|
ИСТИНА |
Войти в систему Регистрация |
Интеллектуальная Система Тематического Исследования НАукометрических данных |
||
COMPARISON OF Phi-VALUES AND FOLDING TIME PREDICTIONS BY USING MONTE-CARLO AND DYNAMIC PROGRAMMING APPROACHESстатья
- Авторы: Galzitskaya O.V., Garbuzynskiy S.O.
- Сборник: Computational Biology: New Research
- Глава в коллективной монографии
- Год издания: 2009
- Первая страница: 277
- Последняя страница: 314
- Аннотация: we calculate time of folding and explore the transition state ensembles for ten proteins with known experimental data at the point of thermodynamic equilibrium between unfolded and native state using a Monte Carlo Go model and Dynamic Programming where each residue is considered to be either folded as in the native state or completely disordered. The order of events in folding simulations has been explored in detail for each of the proteins. The times of folding for ten proteins which reach the native state within a limit of 10(8) Monte Carlo steps are in a good correlation with experimentally measured folding time at mid-transition point (the correlation coefficient is 0.71). A lower correlation was obtained if to use Dynamic Programming approach (the correlation coefficient is 0.53). Moreover, Phi-values calculated from the Monte Carlo simulations for ten proteins correlate with experimental data (the correlation coefficient is 0.41) practically at the same level as Phi-values calculated from Dynamic Programming approach (the correlation coefficient is 0.48). The model provides good prediction of folding nuclei for proteins whose 3D structures have been determined by X-ray, and exhibits a more limited success for proteins whose structures have been determined by NMR.
- Добавил в систему: Галзитская Оксана Валериановна