Study of Enzyme Evolution Within the MLE Subgroup Focusing on Characterizing Member Enzymes for the Purpose of Discovering Relationships Among Sequence, Structure, and Function

This investigation explores sequence/structure/function relationships of enzymes by elucidating interesting insights into the structural basis for catalysis as well as potential design principles that can be used to develop catalysts for new reactions. The enolase superfamily possesses the most ubiquitous protein fold in Nature while the muconate lactonizing enzyme (MLE) subgroup represents the most divergent in chemical reactions in the superfamily; therefore, the MLE subgroup is an excellent candidate to appreciate chemistry driven evolution of enzymes. The MLE subgroup, whose members have diverse sequences but make up enzyme catalytic domains of close homology, is a good target of study for understanding the sequence/structure/function relationships. Exploring characterized members in the subgroup has improved our understanding of underlying mechanisms, and exploring members of the subgroup whose functions have not yet been assigned will offer new insights into possible metabolic pathways and enzyme evolution. In order to achieve an efficient, integrative research strategy to move from genomic sequence to actual function assignment, our new approach to assigning correct function to enzymes in the MLE subgroup incorporates two analytic techniques: operon context analysis and computational analysis, along with in vitro enzymology. The benefits of this approach for accurate prediction of a function for selected members of the MLE subgroup are discussed. Integrative analysis of protein functions guided by both sequence assessment and structural prediction will revolutionize the study of protein function assignment in the field of Biology and will promote advances in understanding the relationship between function and structure of proteins in science.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Biophysics and Computational Biology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Sakai, Ayano

Contributors dc:contributor

• Gerlt, John A.

• Chemistry, Biochemistry
• Biology, Bioinformatics
• Biophysics, General

Identifier

(UMI)AAI3395576

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72403