Some approaches to the multiple‐minima problem in the calculation of polypeptide and protein structures

Various methods are used to surmount the multiple-minima problem that is encountered in the multidimensional conformational energy surface of a polypeptide. A summary is given here of two of these methods: (i) The build-up procedure that is modified to include statistical data on the positional frequencies of occurrence of amino acid residues along the chain, and (ii) the diffusion equation method that smoothes out the potential surface, leaving only the potential well containing the global minimum.

[1]  H. Scheraga,et al.  Energy parameters in polypeptides. 9. Updating of geometrical parameters, nonbonded interactions, and hydrogen bond interactions for the naturally occurring amino acids , 1983 .

[2]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[3]  Harold A. Scheraga,et al.  Structure and free energy of complex thermodynamic systems , 1988 .

[4]  J. Kostrowicki,et al.  Diffusion equation method of global minimization: Performance for standard test functions , 1991 .

[5]  I. Simon,et al.  A possible way for prediction of domain boundaries in globular proteins from amino acid sequence. , 1986, Biochemical and biophysical research communications.

[6]  H. Scheraga,et al.  Monte Carlo-minimization approach to the multiple-minima problem in protein folding. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[7]  F Vonderviszt,et al.  Characteristic sequential residue environment of amino acids in proteins. , 1986, International journal of peptide and protein research.

[8]  H A Scheraga,et al.  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. , 1988, Journal of biomolecular structure & dynamics.

[9]  I. Simon,et al.  Investigation of protein refolding: a special feature of native structure responsible for refolding ability. , 1985, Journal of theoretical biology.

[10]  H. Scheraga,et al.  Performance of the diffusion equation method in searches for optimum structures of clusters of Lennard-Jones atoms , 1991 .

[11]  H. Scheraga,et al.  Conformational analysis of the 20 naturally occurring amino acid residues using ECEPP. , 1977, Macromolecules.

[12]  Regularities in the primary structure of proteins. , 2009, International journal of peptide and protein research.

[13]  I. Simon,et al.  Predicting isomorphic residue replacements for protein design. , 2009, International journal of peptide and protein research.

[14]  H. Scheraga,et al.  Calculation of protein conformation by the build-up procedure. Application to bovine pancreatic trypsin inhibitor using limited simulated nuclear magnetic resonance data. , 1988, Journal of biomolecular structure & dynamics.

[15]  H A Scheraga,et al.  Calculation of protein conformation as an assembly of stable overlapping segments: application to bovine pancreatic trypsin inhibitor. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Steven G. Louie,et al.  A Monte carlo simulated annealing approach to optimization over continuous variables , 1984 .

[17]  H A Scheraga,et al.  Assessment of some problems associated with prediction of the three-dimensional structure of a protein from its amino-acid sequence. , 1975, Proceedings of the National Academy of Sciences of the United States of America.

[18]  A. Mackay.  A dense non-crystallographic packing of equal spheres , 1962 .

[19]  H. Scheraga,et al.  On the multiple-minima problem in the conformational analysis of molecules: deformation of the potential energy hypersurface by the diffusion equation method , 1989 .

[20]  Akbar Nayeem,et al.  A comparative study of the simulated‐annealing and Monte Carlo‐with‐minimization approaches to the minimum‐energy structures of polypeptides: [Met]‐enkephalin , 1991 .