Pre-equilibrium competitive library screening for tuning inhibitor association rate and specificity toward serine proteases

Abstract

High structural and sequence similarity within protein families can pose significant challenges to the development of selective inhibitors, especially toward proteolytic enzymes. Such enzymes usually belong to large families of closely similar proteases and may also hydrolyze, with different rates, protein- or peptide-based inhibitors. To address this challenge, we employed a combinatorial yeast surface display library approach complemented with a novel pre-equilibrium, competitive screening strategy for facile assessment of the effects of multiple mutations on inhibitor association rates and binding specificity. As a proof of principle for this combined approach, we utilized this strategy to alter inhibitor/protease association rates and to tailor the selectivity of the amyloid β-protein precursor Kunitz protease inhibitor domain (APPI) for inhibition of the oncogenic protease mesotrypsin, in the presence of three competing serine proteases, anionic trypsin, cationic trypsin and kallikrein-6. We generated a variant, designated APPI_{P13W/M17G/I18F/F34V}, with up to 30-fold greater specificity relative to the parental APPI_{M17G/I18F/F34V} protein, and 6500- to 230 000-fold improved specificity relative to the wild-type APPI protein in the presence of the other proteases tested. A series of molecular docking simulations suggested a mechanism of interaction that supported the biochemical results. These simulations predicted that the selectivity and specificity are affected by the interaction of the mutated APPI residues with nonconserved enzyme residues located in or near the binding site. Our strategy will facilitate a better understanding of the binding landscape of multispecific proteins and will pave the way for design of new drugs and diagnostic tools targeting proteases and other proteins.

Keywords: directed evolution; protease inhibitor; protein engineering; protein–protein interactions (PPIs); serine proteases.

Figure 1

Determination of enzyme concentrations for selective maturation screenings. (A) Binding titration curves of yeast-displayed APPI_{M17G/I18F/F34V} with fluorescently labeled enzymes and corresponding K_d values are shown in the top panel. The zoom-in in the bottom panel was used to determine enzyme concentrations that produced similar binding signals (dashed green line). Calculated K_d values for cationic trypsin, anionic trypsin, kallikrein-6 and mesotrypsin were 31, 42, 55, and 26 nM, respectively. Data were analyzed using Prism, GraphPad Software, fitted to a one-site binding model. *Normalized fluorescence is the mean fluorescence value obtained by flow cytometry analysis normalized to the yeast autofluorescence. (B) Flow cytometry analysis of enzyme competition for the yeast-displayed APPI_{M17G/I18F/F34V}. Simultaneous competition reactions of mesotrypsin against cationic trypsin (top plot), anionic trypsin (middle plot) or kallikrein-6 (bottom plot) are shown. X and Y axes are fluorescence intensity signals of yeast-displayed APPI (represented by each point on the graph) for mesotrypsin binding (labeled with DyLight 488 fluorophore), and competitor binding (labeled with DyLight 650 fluorophore), respectively. Enzyme concentrations were as determined from (A) and are specified on each axis. Flow cytometry signals from each competition plot showed similar cell distributions and demonstrated an unbiased system at the enzyme concentrations used. Non-induced cells are located in the bottom left quadrant of each plot.

Figure 2

Selective maturation of yeast-displayed APPI. The APPI library was sorted for preference for mesotrypsin binding over cationic trypsin, anionic trypsin and kallikrein-6. (A) General scheme of the selective maturation procedure: (I) fluorescently labeled mesotrypsin (488 fluorophore) and competitor enzymes (labeled with 650 fluorophore) were allowed to compete for APPI binding; (II) APPI clones that favored mesotrypsin binding were selected by FACS [e.g., as S₂ population in (B)]. (B) FACS of the initial selectivity sort (S₁). X and Y axes are fluorescence intensity signals of the yeast-displayed APPI library (represented by each point on the graph) (S₁) for mesotrypsin binding (labeled with DyLight 488 fluorophore), and competitors binding (labeled with DyLight 650 fluorophore), respectively. Fluorescence signals from the YSD APPI library showed several populations with high heterogeneity for enzyme binding, suggesting that APPI variants in the library had different enzyme specificities. Non-induced cells are located in the bottom left quadrant of each plot. A diagonal sorting gate (green) was used to select the S₂ population (having a high affinity to mesotrypsin but relatively low affinity to the other competitor enzymes). (C) 3D-bar plot of mesotrypsin/competitor binding ratios obtained by flow cytometry analysis. Ratios of mesotrypsin binding relative to the competitor binding (competition ratio) are shown for sorting rounds S₁- S₅. Higher ratios indicate higher mesotrypsin binding relative to the binding of competitors. Concentrations of mesotrypsin were 25, 12, 6, and 3 nM for sorts S₁, S_2, S₃ and S₄, respectively. The concentrations of anionic trypsin, cationic trypsin and kallikrein-6 in all sorts were 12.5, 4.7 and 7 nM, respectively. Red columns indicate values obtained upon sorting.

