Computational design of orthogonal nucleoside kinases

Enzyme engineering: reaching the maximal catalytic efficiency peak

The practical need for highly efficient enzymes presents new challenges in enzyme engineering, in particular, the need to improve catalytic turnover (k_cat) or efficiency (k_cat/K_M) by several orders of magnitude. However, optimizing catalysis demands navigation through complex and rugged fitness landscapes, with optimization trajectories often leading to strong diminishing returns and dead-ends. When no further improvements are observed in library screens or selections, it remains unclear whether the maximal catalytic efficiency of the enzyme (the catalytic 'fitness peak') has been reached; or perhaps, an alternative combination of mutations exists that could yield additional improvements. Here, we discuss fundamental aspects of the process of catalytic optimization, and offer practical solutions with respect to overcoming optimization plateaus.

Quantification and tracking of genetically engineered dendritic cells for studying immunotherapy

PURPOSE

Genetically encoded reporters can assist in visualizing biological processes in live organisms and have been proposed for longitudinal and noninvasive tracking of therapeutic cells in deep tissue. Cells can be labeled in situ or ex vivo and followed in live subjects over time. Nevertheless, a major challenge for reporter systems is to identify the cell population that actually expresses an active reporter.

METHODS

We have used a nucleoside analog, pyrrolo-2'-deoxycytidine, as an imaging probe for the putative reporter gene, Drosophila melanogaster 2'-deoxynucleoside kinase. Bioengineered cells were imaged in vivo in animal models of brain tumor and immunotherapy using chemical exchange saturation transfer MRI. The number of transduced cells was quantified by flow cytometry based on the optical properties of the probe.

RESULTS

We performed a comparative analysis of six different cell lines and demonstrate utility in a mouse model of immunotherapy. The proposed technology can be used to quantify the number of labeled cells in a given region, and moreover is sensitive enough to detect less than 10,000 cells.

CONCLUSION

This unique technology that enables efficient selection of labeled cells followed by in vivo monitoring with both optical and MRI. Magn Reson Med 79:1010-1019, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Biological phosphorylation of an Unnatural Base Pair (UBP) using a Drosophila melanogaster deoxynucleoside kinase (DmdNK) mutant

One research goal for unnatural base pair (UBP) is to replicate, transcribe and translate them in vivo. Accordingly, the corresponding unnatural nucleoside triphosphates must be available at sufficient concentrations within the cell. To achieve this goal, the unnatural nucleoside analogues must be phosphorylated to the corresponding nucleoside triphosphates by a cascade of three kinases. The first step is the monophosphorylation of unnatural deoxynucleoside catalyzed by deoxynucleoside kinases (dNK), which is generally considered the rate limiting step because of the high specificity of dNKs. Here, we applied a Drosophila melanogaster deoxyribonucleoside kinase (DmdNK) to the phosphorylation of an UBP (a pyrimidine analogue (6-amino-5-nitro-3-(1’-b-d-2’-deoxyribofuranosyl)-2(1H)-pyridone, Z) and its complementary purine analogue (2-amino-8-(1’-b-d-2’-deoxyribofuranosyl)-imidazo[1,2-a]-1,3,5-triazin-4(8H)-one, P). The results showed that DmdNK could efficiently phosphorylate only the dP nucleoside. To improve the catalytic efficiency, a DmdNK-Q81E mutant was created based on rational design and structural analyses. This mutant could efficiently phosphorylate both dZ and dP nucleoside. Structural modeling indicated that the increased efficiency of dZ phosphorylation by the DmdNK-Q81E mutant might be related to the three additional hydrogen bonds formed between E81 and the dZ base. Overall, this study provides a groundwork for the biological phosphorylation and synthesis of unnatural base pair in vivo.

A Single Deoxynucleoside Kinase Variant from Drosophila melanogaster Synthesizes Monophosphates of Nucleosides That Are Components of an Expanded Genetic System

