Integrating computational methods to retrofit enzymes to synthetic pathways

Abstract

Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target compounds with high yields and turnover rates. We use integrated computational methods to generate and quantify the performance of novel biosynthetic routes that contain highly optimized catalysts. Engineering a novel reaction pathway entails addressing feasibility on multiple levels, which involves handling the complexity of large-scale biochemical networks while respecting the critical chemical phenomena at the atomistic scale. To pursue this multi-layer challenge, our strategy merges knowledge-based metabolic engineering methods with computational chemistry methods. By bridging multiple disciplines, we provide an integral computational framework that could accelerate the discovery and implementation of novel biosynthetic production routes. Using this approach, we have identified and optimized a novel biosynthetic route for the production of 3HP from pyruvate.

Knowledge-driven approaches for engineering complex metabolic pathways in plants

“…The integration of metabolic, thermodynamic and kinetic data can be used to build logic models that help to define the most suitable intervention points as recently described in microbial systems [18,19], and as applied specifically to glycolysis [20], protein synthesis [21] and the retrofitting of novel enzymes into synthetic metabolic pathways [22].…”

Design of computational retrobiosynthesis tools for the design of de novo synthetic pathways

“…The enzymes encoded by those genes might be able to catalyze novel reactions but with very low activity, or they might perform very similar catalysis reactions, as they will belong to the same 3rd level in the Enzyme Commission (EC) classification system. Therefore, one must use evolution-based protein engineering and computational protein design [32 ] to obtain sequences and enzymes for the experimental implementation of novel pathways with significant performance [7,45].…”

The Need for Integrated Approaches in Metabolic Engineering

“…BNICE uses existing enzyme chemistry as a groundwork for novel enzyme mechanisms that can be fine-tuned and tailored via minimal enzyme reengineering. Several examples of in silico strategies for the reengineering of naturally occurring enzymes into novel biocatalysts are shown by the work of (1) Cho et al (2010), who predicted novel enzyme activities on the basis of physicochemical properties of substrate/product pairs, (2) Brunk et al (2012), who predicted novel enzyme activity within a biosynthetic pathway (Henry et al 2010) on the basis of 3D protein structural characteristics and molecular dynamics simulations (Fig. 4), and (3) Campodonico et al (2014), who predicted enzyme similarity on the basis of enzyme commission classification.…”