WEBVTT 00:00:00.000 --> 00:00:02.810 NARRATOR: The following content is provided under a Creative 00:00:02.810 --> 00:00:04.380 Commons license. 00:00:04.380 --> 00:00:06.670 Your support will help MIT Open Courseware 00:00:06.670 --> 00:00:11.010 continue to offer high quality educational resources for free. 00:00:11.010 --> 00:00:13.670 To make a donation or view additional materials 00:00:13.670 --> 00:00:17.600 from hundreds of MIT courses, visit MIT OpenCourseware 00:00:17.600 --> 00:00:18.800 at ocw.MIT.edu. 00:00:27.152 --> 00:00:30.000 PROFESSOR: So we have the five-step model. 00:00:30.000 --> 00:00:31.742 And what we're going to do-- 00:00:31.742 --> 00:00:33.200 this model was presented last time. 00:00:33.200 --> 00:00:35.150 And what we'll do is look at experiments 00:00:35.150 --> 00:00:38.990 that were designed to look at the denaturation, 00:00:38.990 --> 00:00:43.520 translocation, and degradation processes here. 00:00:43.520 --> 00:00:47.510 So one question is, can we separate denaturation 00:00:47.510 --> 00:00:50.660 from translocation in experiments 00:00:50.660 --> 00:00:53.330 to learn about the rates of each process. 00:00:53.330 --> 00:00:56.845 And also, how can we examine the role of ATP? 00:00:56.845 --> 00:00:58.720 Because that's a question key question here-- 00:00:58.720 --> 00:01:03.920 how is ATP hydrolysis by ClpXP allowing this macromolecular 00:01:03.920 --> 00:01:06.830 machine to work? 00:01:06.830 --> 00:01:13.310 And so we're going to begin with some experiments that 00:01:13.310 --> 00:01:14.960 involve a GFP substrate. 00:01:19.620 --> 00:01:31.670 So these are some studies of ClpXP activity with a substrate 00:01:31.670 --> 00:01:39.080 that has radio-label GFP ssrA. 00:01:39.080 --> 00:01:44.060 And so if we think about this substrate here, 00:01:44.060 --> 00:01:47.000 we have a radio-label-- 00:01:47.000 --> 00:01:49.490 bless you. 00:01:49.490 --> 00:01:52.100 We have green fluorescent protein. 00:01:52.100 --> 00:01:54.320 And this has a particular fold. 00:01:54.320 --> 00:01:56.990 So we have a folded substrate that's fluorescent. 00:02:02.110 --> 00:02:05.860 And here we have our tag that will 00:02:05.860 --> 00:02:11.140 direct the GFP to the ClpXP degradation machine. 00:02:11.140 --> 00:02:16.960 And so this substrate has been used 00:02:16.960 --> 00:02:25.910 to look at both degradation and unfolding. 00:02:25.910 --> 00:02:28.460 We'll get to the translocation issue 00:02:28.460 --> 00:02:32.270 in the second type of substrate we examine today. 00:02:32.270 --> 00:02:35.850 And so if we think about degradation, 00:02:35.850 --> 00:02:40.250 this is where the radio-label comes in. 00:02:40.250 --> 00:02:43.430 And if we think about unfolding, this 00:02:43.430 --> 00:02:45.140 is where the fluorescence comes in. 00:02:50.270 --> 00:02:52.360 And so what we're going to look is 00:02:52.360 --> 00:02:58.450 at degradation and denaturation assays using this substrate. 00:02:58.450 --> 00:03:03.190 And so just as a reminder, for anyone not familiar 00:03:03.190 --> 00:03:05.260 with green fluorescent protein, I 00:03:05.260 --> 00:03:08.380 might just show you the barrel-like structure here 00:03:08.380 --> 00:03:10.540 and the chromophores in the interior. 00:03:10.540 --> 00:03:12.520 And so in order for GFP to fluoresce, 00:03:12.520 --> 00:03:14.900 it needs to have its proper fold. 00:03:14.900 --> 00:03:19.660 And if it's denatured, that fluorescence emission is lost. 00:03:19.660 --> 00:03:22.550 So let's first look at a degradation assay. 00:03:22.550 --> 00:03:24.100 So this is experiment one. 00:03:38.290 --> 00:03:39.550 So what is the experiment? 00:03:39.550 --> 00:03:43.960 We have GFP here. 00:03:43.960 --> 00:03:46.180 And it has this ssrA tag. 00:03:49.420 --> 00:03:58.460 And we're going to incubate GFP with ATP and with ClpXP 00:03:58.460 --> 00:04:01.220 for some period of time. 00:04:01.220 --> 00:04:04.310 And then we're going to stop this reaction with a quench. 00:04:04.310 --> 00:04:05.510 And the quench will be acid. 00:04:12.710 --> 00:04:16.490 And so if we think about this protein and this degradation 00:04:16.490 --> 00:04:19.910 process by ClpXP, what are possible products? 