Allosteric Communications between Domains Modulate the Activity of Matrix Metalloprotease-1

Abstract

An understanding of the structure-dynamics relationship is essential for understanding how a protein works. Prior research has shown that the activity of a protein correlates with intradomain dynamics occurring at picosecond to millisecond timescales. However, the correlation between interdomain dynamics and the function of a protein is poorly understood. Here, we show that communications between the catalytic and hemopexin domains of matrix metalloprotease-1 (MMP1) on type 1 collagen fibrils correlate with its activity. Using single-molecule Förster resonance energy transfer, we identified functionally relevant open conformations in which the two MMP1 domains are well separated, which were significantly absent for catalytically inactive point mutant (E219Q) of MMP1 and could be modulated by an inhibitor or an enhancer of activity. The observed relevance of open conformations resolves the debate about the roles of open and closed MMP1 structures in function. We fitted the histograms of single-molecule Förster resonance energy transfer values to a sum of two Gaussians and the autocorrelations to an exponential and power law. We used a two-state Poisson process to describe the dynamics and calculate the kinetic rates from the fit parameters. All-atom and coarse-grained simulations reproduced some of the experimental features and revealed substrate-dependent MMP1 dynamics. Our results suggest that an interdomain separation facilitates opening up the catalytic pocket so that the collagen chains come closer to the MMP1 active site. Coordination of functional conformations at different parts of MMP1 occurs via allosteric communications that can take place via interactions mediated by collagen even if the linker between the domains is absent. Modeling dynamics as a Poisson process enables connecting the picosecond timescales of molecular dynamics simulations with the millisecond timescales of single-molecule measurements. Water-soluble MMP1 interacting with water-insoluble collagen fibrils poses challenges for biochemical studies that the single-molecule tracking can overcome for other insoluble substrates. Interdomain communications are likely important for multidomain proteins.

Figure 1

Single-molecule measurement of MMP1 dynamics on type 1 collagen fibril. (A) Relative positions of the MMP1 domains and residues (green and red spheres) created using 4AUO. (B) Left panel: 12% sodium dodecyl sulfate polyacrylamide gel electrophoresis of labeled MMP1; right panel: fluorescence from degraded peptide substrate as a function of time for unlabeled (green squares) and labeled (red circles) MMP1 at 37°C. Solid lines are respective best fits to y = a − b × exp(−kt). After calibration, the specific activity is ∼1000 pmol/min/μg. The error bars are the SDs of three technical repeats. (C) Schematics of the TIRF microscope. (D) Emission intensities of the two dyes attached to active MMP1. Low FRET conformations lead to high Alexa Fluor 555 (Thermo Fisher Scientific) emission, whereas high FRET conformations lead to low Alexa Fluor 555 (Thermo Fisher Scientific) emission. Anticorrelated Alexa Fluor 647 and Alexa Fluor 555 (Thermo Fisher Scientific) emissions, I_A and I_D, respectively, indicate the conformational dynamics of MMP1. To see this figure in color, go online.

Figure 2

Activity-dependent interdomain dynamics of MMP1 on reconstituted type 1 collagen fibrils at 22°C with a 100-ms time resolution. Area-normalized histograms of MMP1 interdomain distance (more than 300,000 FRET values for each condition; bin size = 0.005) (A) without ligand, (B) in the presence of MMP9 (an enhancer), and (C) in the presence of tetracycline (an inhibitor) for active (blue) and inactive (orange) MMP1. All histograms are fitted to a sum of two Gaussians (active: solid blue line; inactive: solid red line). Blue and orange lines indicate the peak positions for active and inactive MMP1 without ligands, whereas blue and orange arrows indicate the directions of shifts of the FRET peaks in the presence of ligands. Autocorrelations of MMP1 interdomain distance (D) without ligand, (E) in the presence of MMP9, and (F) in the presence of tetracycline for active (blue) and inactive (orange) MMP1. All autocorrelations are fitted to exponentials and power laws (exponential fit to active: dashed black line; power law fit to active: dashed red line; exponential fit to inactive: solid black line; power law fit to inactive: solid green line). The error bars in histograms and autocorrelations represent the square roots of the bin counts and the the standard errors of the means (SE) and are too small to be seen. The Supporting Materials and Methods contain the fit equations and the best-fit parameters for histograms (Table S1) and autocorrelations (Table S2). To see this figure in color, go online.

