Literature DB >> 19216927

A computational approach for the rational design of stable proteins and enzymes: optimization of surface charge-charge interactions.

Katrina L Schweiker1, George I Makhatadze.   

Abstract

The design of stable proteins and enzymes is not only of particular biotechnological importance, but also addresses some important fundamental questions. While there are a number of different options available for designing or engineering stable proteins, the field of computational design provides fast and universal methods for stabilizing proteins of interest. One of the successful computational design strategies focuses on stabilizing proteins through the optimization of charge-charge interactions on the protein surface. By optimizing surface interactions, it is possible to alleviate some of the challenges that accompany efforts to redesign the protein core. The rational design of surface charge-charge interactions also allows one to optimize only the interactions that are distant from binding sites or active sites, making it possible to increase stability without adversely affecting activity. The optimization of surface charge-charge interactions is discussed in detail along with the experimental evidence to demonstrate that this is a robust and universal approach to designing proteins with enhanced stability.

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Year:  2009        PMID: 19216927     DOI: 10.1016/S0076-6879(08)03807-X

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  12 in total

1.  Increasing protein stability: importance of DeltaC(p) and the denatured state.

Authors:  Hailong Fu; Gerald Grimsley; J Martin Scholtz; C Nick Pace
Journal:  Protein Sci       Date:  2010-05       Impact factor: 6.725

2.  Modulation of folding energy landscape by charge-charge interactions: linking experiments with computational modeling.

Authors:  Franco O Tzul; Katrina L Schweiker; George I Makhatadze
Journal:  Proc Natl Acad Sci U S A       Date:  2015-01-06       Impact factor: 11.205

3.  Proton pump inhibitors have pH-dependent effects on the thermostability of the carboxyl-terminal domain of voltage-gated proton channel Hv1.

Authors:  Qing Zhao; Weiyan Zuo; Shangrong Zhang; Yongqiang Zhang; Chuanyong Li; Shu Jie Li
Journal:  Eur Biophys J       Date:  2017-09-09       Impact factor: 1.733

4.  Computational design of a thermostable mutant of cocaine esterase via molecular dynamics simulations.

Authors:  Xiaoqin Huang; Daquan Gao; Chang-Guo Zhan
Journal:  Org Biomol Chem       Date:  2011-03-04       Impact factor: 3.876

5.  Electrostatic contribution of surface charge residues to the stability of a thermophilic protein: benchmarking experimental and predicted pKa values.

Authors:  Chi-Ho Chan; Cecily C Wilbanks; George I Makhatadze; Kam-Bo Wong
Journal:  PLoS One       Date:  2012-01-18       Impact factor: 3.240

6.  Investigation of Supercharging as A Strategy to Enhance the Solubility and Plasminogen Cleavage Activity of Reteplase.

Authors:  Hooria Seyedhosseini Ghaheh; Mohamad Reza Ganjalikhany; Parichehreh Yaghmaei; Morteza Pourfarzam; Hamid Mir Mohammad Sadeghi
Journal:  Iran J Biotechnol       Date:  2020-10-01       Impact factor: 1.671

7.  PROTS-RF: a robust model for predicting mutation-induced protein stability changes.

Authors:  Yunqi Li; Jianwen Fang
Journal:  PLoS One       Date:  2012-10-15       Impact factor: 3.240

8.  In silico classification of proteins from acidic and neutral cytoplasms.

Authors:  Yaping Fang; C Russell Middaugh; Jianwen Fang
Journal:  PLoS One       Date:  2012-09-26       Impact factor: 3.240

9.  A novel scoring function for discriminating hyperthermophilic and mesophilic proteins with application to predicting relative thermostability of protein mutants.

Authors:  Yunqi Li; C Russell Middaugh; Jianwen Fang
Journal:  BMC Bioinformatics       Date:  2010-01-28       Impact factor: 3.169

10.  Engineering a more thermostable blue light photo receptor Bacillus subtilis YtvA LOV domain by a computer aided rational design method.

Authors:  Xiangfei Song; Yefei Wang; Zhiyu Shu; Jingbo Hong; Tong Li; Lishan Yao
Journal:  PLoS Comput Biol       Date:  2013-07-04       Impact factor: 4.475

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