The role of side chain entropy and mutual information for improving the de novo design of Kemp eliminases KE07 and KE70

Literature Information

Publication Date 2016-06-24
DOI 10.1039/C6CP03622H
Impact Factor 3.676
Authors

Asmit Bhowmick, Sudhir C. Sharma, Hallie Honma


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Abstract

Side chain entropy and mutual entropy information between residue pairs have been calculated for two de novo designed Kemp eliminase enzymes, KE07 and KE70, and for their most improved versions at the end of laboratory directed evolution (LDE). We find that entropy, not just enthalpy, helped to destabilize the preference for the reactant state complex of the designed enzyme as well as favoring stabilization of the transition state complex for the best LDE enzymes. Furthermore, residues with the highest side chain couplings as measured by mutual information, when experimentally mutated, were found to diminish or annihilate catalytic activity, some of which were far from the active site. In summary, our findings demonstrate how side chain fluctuations and their coupling can be an important design feature for de novo enzymes, and furthermore could be utilized in the computational steps in lieu of or in addition to the LDE steps in future enzyme design projects.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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