00:04:19.910 --> 00:04:27.920 So maybe there's some GFP ssrA that hasn't yet been degraded, 00:04:27.920 --> 00:04:30.440 depending on your time point. 00:04:30.440 --> 00:04:35.440 And we can imagine some of these short polypeptide fragments 00:04:35.440 --> 00:04:38.540 of seven to eight amino acids. 00:04:38.540 --> 00:04:41.920 And so we have this radio-label. 00:04:41.920 --> 00:04:44.960 And what we want to do is track the radio-label. 00:04:44.960 --> 00:04:49.700 So here, we have radio-labeled protein. 00:04:54.870 --> 00:04:58.725 And here, we have radio-labeled peptides. 00:05:02.400 --> 00:05:05.460 And so if we want to quantify how much degradation occurred, 00:05:05.460 --> 00:05:09.210 somehow, we need to separate these. 00:05:09.210 --> 00:05:13.440 And so what is a way we can do that here-- something simple. 00:05:13.440 --> 00:05:15.090 And so what you want to think about 00:05:15.090 --> 00:05:19.810 is just relative solubility under acidic conditions. 00:05:19.810 --> 00:05:22.350 So if we have this large GFP that's 00:05:22.350 --> 00:05:25.920 folded, when that is treated with acid, 00:05:25.920 --> 00:05:28.830 GFP is going to precipitate. 00:05:28.830 --> 00:05:30.300 So this will be insoluble. 00:05:35.680 --> 00:05:38.460 And in contrast, these peptide fragments 00:05:38.460 --> 00:05:40.560 will be soluble, in most instances. 00:05:45.410 --> 00:05:47.570 So as a result, we can take advantage 00:05:47.570 --> 00:05:51.020 of this differing solubility, effectively 00:05:51.020 --> 00:05:52.145 to centrifuge the mixture. 00:05:59.260 --> 00:06:08.560 And we can measure the radioactivity in the pellet 00:06:08.560 --> 00:06:09.853 and in the supernatant. 00:06:15.050 --> 00:06:24.280 And then we can quantify degradation here. 00:06:28.550 --> 00:06:30.250 And so what are the results? 00:06:34.810 --> 00:06:42.610 So the result-- here, we can imagine a plot 00:06:42.610 --> 00:06:54.350 where we have percent of the substrate versus time. 00:06:57.840 --> 00:07:01.460 And these were conducted over the course of an hour. 00:07:05.240 --> 00:07:08.540 And what's observed here-- 00:07:08.540 --> 00:07:12.410 for instance, we have reactions where the substrate was 00:07:12.410 --> 00:07:17.240 incubated with ClpXP and ATP. 00:07:17.240 --> 00:07:19.700 So we see that over time, there's 00:07:19.700 --> 00:07:25.010 a decrease in the percent of GFP ssrA. 00:07:25.010 --> 00:07:28.850 And from these data, we can get some degradation rate. 00:07:28.850 --> 00:07:30.590 And we'll come back to that degradation 00:07:30.590 --> 00:07:32.840 rate in a little bit here. 00:07:32.840 --> 00:07:36.650 So what we see here is degradation. 00:07:41.050 --> 00:07:45.400 What happens if we add an inhibitor of the protease? 00:07:45.400 --> 00:07:47.230 So in the introductory lecture, we 00:07:47.230 --> 00:07:50.960 talked about a number of different types of inhibitors. 00:07:50.960 --> 00:07:53.600 And so that experiment was done. 00:07:53.600 --> 00:08:07.150 And so here, if we take ClpXP plus ATP plus inhibitor, 00:08:07.150 --> 00:08:09.160 what we see is no degradation. 00:08:19.230 --> 00:08:22.660 And the name of this inhibitor is DFP. 00:08:22.660 --> 00:08:25.880 And effectively, it covalently modifies the serine, 00:08:25.880 --> 00:08:29.130 in terms of what was used. 00:08:29.130 --> 00:08:33.289 So what do we conclude from these data? 00:08:33.289 --> 00:08:36.409 If the active site serine of ClpX 00:08:36.409 --> 00:08:39.470 is covalently modified with an inhibitor, which 00:08:39.470 --> 00:08:44.090 is diisopropyl fluorophosphate, we lose activity. 00:08:44.090 --> 00:08:48.080 So that serine is important. 00:08:48.080 --> 00:08:55.130 So what about unfolding or denaturation? 00:08:55.130 --> 00:08:56.990 How can we get at that? 00:08:56.990 --> 00:08:58.520 So that will be experiment two. 00:09:02.630 --> 00:09:11.950 And in terms of thinking about denaturation, 00:09:11.950 --> 00:09:13.450 rather than the radio-label, we're 00:09:13.450 --> 00:09:16.750 going to think about the GFP. 00:09:16.750 --> 00:09:22.770 And so imagine we have our folded GFP-- 00:09:22.770 --> 00:09:24.820 however we want to show that here-- 00:09:24.820 --> 00:09:28.930 that has this ssrA tag. 00:09:28.930 --> 00:09:33.447 So this is folded and fluorescent. 