In-depth Sequence-Function Characterization Reveals Multiple Pathways to Enhance Enzymatic Activity

Abstract

Deep mutational scanning (DMS) has recently emerged as a powerful method to study protein sequence-function relationships but it has not been well-explored as a guide to enzyme engineering and identifying pathways by which their catalytic cycle may be improved. We report such a demonstration in this work using a Phenylalanine ammonia-lyase (PAL), which deaminates L-phenylalanine to trans-cinnamic acid and has widespread application in chemo-enzymatic synthesis, agriculture, and medicine. In particular, the PAL from Anabaena variabilis (AvPAL*) has garnered significant attention as the active ingredient in Pegvaliase^®, the only FDA-approved drug treating classical Phenylketonuria (PKU). Although an extensive body of literature exists on the structure, substrate-specificity, and catalytic cycle, protein-wide sequence determinants of function remain unknown, as do intermediate reaction steps that limit turnover frequency, all of which has hindered rational engineering of these enzymes. Here, we created a detailed sequence-function landscape of AvPAL* by performing DMS and revealed 112 mutations at 79 functionally relevant sites that affect a positive change in enzyme fitness. Using fitness values and structure-function analysis, we picked a subset of positions for comprehensive single- and multi-site saturation mutagenesis and identified combinations of mutations that led to improved reaction kinetics in cell-free and cellular contexts. We then performed QM/MM and MD to understand the mechanistic role of the most beneficial mutations and observed that different mutants confer improvements via different mechanisms, including stabilizing transition and intermediate states, improving substrate diffusion into the active site, and decreasing product inhibition. This work demonstrates how DMS can be combined with computational analysis to effectively identify significant mutations that enhance enzyme activity along with the underlying mechanisms by which these mutations confer their benefit.

Keywords: PAL; PKU; QM/MM; deep mutational scanning; directed evolution; molecular dynamics; phenylalanine ammonia-lyase; phenylketonuria.

Fig. 1:. Overview of work.

We started with a randomly mutagenized library of AvPAL* and performed deep mutational scanning (DMS). We identified mutational hotspots and used that to guide further mutagenesis and computational modeling studies (QM/MM, MD, and metadynamics) to assess multiple pathways to improve enzyme activity. Finally, culling data from DMS, targeted mutagenesis, and mechanistic modeling aided in design of hyperactive AvPAL* variants.

Fig. 2:. AvPAL* deep mutational scanning (DMS) outcomes.

a) Mutation frequency in naïve and passages #1–3. Positions (a.a.) corresponding to the three most highly enriched positions are labeled (218, 222, and 453). b) Number of mutations sampled at each position in the naïve (dark blue) and passage #3 (red) libraries. The naïve library had an average of 5.6 mutations per position across all 565 positions. Passage #3 library had an average of 0.6 mutations per position across 222 positions. c) Fitness of all mutations present at all positions in the passage #3 library. Negative fitness denotes mutations that decrease in frequency over passages; the highest fitness mutations are labeled (G218A, G218S, M222L, I268T, D306G, G360C, and N453S). Position labels (x-axis) are the same for panels (a-c). From here we identified 79 functionally relevant sites of these, 7 positions T102, G218, M222L, I268, D306, G360 and N453 showed maximum fitness gradient and are thus referred to as hotspots. d) Active site residues of AvPAL* (grey sticks) with phenylalanine ligand (yellow) docked. e) Fitness heatmap of active site residues at passage #3. Wildtype residues of AvPAL* are bordered in black and listed above the residue position. Grey boxes indicate mutations not sampled in library.

Fig. 3:. Identification and location of highest fitness positions.

