蒙特卡洛模拟退火与距离限制相结合的方法在多肽溶液构象分析中的应用

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Distance geometry and molecular dyndrics are currently employed in determining molecular structures with interatondc distances from NMR NOESY experiment.Because of the flexibility of peptide, distances obtained from NMR are usually not sufficient to coallne its structure. Both distance geometry and molecular dynamics will biasin the cocformational space at this circumstance. Constraint Monte Carlo simulated annealing was established to solve this problem. Distance constraints were included into the ECEPP/2 force field by introducing a harmonic energy term. Conformational analysis of a pentapeptide with eight interatodric distances from NMR was carried out as a test. By comparison of the 100 conformers obtained from constraint simulated annealing and the 100 conformers from distance geometry calculation, it was found that constraint sirnulated armealing can cover the outcomes of distance geometry and at the same time give more con-formers fitting to the experimental data. The result shows that constraint Monte-Carlo simulated aunealing is more valid in constructing peptide structures from NMR distances than currently employed methods when no swhcient distances from NMR are available. Distance geometry and molecular dyndrics are currently employed in determining molecular structures with interatonc distances from NMR NOESY experiment. Since the flexibility of the peptide, distances obtained from NMR are usually not sufficient to coallne its structure. Both distance geometry and molecular dynamics will bias in the cocformational space constraints at this circumstance. Constraint Monte Carlo simulated annealing was established to solve this problem. Distance constraints were included into the ECEPP / 2 force field by introducing a harmonic energy term. Conformational analysis of a pentapeptide with eight interatodric distances from NMR was carried out as a test. By comparison of the 100 conformers obtained from constraint simulated annealing and the 100 conformers from distance geometry calculation, it was found that constraint sirnulated armealing can cover the outcomes of distance geometry and at the same time give more con-formers fitting to the experimental data. The result sho ws that constraint Monte-Carlo simulated aunealing is more valid in constructing peptide structures from NMR distances than currently employed methods when no swhcient distances from NMR are available.
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