Assessing the predictive capabilities of design heuristics and coarse-grain simulation toward understanding and optimizing site-specific covalent immobilization of ß-lactamase.

For industrial applications, covalent immobilization of enzymes provides minimum leakage, recoverability, reusability, and high stability. Yet, the suitability of a given site on the enzyme for immobilization remains a trial-and-error procedure. Here, we investigate the reliability of design heuristics and a coarse-grain molecular simulation in predicting the optimum sites for covalent immobilization of TEM-1 ß-lactamase. We utilized Escherichia coli-lysate-based cell-free protein synthesis (CFPS) to produce variants containing a site-specific incorporated unnatural amino acid with a unique moiety to facilitate site directed covalent immobilization. To constrain the number of potential immobilization sites, we investigated the predictive capability of several design heuristics. The suitability of immobilization sites was determined by analyzing expression yields, specific activity, immobilization efficiency, and stability of variants. These experimental findings are compared with coarse-grain simulation of TEM-1 domain stability and thermal stability and analyzed for a priori predictive capabilities. This work demonstrates that the design heuristics successfully identify a subset of locations for experimental validation. Specifically, the nucleotide following amber stop codon and domain stability correlate well with the expression yield and specific activity of the variants, respectively. Our approach highlights the advantages of combining coarse-grain simulation and high-throughput experimentation using CFPS to identify optimal enzyme immobilization sites.

Mechanistic discoveries and simulation-guided assay optimization of portable hormone biosensors with cell-free protein synthesis.

Nuclear receptors (NRs) influence nearly every system of the body and our lives depend on correct NR signaling. Thus, a key environmental and pharmaceutical quest is to identify and detect chemicals which interact with nuclear hormone receptors, including endocrine disrupting chemicals (EDCs), therapeutic receptor modulators, and natural hormones. Previously reported biosensors of nuclear hormone receptor ligands facilitated rapid detection of NR ligands using cell-free protein synthesis (CFPS). In this work, the advantages of CFPS are further leveraged and combined with kinetic analysis, autoradiography, and western blot to elucidate the molecular mechanism of this biosensor. Additionally, mathematical simulations of enzyme kinetics are used to optimize the biosensor assay, ultimately lengthening its readable window by five-fold and improving sensor signal strength by two-fold. This approach enabled the creation of an on-demand thyroid hormone biosensor with an observable color-change readout. This mathematical and experimental approach provides insight for engineering rapid and field-deployable CFPS biosensors and promises to improve methods for detecting natural hormones, therapeutic receptor modulators, and EDCs.