Evolutionary algorithms are parallel computing algorithms and simulated annealing algorithm is a sequential computing algorithm. This paper inserts simulated annealing into evolutionary computations and successful developed a hybrid Self-Adaptive Evolutionary Strategy \mu+\lambda method and a hybrid Self-Adaptive Classical Evolutionary Programming method. Numerical results on more than 40 benchmark test problems of global optimization show that the hybrid methods presented in this paper are very effective. Lennard-Jones potential energy minimization is another benchmark for testing new global optimization algorithms. It is studied through the amyloid fibril constructions by this paper. To date , there is little molecular structural data available  on the AGAAAAGA palindrome in the hydrophobic region ( 113-120 ) of prion proteins .This region belongs to the N-terminal unstructured region ( 1-123 ) of prion proteins , the structure of which has proved hard to determine using NMR spectroscopy or X-ray crystallography due to the insoluble and noncrystalline nature of the amyloid fibril . However, computer computational optimization can easily obtain a description of this peptide at a submicroscopic level. The hybrid methods presented in this paper will be applied to construct amyloid fibril molecular structures of the prion 113-120 region .
X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy are two powerful tools to determine the protein 3D structure. However, not all proteins can be successfully crystallized, particularly for membrane proteins. Although NMR spectroscopy is indeed very powerful in determining the 3D structures of membrane proteins, same as X-ray crystallography, it is still very time-consuming and expensive. Under many circumstances, due to the noncrystalline and insoluble nature of some proteins, X-ray and NMR cannot be used at all. Computational approaches, however, allow us to obtain a description of the protein 3D structure at a submicroscopic level. To the best of the author's knowledge , there is little structural data available to date on the AGAAAAGA palindrome in the hydrophobic region ( 113--120 ) of prion proteins , which falls just within the N-terminal unstructured region ( 1--123 ) of prion proteins . Many experimental studies have shown that the AGAAAAGA region has amyloid fibril forming properties and plays an important role in prion diseases. However, due to the noncrystalline and insoluble nature of the amyloid fibril , little structural data on the AGAAAAGA is available. This paper introduces a simple optimization strategy approach to address the 3D atomic-resolution structure of prion AGAAAAGA amyloid fibrils. Atomic-resolution structures of prion AGAAAAGA amyloid fibrils got in this paper are useful for the drive to find treatments for prion diseases in the field of medicinal chemistry .
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Evolutionary algorithms are parallel computing algorithms and simulated annealing algorithm is a sequential computing algorithm. This paper inserts simulated annealing into evolutionary computations and successful developed a hybrid Self-Adaptive Evolutionary Strategy \mu+\lambda method and a hybrid Self-Adaptive Classical Evolutionary Programming method. Numerical results on more than 40 benchmark test problems of global optimization show that the hybrid methods presented in this paper are very effective. Lennard-Jones potential energy minimization is another benchmark for testing new global optimization algorithms. It is studied through the amyloid fibril constructions by this paper. To date
X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy are two powerful tools to determine the protein 3D structure. However, not all proteins can be successfully crystallized, particularly for membrane proteins. Although NMR spectroscopy is indeed very powerful in determining the 3D structures of membrane proteins, same as X-ray crystallography, it is still very time-consuming and expensive. Under many circumstances, due to the noncrystalline and insoluble nature of some proteins, X-ray and NMR cannot be used at all. Computational approaches, however, allow us to obtain a description of the protein 3D structure at a submicroscopic level. To the best of the author's knowledge
D
molecular
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to date
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113-120
113--120
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.This region belongs to
, which falls just within
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1-123
1--123
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, the structure of which has proved hard to determine using NMR spectroscopy or X-ray crystallography
. Many experimental studies have shown that the AGAAAAGA region has amyloid fibril forming properties and plays an important role in prion diseases. However,
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insoluble and noncrystalline
noncrystalline and insoluble
R
. However, computer computational optimization can easily obtain a description of this peptide at a submicroscopic level. The hybrid methods presented in this paper will be applied to construct amyloid fibril molecular structures of the prion 113-120 region
, little structural data on the AGAAAAGA is available. This paper introduces a simple optimization strategy approach to address the 3D atomic-resolution structure of prion AGAAAAGA amyloid fibrils. Atomic-resolution structures of prion AGAAAAGA amyloid fibrils got in this paper are useful for the drive to find treatments for prion diseases in the field of medicinal chemistry