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Sampling of Protein Conformations with Computers to Predict the Native Structure

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Book cover High-Performance Computing (ISHPC 2005, ALPS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4759))

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Abstract

Native-structure prediction of proteins only from the amino-acid sequential information, without using information from a sequence-structure database of proteins, has not yet been succeeded. Computer simulation is now popular in protein conformational sampling for the prediction. The sampling is, however, hopelessly difficult when a conventional simulation technique (canonical molecular dynamics simulation) is used, because the conformation is frequently trapped in energy minima in the conformational space. This trapping makes the sampling efficiency considerable poor. I explain an efficient conformational sampling algorithm, multicanonical molecular dynamics simulation, recently developed. Results on the sampling of polypeptide chains showed that the conformation easily overcomes the energy barriers between the energy minima with using this method.

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Jesús Labarta Kazuki Joe Toshinori Sato

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© 2008 Springer-Verlag Berlin Heidelberg

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Higo, J. (2008). Sampling of Protein Conformations with Computers to Predict the Native Structure. In: Labarta, J., Joe, K., Sato, T. (eds) High-Performance Computing. ISHPC ALPS 2005 2006. Lecture Notes in Computer Science, vol 4759. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77704-5_35

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  • DOI: https://doi.org/10.1007/978-3-540-77704-5_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77703-8

  • Online ISBN: 978-3-540-77704-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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