a) Gradient of fitness is calculated from passages 1–3. Only mutations with a frequency greater than zero in all passages and a passage #3 frequency greater than 0.625 % are shown. A positive gradient indicates increasing fitness across passages. b) Fitness score for the top variant found at that position is mapped to the structure of a single chain of AvPAL*. c) Distance of the α-carbon of docked phenylalanine to the α-carbon of every residue in AvPAL* within the same chain. Residues with a passage #3 fitness < 1 are dark blue, 1–2 are pink, and > 2 are red outlined in black. Active site loops are numbered 1–4 and shaded grey. d) High fitness residues that are distal from the active site are proximal to active sites of other subunits when visualized as part of a homotetramer. Chains A (white), B (light blue), C (dark blue), and D (grey) are shown from top and two side views. Residues near the active site are red. e) Locations of most fit residues relative to the active site of Chain A. Chains A (white), B (light blue), C (dark blue), and D (grey) are shown. The MIO adduct is black and the phenylalanine in yellow with red and blue oxygen and nitrogen atoms, respectively. Fit residues are colored red with sidechains shown. f) Residues 400, 407, 306, and 453 are in the active site loops (rendered opaque) previously identified as important for active site stability. g) Residues 102, 108, 218, and 222, are part of α-helices that form a surface within the active site, near the phenyl ring of the docked phenylalanine.

Fig. 4.. Characterization of site saturation mutant libraries.

Fitness heatmaps of a) ⁷C₁, b) ⁷C₃, and c) ⁷C₇ mutant libraries. Relative fitness is shown as two gradients, from highest fitness (red) to zero fitness (white) and zero fitness to lowest fitness (dark blue). Relative fitness for ¹C₁ library was calculated at each position individually, and at all positions in combination for ⁷C₃ and ⁷C₇. d) Sequence comparison to 100 proteins with greatest homology to AvPAL*. Black cells are the 7 hotspot positions, numbered for AvPAL*. Yellow cells indicate positively fit mutations found during our enrichments that were unique relative to the homologous proteins. A green gradient was applied to the natural residues indicating frequency of residue at each position, with dark green as the most frequent and light green as infrequent.

Figure 5.. Results from MD.

Scatter plots of distance calculated between Y314(O)–Phe(N) and MIO(Cβ2)–Phe(N) atoms in parental AvPAL* (black), a) G218S (green), b) M222L (red), c) N453S (pink), d) L108G (blue), e) T102E-M222L (purple), and f) T102R-M222L-D306G (khaki). The scatter plot shown here is average of two runs. g) RMSF (root mean square fluctuation) plot of protein backbone atoms (carboxylate, Cα, amine). The RMSF values of mutants are normalized to that of the parental enzyme so that only major movements are amplified. All variants are plotted on the same scale. Regions with high deviation from the parent are boxed.

Figure 6.. Results from SMD and umbrella sampling for parental AvPAL* and N453S.

a) The conformational transition of the substrate along the PMF profile, b) extracted from the parental and c) mutant N453S. The peripheral regions of the substrate entry path are highlighted as R1, R2, R3, and R4. They composed of residues 397–403, 308–315 of chain C and 83–94, 446–455 of chain A, respectively. The region marked in as (*) in (a) is the free energy dip that facilities the substrate entry in N453S. d) Binding free energy calculations showed higher affinity of Phe for mutant N453S. e, f) E-S complex extracted from free energy calculations with least binding energies for parental and mutant (dotted box in (d)) reveal that the substrate is stabilized by salt bridges and hydrogen bonds in N453S and only hydrogen bonds in the parent. Green lines show hydrogen bond interactions, orange lines are salt bridge interactions, and light pink lines are hydrophobic interactions.

Figure 7.. Kinetic characterization and whole cell activity of N453S variants.

a–e) Michaelis-Menten plots of AvPAL* and high active variants combined with N453S. L4P-G218S-N453S and T102R-M222L-D306G-N453S did not exhibit any activity at any of the Phe concentrations tested. Kinetic parameters are listed in Table S3. f) Whole cell conversion assay indicates that active enzymes are more active when encapsulated in E. coli cells even though there do not display superior kinetic parameters.

Figure 8.. QM/MM studies on AvPAL* variants.

Proposed reaction mechanism. a-c) Transition states for the first step of the reaction, where proton transfer takes place, with Phe (pink), MIO (yellow), catalytic Y314 (blue), and R317 (green), and other protein residues (light grey) as stick models. Only polar hydrogens are shown for clarity. All distances are in Å. d) Relative energy landscape for AvPAL* (black), M222L (red), G218S (blue), L108G (green), T102E-M222L (pink), and T102R-M222L-D306G (cyan) for all the steps from ground state (GS) to IS1. Energies along paths are not to scale. Relative energy values for TS1 and IS1 from three independent runs are also in Table S10.