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Thermodynamic Database for Proteins: Features and Applications

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 609))

Abstract

We have developed a thermodynamic database for proteins and mutants, ProTherm, which is a collection of a large number of thermodynamic data on protein stability along with the sequence and structure information, experimental methods and conditions, and literature information. This is a valuable resource for understanding/predicting the stability of proteins, and it can be accessible at http://www.gibk26.bse.kyutech.ac.jp/jouhou/Protherm/protherm.html. ProTherm has several features including various search, display, and sorting options and visualization tools. We have analyzed the data in ProTherm to examine the relationship among thermodynamics, structure, and function of proteins. We describe the progress on the development of methods for understanding/predicting protein stability, such as (i) relationship between the stability of protein mutants and amino acid properties, (ii) average assignment method, (iii) empirical energy functions, (iv) torsion, distance, and contact potentials, and (v) machine learning techniques. The list of online resources for predicting protein stability has also been provided.

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Acknowledgments

We thank Dr. Oliviero Carugo for the invitation to contribute the article. We also acknowledge Prof. M.N. Ponnuswamy, Dr. A. Bava, Dr. H. Uedaira, Dr. H. Kono, Mr. K. Kitajima, Dr. V. Parthiban, Dr. L. Huang, and Dr. K. Saraboji for stimulating discussions and help at various stages of the work.

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Authors and Affiliations

  1. Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan

    M. Michael Gromiha

  2. Department of Bioscience & Bioinformatics, Kyushu Institute of Technology (KIT), Iizuka, Japan

    Akinori Sarai

Authors
  1. M. Michael Gromiha
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  2. Akinori Sarai
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Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Dr. Bohr-Gasse 9, Wien, 1030, Austria

    Oliviero Carugo

  2. Research (A*STAR), Agency for Science & Technology, Biopolis Street 30, Singapore, 138671, Singapore

    Frank Eisenhaber

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Gromiha, M.M., Sarai, A. (2010). Thermodynamic Database for Proteins: Features and Applications. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 609. Humana Press. https://doi.org/10.1007/978-1-60327-241-4_6

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  • DOI: https://doi.org/10.1007/978-1-60327-241-4_6

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-240-7

  • Online ISBN: 978-1-60327-241-4

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