Figure 3

Simulated MMP1 interdomain dynamics as a Poisson process. (A) Examples of simulated two-state FRET trajectories with noise for active (blue) and inactive (orange) MMP1. (B) Histograms of simulated FRET values. (C) Autocorrelations of simulated trajectories recover the sum, k1 + k2, from exponential fits (active: dashed black line; inactive: solid black line). As expected, the power law does not fit autocorrelations (active: dashed red line; inactive: solid green line). Exponential fits recover k1 + k2 with and without noise. The addition of noise changes the width of the FRET histograms and y-intercepts. The error bars are the SEs for histograms and autocorrelations and are too small to be seen. The Supporting Materials and Methods contain the best-fit parameters for histograms (Table S4) and autocorrelations (Table S5). To see this figure in color, go online.

Figure 4

All-atom MD simulations with collagen backbone restrained (A and B) and unrestrained (C and D). Simulated dynamics using GROMACS simulation package at 37°C with a 2-fs time step, data saved every 5 ps, and 225- and 700-ns simulations for restrained and unrestrained, respectively. (A) Area-normalized histograms of simulated dynamics with bin size = 0.02 nm and (B) autocorrelations for active (blue) and inactive (orange) with the collagen backbone restrained by an energy penalty of 1000 kJ/mol. (C) Area-normalized histograms of simulated dynamics and (D) autocorrelations for active (blue) and inactive (orange) with the collagen backbone unrestrained. All histograms are fitted to a sum of two Gaussians (active: solid blue line; inactive: solid red line). All autocorrelations are fitted to exponentials and power laws (exponential fit to active: dashed black line; power law fit to active: dashed red line; exponential fit to inactive: solid black line; power law fit to inactive: solid green line). The error bars in the histograms represent the square roots of the bin counts and are too small to be seen, whereas the autocorrelations do not have error bars. The Supporting Materials and Methods contain the best-fit parameters for histograms (Table S6) and autocorrelations (Table S7). To see this figure in color, go online.

Figure 5

Insights from all-atom MD simulations with collagen backbone restrained (A and B) and unrestrained (C and D). Three-dimensional scatter plots of S142–S366 distance (represents interdomain dynamics), N171–T230 distance (represents the opening of the MMP1 catalytic pocket), and rms distance between the MMP1 catalytic site and the cleavage sites on three collagen chains for active (blue) and inactive (orange) MMP1. Two-dimensional projections of the scatter plots are in gray. The clusters encircled in red in (A) represent the plausible catalytically relevant conformations. To see this figure in color, go online.

Figure 6

Two-state simulations at faster nanosecond timescales. Different trials with the same underlying parameters produced different (A) trajectories (blue: active MMP1; orange: inactive MMP1), (B) histograms with bin size = 0.005 (active: solid blue line; inactive: solid orange line), and (C) autocorrelations (active: blue circle; inactive: orange diamond). Different trials of simulations lead to different results even though the underlying process is the same two-state Poisson process. It is challenging to see hidden transitions in the example trajectories because the difference between S1 and S2 (∼0.1) is similar to the noise levels (∼0.1). For simulated trajectories with the same parameters but without noise, see Fig. S3A. To see this figure in color, go online.

Figure 7

Normal mode analysis of MMP1 using the ANM. Three-dimensional scatter plots of S142–S366 distance (represents interdomain dynamics), N171–T230 distance (represents the opening of the MMP1 catalytic pocket), and rms distance between the MMP1 catalytic site and the cleavage sites on three collagen chains for (A) collagen-bound activated (green) and (B) pro (greenish-yellow) MMP1. Two-dimensional projections in (A) and (B) of the scatter plots are in gray. Two-dimensional scatter plots of S142–S366 distance and N171–T230 distance for free (C) activated (green) and (D) pro (greenish-yellow) MMP1. To see this figure in color, go online.

Figure 8

Interdomain communications via collagen even without the linker. The catalytic pocket openings as measured by the distance between N171 and T230 (cyan line) are (A) 2.56 ± 0.52, (B) 2.56 ± 0.26, and (C) 2.55 ± 0.19 nm. The error bars represent the SDs of 60 measurements of the catalytic pocket opening obtained from 20 frames each for the three slowest normal modes. The red, blue, and green spheres on collagen represent the cleavage sites. The catalytic domain (cyan), the linker (brown), and the hemopexin (wheat) domains represent the residue ranges F100–Y260, G261–C278, and D279–C466, respectively. To see this figure in color, go online.