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Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions

Overview of attention for article published in PLOS ONE, June 2014
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Title
Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions
Published in
PLOS ONE, June 2014
DOI 10.1371/journal.pone.0100643
Pubmed ID
Authors

Dmitry Suplatov, Nikolay Panin, Evgeny Kirilin, Tatyana Shcherbakova, Pavel Kudryavtsev, Vytas Švedas

Abstract

Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties.

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Geographical breakdown

Country Count As %
United States 2 2%
Spain 1 1%
Brazil 1 1%
Unknown 80 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Researcher 12 14%
Student > Bachelor 10 12%
Student > Master 10 12%
Student > Doctoral Student 7 8%
Other 9 11%
Unknown 17 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 29%
Agricultural and Biological Sciences 22 26%
Chemistry 8 10%
Engineering 3 4%
Computer Science 2 2%
Other 6 7%
Unknown 19 23%