Effective conformational search methods for biological macromolecules
The configuration space of many complex physical systems presents a rough energy landscape consisting of tremendous number of local minima separated by high energy barriers. One way to overcome these barriers is to perform the simulation in a generalized-ensemble where each state is weighted by a...
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| Veröffentlicht in: | Физика низких температур |
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| Datum: | 2007 |
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| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Фізико-технічний інститут низьких температур ім. Б.І. Вєркіна НАН України
2007
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| Online Zugang: | https://nasplib.isofts.kiev.ua/handle/123456789/120928 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | Effective conformational search methods for biological macromolecules / T. Çelik // Физика низких температур. — 2007. — Т. 33, № 9. — С. 1052–1054. — Бібліогр.: 9 назв. — англ. |
Institution
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Zusammenfassung: | The configuration space of many complex physical systems presents a rough energy landscape consisting
of tremendous number of local minima separated by high energy barriers. One way to overcome these
barriers is to perform the simulation in a generalized-ensemble where each state is weighted by a
non-Boltzmann probability weight factor. Multicanonical Ensemble Approach overcomes this difficulty by
performing a random walk in one-dimensional energy space. Our attempts to design hybrid generalized ensemble
algorithms will be reported. The folding of a protein into its native structure involves one or more
transitions between distinct phases. The representation of the energy landscape would be useful for the determination
of the conformational transition temperatures. Such a study would lead to clear indications of
the equilibrium conformations of proteins and provide a detailed picture of the folding pathway. The topographic
structure of energy landscape of short peptides will be presented.
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| ISSN: | 0132-6414 |