Genetic algorithms (GAs) together with classical pair potentials and density functional theory (DFT) are used to investigate cation order in MgAl2O4 (Spinel). To efficiently locate the global minimum/minima on the sys...
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Genetic algorithms (GAs) together with classical pair potentials and density functional theory (DFT) are used to investigate cation order in MgAl2O4 (Spinel). To efficiently locate the global minimum/minima on the system potential energy surface, corresponding to the ordered and fully equilibrated low-temperature phase, local structural optimizations are essential. Such energy minimizations are expensive at the DFT level, but a comparison of the distribution of the energy minima from DFT and popular classical pair potentials allows one to rapidly tune the GA parameters. We show that GAs are able to find, not only the global minimum on the potential energy, but also other low-energy cation configurations representing possible frozen-in disordered or metastable phases after quenching. The nature of these low-energy configurations can help to interpret the extent of kinetic trapping which hampers the comparison between different experimental studies.
Protein structureprediction is beginning to be, at least partially, successful. Evaluating predictions, however, has many elements of subjectivity, making it difficult to determine the nature and extent of improvemen...
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Protein structureprediction is beginning to be, at least partially, successful. Evaluating predictions, however, has many elements of subjectivity, making it difficult to determine the nature and extent of improvements that are most needed. We describe how the funnel-like nature of energy functions used for protein structureprediction determines their quality and can be quantified using landscape theory and multiple histogram sampling methods. prediction algorithms exhibit a "caldera"-like landscape rather than a perfectly funneled one. Estimates are made of the expected number of effectively distinct structures produced by a prediction algorithm.
A method is developed to compute backbone tertiary folds from the amino acid sequence. In this method, the number of degrees of freedom is drastically reduced by neglecting side-chain flexibility, and by describing ba...
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A method is developed to compute backbone tertiary folds from the amino acid sequence. In this method, the number of degrees of freedom is drastically reduced by neglecting side-chain flexibility, and by describing backbone conformations as combinations of only seven structural states. These are characterized by single values of the dihedral angles phi, psi and omega, representing allowed conformations of the isolated dipeptide. We show that this restrictive model is none the less capable of describing native backbones to within acceptable deviations. Using our backbone description, potentials of mean force are derived from a database of known protein structures, based on statistical influences of single residues and residue pairs on the conformational states in their vicinity along the chain. This yields the force-field component due to local interactions, which is then used to predict lowest-energy conformations from any given amino acid sequence. The prediction algorithm does not require searching conformational space and is therefore extremely fast. Another important asset of our method is that it is able to compute not only the minimum energy conformation, but any number of lowest energy structures, whose relative preferences can be determined from the corresponding computed energy values. The performance of our procedure is tested on short peptides that are likely to be stabilized by local interactions. These include several helical structures and a hexapeptide with a beta-bend conformation, corresponding to peptides shown to have relatively well-defined conformations in aqueous solution, and to protein segments believed to adopt their native conformation early during folding. In addition, several flexible peptides are analysed. Except for the problems encountered in predicting observed disulphide bridges in two of the flexible peptides, and in a somewhat larger fragment comprising residues 30 to 51 of bovine trypsin inhibitor, prediction results compare very
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