Deoxynucleoside kinase from D. melanogaster (DmdNK) has broad specificity; although it catalyzes the phosphorylation of natural pyrimidine more efficiently than natural purine nucleosides, it accepts all four 2'-deoxynucleosides and many analogues, using ATP as a phosphate donor to give the corresponding deoxynucleoside monophosphates. Here, we show that replacing a single amino acid (glutamine 81 by glutamate) in DmdNK creates a variant that also catalyzes the phosphorylation of nucleosides that form part of an artificially expanded genetic information system (AEGIS). By shuffling hydrogen bonding groups on the nucleobases, AEGIS adds potentially as many as four additional nucleobase pairs to the genetic "alphabet". Specifically, we show that DmdNK Q81E creates the monophosphates from the AEGIS nucleosides dP, dZ, dX, and dK (respectively 2-amino-8-(1'-β-d-2'-deoxyribofuranosyl)-imidazo[1,2-a]-1,3,5-triazin-4(8H)-one, dP; 6-amino-3-(1'-β-d-2'-deoxyribofuranosyl)-5-nitro-1H-pyridin-2-one, dZ; 8-(1'β-d-2'-deoxy-ribofuranosyl)imidazo[1,2-a]-1,3,5-triazine-2(8H)-4(3H)-dione, dX; and 2,4-diamino-5-(1'-β-d-2'-deoxyribofuranosyl)-pyrimidine, dK). Using a coupled enzyme assay, in vitro kinetic parameters were obtained for three of these nucleosides (dP, dX, and dK; the UV absorbance of dZ made it impossible to get its precise kinetic parameters). Thus, DmdNK Q81E appears to be a suitable enzyme to catalyze the first step in the biosynthesis of AEGIS 2'-deoxynucleoside triphosphates in vitro and, perhaps, in vivo, in a cell able to manage plasmids containing AEGIS DNA.

Enantioselective enzymes by computational design and in silico screening

Computational enzyme design holds great promise for providing new biocatalysts for synthetic chemistry. A strategy to design small mutant libraries of complementary enantioselective epoxide hydrolase variants for the production of highly enantioenriched (S,S)-diols and (R,R)-diols is developed. Key features of this strategy (CASCO, catalytic selectivity by computational design) are the design of mutations that favor binding of the substrate in a predefined orientation, the introduction of steric hindrance to prevent unwanted substrate binding modes, and ranking of designs by high-throughput molecular dynamics simulations. Using this strategy we obtained highly stereoselective mutants of limonene epoxide hydrolase after experimental screening of only 37 variants. The results indicate that computational methods can replace a substantial amount of laboratory work when developing enantioselective enzymes.

Redesigning human 2'-deoxycytidine kinase enantioselectivity for L-nucleoside analogues as reporters in positron emission tomography

Recent advances in nuclear medicine have allowed for positron emission tomography (PET) to track transgenes in cell-based therapies using PET reporter gene/probe pairs. A promising example for such reporter gene/probe pairs are engineered nucleoside kinases that effectively phosphorylate isotopically labeled nucleoside analogues. Upon expression in target cells, the kinase facilitates the intracellular accumulation of radionuclide monophosphate, which can be detected by PET imaging. We have employed computational design for the semi-rational engineering of human 2′-deoxycytidine kinase to create a reporter gene with selectivity for l-nucleosides including l-thymidine and 1-(2′-fluoro-5-methyl-β-l-arabinofuranosyl) uracil. Our design strategy relied on a combination of preexisting data from kinetic and structural studies of native kinases, as well as two small, focused libraries of kinase variants to generate an in silico model for assessing the effects of single amino acid changes on favorable activation of l-nucleosides over their corresponding d-enantiomers. The approach identified multiple amino acid positions distal to the active site that conferred desired l-enantioselectivity. Recombination of individual amino acid substitutions yielded orthogonal kinase variants with significantly improved catalytic performance for unnatural l-nucleosides but reduced activity for natural d-nucleosides.

Recent advances in rational approaches for enzyme engineering

Enzymes are an attractive alternative in the asymmetric syntheses of chiral building blocks. To meet the requirements of industrial biotechnology and to introduce new functionalities, the enzymes need to be optimized by protein engineering. This article specifically reviews rational approaches for enzyme engineering and de novo enzyme design involving structure-based approaches developed in recent years for improvement of the enzymes’ performance, broadened substrate range, and creation of novel functionalities to obtain products with high added value for industrial applications.

A generic program for multistate protein design

Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design.

Status of protein engineering for biocatalysts: how to design an industrially useful biocatalyst

Recent advances in the development of both experimental and computational protein engineering tools have enabled a number of further successes in the development of biocatalysts ready for large-scale applications. Key tools are first, the targeting of libraries, leading to far smaller but more useful libraries than in the past, second, the combination of structural, mechanistic, and sequence-based knowledge often based on prior successful cases, and third, the advent of structurally based algorithms allowing the design of novel functions. Based on these tools, a number of improved biocatalysts for pharmaceutical applications have been presented, such as an (R)-transaminase for the synthesis of active pharmaceutical ingredients (APIs) of sitagliptin (Januvia®) and ketoreductases, glucose dehydrogenases, and haloalkane dehalogenases for the API synthesis toward atorvastatin (Lipitor®) and montelukast (Singulair®).