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Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1415))

Abstract

Protein stability is the free energy difference between unfolded and folded states of a protein, which lies in the range of 5–25 kcal/mol. Experimentally, protein stability is measured with circular dichroism, differential scanning calorimetry, and fluorescence spectroscopy using thermal and denaturant denaturation methods. These experimental data have been accumulated in the form of a database, ProTherm, thermodynamic database for proteins and mutants. It also contains sequence and structure information of a protein, experimental methods and conditions, and literature information. Different features such as search, display, and sorting options and visualization tools have been incorporated in the database. ProTherm is a valuable resource for understanding/predicting the stability of proteins and it can be accessed at http://www.abren.net/protherm/. ProTherm has been effectively used to examine the relationship among thermodynamics, structure, and function of proteins. We describe the recent progress on the development of methods for understanding/predicting protein stability, such as (1) general trends on mutational effects on stability, (2) relationship between the stability of protein mutants and amino acid properties, (3) applications of protein three-dimensional structures for predicting their stability upon point mutations, (4) prediction of protein stability upon single mutations from amino acid sequence, and (5) prediction methods for addressing double mutants. A list of online resources for predicting has also been provided.

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Acknowledgments

The work was dedicated to the memory of Prof. Akinori Sarai, the principal investigator for the development and maintenance of ProTherm database. 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, and Dr. K. Saraboji for their stimulating discussions and help at various stages of the work.

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Authors and Affiliations

  1. Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600 036, India

    M. Michael Gromiha & P. Anoosha

  2. Department of Medical Informatics, Tzu Chi University, Hualien, 970, Taiwan

    Liang-Tsung Huang

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  1. M. Michael Gromiha
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  2. P. Anoosha
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  3. Liang-Tsung Huang
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Correspondence to M. Michael Gromiha .

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Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Wien, Austria

    Oliviero Carugo

  2. Technology and Research (A*STAR), Agency for Science, Singapore, Singapore

    Frank Eisenhaber

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Gromiha, M.M., Anoosha, P., Huang, LT. (2016). Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 1415. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3572-7_4

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  • DOI: https://doi.org/10.1007/978-1-4939-3572-7_4

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