## Abstract An efficient and general strategy for the determination of all low‐energy minima of a molecule, viz., the stochastic conformational jump procedure, has been implemented in the BOSS package. In this method, a new structure is generated by random movement (“kick”) of individual atoms with
Systematic stepsize variation: Efficient method for searching conformational space of polypeptides
✍ Scribed by Klein, Christian T.; Mayer, Bernd; K�hler, Gottfried; Wolschann, Peter
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 235 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0192-8651
No coin nor oath required. For personal study only.
✦ Synopsis
A new and efficient method for overcoming the multiple minima
Ž
. problem of polypeptides, the systematic stepsize variation SSV method, is presented. The SSV is based on the assumption that energy barriers can be passed over by sufficiently large rotations about rotatable bonds: randomly Ž chosen dihedral angles are updated starting with a small stepsize i.e., magnitude . of rotation . A new structure is accepted only if it possesses a lower energy than the precedent one. Local minima are passed over by increasing the stepsize systematically. When no new structures are found any longer, the simulation is continued with the starting structure, but other trajectories will be followed due to the random order in updating the torsional angles. First, the method is tested with Met-enkephalin, a peptide with a known global minimum structure; in all runs the latter is found at least once. The global minimum conformations obtained in the simulations show deviations of "0.0004 kcalrmol from the reference structure and, consequently, are perfectly superposable. For Ž . comparison, Metropolis Monte Carlo simulated annealing MMC-SA is performed. To estimate the efficiency of the algorithm depending on the complexity of the optimization problem, homopolymers of Ala and Gly of different lengths are simulated, with both the SSV and the MMC-SA method. The comparative simulations clearly reveal the higher efficiency of SSV compared with MMC-SA.
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A genetic algorithm-driven search method GAP1.0; Genetic . Algorithm Peptide search, version 1.0 has been developed for the computational exploration of peptide conformational space. The suitability of a variety of genetic algorithm operators was evaluated through representative calculations w x Ž .
Three genetic algorithm programs, GAP 1.0, 2.0, and 3.0, were used in conjunction with the ECEPPr2 force field to search the conformation w x space of Met -enkephalin. Each program was proficient at quickly finding many diverse low-energy conformers. Conformer populations displayed a variety of seco
## Abstract Conformations of peptides are the basis for their property studies and the predictions of peptide structures are highly important in life science but very complex in practice. Here, thorough searches on the potential energy surfaces of 13 representative dipeptides by considering all pos