Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production

Alcohol-forming fatty acyl reductases (FARs) catalyze the reduction of thioesters to alcohols and are key enzymes for microbial production of fatty alcohols. Many metabolic engineering strategies utilize FARs to produce fatty alcohols from intracellular acyl-CoA and acyl-ACP pools; however, enzyme activity, especially on acyl-ACPs, remains a significant bottleneck to high-flux production. Here, we engineer FARs with enhanced activity on acyl-ACP substrates by implementing a machine learning (ML)-driven approach to iteratively search the protein fitness landscape. Over the course of ten design-test-learn rounds, we engineer enzymes that produce over twofold more fatty alcohols than the starting natural sequences. We characterize the top sequence and show that it has an enhanced catalytic rate on palmitoyl-ACP. Finally, we analyze the sequence-function data to identify features, like the net charge near the substrate-binding site, that correlate with in vivo activity. This work demonstrates the power of ML to navigate the fitness landscape of traditionally difficult-to-engineer proteins.

The Role of Redox Potential and Molecular Structure of Co(II)-Polypyridine Complexes on the Molecular Catalysis of CO2 Reduction

In this work, we report the electrochemical response of a family of Co(II) complexes, [CoII(L)3]2+ and [CoII(L’)2]2+ (L = 2,2’-bipyridine, 1,10-phenanthroline, 3,4,7,8-tetramethyl-1,10-phenanthroline, 5,6-dimethyl-1,10-phenanthroline, and 4,7-diphenyl-1,10-phenanthroline; L’ = terpyridine and 4-chloro-terpyridine), in the presence and absence of CO2 in order to understand the role of the redox potential and molecular structure on the molecular catalysis of CO2 reduction. The tris chelate complexes exhibited three electron transfer processes [CoII(L)3]2+ ⇄ [CoIII(L)3]3+ + 1e−, [CoΙΙ(L)3]2++1e− ⇄ [CoΙ(L)3]+, and [CoΙ(L)3]+ + 2e- ⇄ [CoΙ(L)(L−)2]−. In the case of complexes with 1,10-phen and 2,2-bipy, the third redox process showed a coupled chemical reaction [CoΙ(L)(L−)2]− → [CoΙ(L−)2]− + L. For bis chelate complexes, three electron transfer processes associated with the redox couples [CoΙΙ(L)2]/[CoIII(L)2]3+, [CoΙΙ(L)2]2+/[CoΙ(L)2]+, and [CoΙ(L)2]+/[CoΙ(L)(L−)] were registered, including a coupled chemical reaction only for the complex containing the ligand 4-chloro-terpyridine. Foot to the wave analysis (FOWA) obtained from cyclic voltammetry experiments allowed us to calculate the catalytic rate constant (k) for the molecular catalysis of CO2 reduction. The complex [Co(3,4,7,8-tm-1,10-phen)3]2+ presented a high k value; moreover, the complex [Co(4-Cl-terpy)3]2+ did not show catalytic activity, indicating that the more negative redox potential and the absence of the coupled chemical reaction increased the molecular catalysis. Density functional theory (DFT) calculations for compounds and CO2 were obtained to rationalize the effect of electronic structure on the catalytic rate constant (k) of CO2 reduction.

A Method for Determining the Kinetics of Small-Molecule-Induced Ubiquitination

Recent advances in targeted protein degradation have enabled chemical hijacking of the ubiquitin–proteasome system to treat disease. The catalytic rate of cereblon (CRBN)-dependent bifunctional degradation activating compounds (BiDAC), which recruit CRBN to a chosen target protein, resulting in its ubiquitination and proteasomal degradation, is an important parameter to consider during the drug discovery process. In this work, an in vitro system was developed to measure the kinetics of BRD4 bromodomain 1 (BD1) ubiquitination by fitting an essential activator kinetic model to these data. The affinities between BiDACs, BD1, and CRBN in the binary complex, ternary complex, and full ubiquitination complex were characterized. Together, this work provides a new tool for understanding and optimizing the catalytic and thermodynamic properties of BiDACs.

On Catalytic Kinetics of Enzymes

Classical enzyme kinetic theories are summarized and linked with modern discoveries here. The sequential catalytic events along time axis by enzyme are analyzed at the molecular level, and by using master equations, this writing tries to connect the microscopic molecular behavior of enzyme to kinetic data (like velocity and catalytic coefficient k) obtained in experiment: 1/k = t equals to the sum of the times taken by the constituent individual steps. The relationships between catalytic coefficient k, catalytic rate or velocity, the amount of time taken by each step and physical or biochemical conditions of the system are discussed, and the perspective and hypothetic equations proposed here regarding diffusion, conformational change, chemical conversion, product release steps and the whole catalytic cycle provide an interpretation of previous experimental observations and can be testified by future experiments.

Solely electrochemical synthesis of Prussian Blue based nanozymes ‘artificial peroxidase’

We report on fully electrochemical flow-through synthesis of Prussian Blue based nanozymes defeating peroxidase in terms of more than 200 times higher catalytic rate constant (kcat=6∙104 s-1). Being reagentless, reproducible,...

On Catalysis by Biological Macromolecular Enzymes

Classical enzyme kinetics are summarized and linked with modern discoveries here. The time course of sequential catalytic events by biological macromolecular enzyme is analyzed at the molecular level; the relationships between catalytic efficiency (turnover number), catalytic rate/velocity, the amount of time taken and physical/biochemical conditions of the system are discussed. This writing tries to connect the microscopic molecular behavior of enzyme to kinetic data obtained in experiment, and the hypothesis proposed here provide an interpretation to previous experimental observations and can be testified by future experiments.