Figure 3

Selectivity-matured APPI variants show improved mesotrypsin specificity in the yeast surface display format. The affinity of yeast-displayed APPI variants that had been sorted for mesotrypsin binding specificity was determined by flow cytometry analysis for mesotrypsin (10 nM) relative to the competitor proteins (in concentrations of 12.5, 4.7, and 7 nM for anionic trypsin, cationic trypsin, and kallikrein-6, respectively). Specificity enhancement is the value obtained relative to APPI_{M17G/I18F/F34V}; therefore, numbers greater than 1 indicate that specificity was improved. Results (means ±SD) were obtained from three independent experiments.

Figure 4

Kinetics of enzyme inhibition by APPI. Representative examples of determination of the kinetic constants for enzyme inhibition by APPI. (A) Progress curves for the inhibition of mesotrypsin by APPI_{M17G/I18F/F34V} [designated APPI_3MUT]. Mesotrypsin cleavage of the peptide substrate Z-GPR-pNA was competitively inhibited by APPI_{M17G/I18F/F34V}. Experimental values are shown in black, with the curve-fit to equation 2 shown as dashed red lines. APPI_{M17G/I18F/F34V} concentrations are shown on the right. V_s and V₀ are the steady-state rates in the presence and absence of inhibitor, and k_obs is the observed first-order rate constant, which describes the transition from V₀ to V_s from which the kinetic constants were calculated. (B) Slow, tight binding inhibition of mesotrypsin by APPI_{M17G/I18F/F34V}. Values of the equilibrium inhibition constant ( $K_i^{eq}$) were calculated from the steady-state portion of the progress curves in (A) using equation 1. (C) Determination of kinetic constants (k_on and k_off) for mesotrypsin inhibition by APPI_{M17G/I18F/F34V}. A plot with linear dependence of k_obs on the inhibitor concentration (according to equation 3) facilitated the calculation of k_on and k_off. (D) Progress curves for kallikrein-6 inhibition by APPI_{M17G/I18F/F34V}. Kallikrein-6 cleavage of the peptide substrate BOC-Phe–Ser–Arg-AMC was competitively inhibited by APPI_{M17G/I18F/F34V}. Experimental values are shown in black, with the curve-fit to equation 7 shown as a dashed red line. k_off is the first-order off-rate constant, which describes the transition from complete inhibition to a steady-state rate of partial inhibition. Concentrations of enzymes, inhibitors and substrates and the reaction time for each inhibition experiment are summarized in Table S1. Results are the averages of at least three independent experiments.

Figure 5

Docked models of APPI_{P13W/M17G/I18F/F34V} complexed with human mesotrypsin and kallikrein-6. A) Mesotrypsin is depicted as a green surface and APPI as a purple ribbon, with Trp-13 shown by an orange stick representation. B) Detail of predicted interactions between Trp-13 (orange) of APPI (purple) with mesotrypsin (green). APPI Tyr-35 exhibits a potential π-cation interaction with Arg-96 of mesotrypsin, while APPI Trp-13 forms a similar interaction with mesotrypsin Lys-175. C) Detail of predicted interactions between APPI Trp-13 and kallikrein-6. Kallikrein-6 is represented by orange ribbons and APPI_{P13W/M17G/I18F/F34V} is shown in purple. Kallikrein-6 His-99 may potentially clash with APPI Trp-13 (residues shown by space-filling model). Kallikrein-6 residues Gln-175, Ala-96 and Ala-97 (shown by stick representations) do not form the potentially stabilizing interactions observed for the alternative residues found in these positions in mesotrypsin, as described in panel B.