Rational design of thiolase substrate specificity for metabolic engineering applications

Abstract

Metabolic engineering efforts require enzymes that are both highly active and specific toward the synthesis of a desired output product to be commercially feasible. The 3‐hydroxyacid (3HA) pathway, also known as the reverse β‐oxidation or coenzyme‐A‐dependent chain‐elongation pathway, can allow for the synthesis of dozens of useful compounds of various chain lengths and functionalities. However, this pathway suffers from byproduct formation, which lowers the yields of the desired longer chain products, as well as increases downstream separation costs. The thiolase enzyme catalyzes the first reaction in this pathway, and its substrate specificity at each of its two catalytic steps sets the chain length and composition of the chemical scaffold upon which the other downstream enzymes act. However, there have been few attempts reported in the literature to rationally engineer thiolase substrate specificity. In this study, we present a model‐guided, rational design study of ordered substrate binding applied to two biosynthetic thiolases, with the goal of increasing the ratio of C6/C4 products formed by the 3HA pathway, 3‐hydroxy‐hexanoic acid and 3‐hydroxybutyric acid. We identify thiolase mutants that result in nearly 10‐fold increases in C6/C4 selectivity. Our findings can extend to other pathways that employ the thiolase for chain elongation, as well as expand our knowledge of sequence–structure–function relationship for this important class of enzymes.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 29, 2018
Source ID
10.1002/bit.26737

Entities

People

  • Brian M Bonk
  • Bruce Tidor
  • Kristala L. J. Prather
  • Michael Hicks
  • Yekaterina Tarasova

Organizations

  • Masdar Institute of Science and Technology
  • Massachusetts Institute of Technology
  • National Institutes of Health
  • United States Department of Defense

Tags

Fields of Study

  • Engineering

Readers

  • Prostate Cancer Biology.
  • Software Engineering.
  • Systems Analysis and Design

Technology Areas

  • Biotechnology