Literature DB >> 10584295

Important amino acid properties for enhanced thermostability from mesophilic to thermophilic proteins.

M M Gromiha1, M Oobatake, A Sarai.   

Abstract

Understanding the role of various interactions in enhancing the thermostability of proteins is important not only for clarifying the mechanism of protein stability but also for designing stable proteins. In this work, we have analyzed the thermostability of 16 different families by comparing mesophilic and thermophilic proteins with 48 various physicochemical, energetic and conformational properties. We found that the increase in shape, s (location of branch point in side chain) increases the thermostability, whereas, an opposite trend is observed for Gibbs free energy change of hydration for native proteins, GhN, in 14 families. A good correlation is observed between these two properties and the simultaneous increases of -GhN and s is necessary to enhance the thermostability from mesophile to thermophile. The increase in shape, which tends to increase with increasing number of carbon atoms both for polar and non-polar residues, may generate more packing and compactness, and the position of beta and higher order branches may be important for better packing. On the other hand, the increase in -GhN in thermophilic proteins increases the solubility of the proteins. This tendency counterbalances the increases in insolubility and unfolding heat capacity change due to the increase in the number of carbon atoms. Thus, the present results suggest that the stability of thermophilic proteins may be achieved by a balance between better packing and solubility.

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Year:  1999        PMID: 10584295     DOI: 10.1016/s0301-4622(99)00103-9

Source DB:  PubMed          Journal:  Biophys Chem        ISSN: 0301-4622            Impact factor:   2.352


  63 in total

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4.  Intrinsic contributions of polar amino acid residues toward thermal stability of an ABC-ATPase of mesophilic origin.

Authors:  Jyoti Sarin; Gajendra P S Raghava; Pradip K Chakraborti
Journal:  Protein Sci       Date:  2003-09       Impact factor: 6.725

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Authors:  Robert Friedman; John W Drake; Austin L Hughes
Journal:  Genetics       Date:  2004-07       Impact factor: 4.562

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9.  A critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

Authors:  Jianwen Fang
Journal:  Brief Bioinform       Date:  2020-07-15       Impact factor: 11.622

10.  Temperature adaptation at homologous sites in proteins from nine thermophile-mesophile species pairs.

Authors:  John H McDonald
Journal:  Genome Biol Evol       Date:  2010-07-12       Impact factor: 3.416

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