similar to the protein folding problem, the number of degrees of freedom is far too large to allow a complete systematic search in all variables. Systematic search methods need to reduce the problem to a few degrees of freedom (see, e.g.. Ref. 30). Conformations of the molecule that satisfy the experimental bounds are therefore usually calculated with metric matrix distance geometry methods followed by optimization or by optimization methods alone. 

Summary. We recently developed an all-atom free energy force field (PFFOl) for protein structure prediction with stochastic optimization methods. We demonstrated that PFFOl correctly predicts the native conformation of several proteins as the global optimum of the free energy surface. Here we review recent folding studies, which permitted the reproducible all-atom folding of the 20 amino-acid trp-cage protein, the 40-amino acid three-helix HIV accessory protein and the sixty amino acid bacterial ribosomal protein L20 with a variety of stochastic optimization methods. These results demonstrate that all-atom protein folding can be achieved with present day computational resources for proteins of moderate size. 

This review indicates that all-atom protein structure prediction with stochastic optimization methods becomes feasible with present-day computational resources. The fact that three proteins were reproducibly folded with different optimization methods to near-native conformation increases the confidence in the parameterization of our all-atom protein force field PFFOl. The... 

A. Schug, A. Verma, T. Herges, and W. Wenzel. Comparison of stochastic optimization methods for all-atom folding of the trp-cage protein, submitted to Proteins, 2005. 

The Mulliken-Mezey AFDF scheme and the more general AFDF schemes - also serve as the basis for the adjustable density matrix assembler (ADMA) method. The ADMA method generates ab initio quality macromolecular density matrices, which can be used for the computation of a variety of ab initio quality properties for macromolecules. The ADMA method is also suitable for the calculation of ab initio quality electronic densities, however, additional molecular properties, such as forces and energies, can also be calculated. These options of the ADMA method are expected to be useful in macromolecular conformational analysis, geometry optimizations, and in computational studies of protein folding. 

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