00:09:37.920 --> 00:09:47.410 So this gets denatured by ClpX of the machine 00:09:47.410 --> 00:09:51.220 to give us some unfolded polypeptide that 00:09:51.220 --> 00:09:54.190 has this ssrA tag-- 00:09:54.190 --> 00:09:58.510 unfolded and non-fluorescent. 00:10:04.180 --> 00:10:05.713 And then what happens? 00:10:05.713 --> 00:10:06.505 This gets degraded. 00:10:15.060 --> 00:10:16.590 And we get these fragments. 00:10:20.850 --> 00:10:23.280 And these fragments are also non-fluorescent. 00:10:28.060 --> 00:10:31.840 So effectively, s we can perform the exact same assay 00:10:31.840 --> 00:10:34.270 as we did an experiment one. 00:10:34.270 --> 00:10:37.090 But we'll look at fluorescence as a readout 00:10:37.090 --> 00:10:39.690 rather than quantifying radioactivity. 00:10:39.690 --> 00:10:44.800 STUDENT: So If you take ssrA on any protein, 00:10:44.800 --> 00:10:47.770 would ClpXP break it down? 00:10:50.410 --> 00:10:52.362 [INAUDIBLE] 00:10:52.362 --> 00:10:59.050 PROFESSOR: Yeah, so GFP probably isn't a native substrate of-- 00:10:59.050 --> 00:11:00.400 definitely not of E. coli ClpXP. 00:11:02.980 --> 00:11:05.650 What happens in a system that expresses GFP natively, 00:11:05.650 --> 00:11:07.150 I'm not sure. 00:11:07.150 --> 00:11:11.200 But yes, this has been a wonderful tool for experiments 00:11:11.200 --> 00:11:14.530 because many different protein substrates 00:11:14.530 --> 00:11:19.360 can be modified with this ssrA tag and directed to ClpXP. 00:11:19.360 --> 00:11:21.380 This is just one example. 00:11:21.380 --> 00:11:23.800 So I think broadly, we can think that there 00:11:23.800 --> 00:11:27.100 are many, many possibilities for what can be delivered. 00:11:27.100 --> 00:11:31.890 Are there certain proteins that ClpXP just can't deal with? 00:11:31.890 --> 00:11:34.330 That's a possibility. 00:11:34.330 --> 00:11:36.970 So the problem set for the upcoming week 00:11:36.970 --> 00:11:39.400 has a case where there's a disulfide bond, for instance, 00:11:39.400 --> 00:11:42.520 and asking what happens when we have 00:11:42.520 --> 00:11:44.230 some other types of structural features 00:11:44.230 --> 00:11:47.710 within a designed substrate. 00:11:47.710 --> 00:11:49.450 But for the purposes of this, yes, we 00:11:49.450 --> 00:11:52.990 can attach ssrA on to some protein 00:11:52.990 --> 00:11:55.720 that we can use to study the system 00:11:55.720 --> 00:11:57.460 and therefore do the experiments. 00:12:01.250 --> 00:12:03.670 And does that make sense, also, just 00:12:03.670 --> 00:12:07.480 thinking from the standpoint of what types of polypeptides 00:12:07.480 --> 00:12:10.720 might get directed to ClpXP in vivo? 00:12:10.720 --> 00:12:15.340 The ribosome could stall with many different types 00:12:15.340 --> 00:12:17.890 of proteins being synthesized there. 00:12:17.890 --> 00:12:20.980 So pretty versatile here. 00:12:20.980 --> 00:12:24.280 So we're going to perform the same assay. 00:12:24.280 --> 00:12:26.890 But we're going to measure fluorescence 00:12:26.890 --> 00:12:28.960 rather than radioactivity. 00:12:28.960 --> 00:12:30.580 And so what is the result? 00:12:35.930 --> 00:12:53.220 So here, we have fluorescence. 00:12:53.220 --> 00:12:56.325 And again, now, we have the percent of folded GFP-- 00:13:00.200 --> 00:13:02.660 100. 00:13:02.660 --> 00:13:06.030 And again, we can we can imagine this going down zero 00:13:06.030 --> 00:13:06.870 to 60 minutes. 00:13:13.420 --> 00:13:14.500 So here we have ClpXP. 00:13:20.310 --> 00:13:24.660 What happens if we have the inhibitor, for instance? 00:13:24.660 --> 00:13:36.920 What they found-- and I'll draw the inhibitor in a minute 00:13:36.920 --> 00:13:39.800 because I'm sure some of you are wondering. 00:13:39.800 --> 00:13:45.140 And here we have ClpX alone. 00:13:45.140 --> 00:13:52.370 So how do we interpret these data? 00:13:52.370 --> 00:13:55.160 So if we have the full machinery-- 00:13:55.160 --> 00:13:59.720 ClpXP and ATP-- we see a loss in fluorescence 00:13:59.720 --> 00:14:03.680 over time, which indicates a loss in folded GFP. 00:14:03.680 --> 00:14:06.620 So the substrate is being denatured. 00:14:06.620 --> 00:14:09.680 What about this case here when we only have ClpX present? 00:14:12.630 --> 00:14:13.950 And also, it won't have ATP. 00:14:17.110 --> 00:14:18.190 What's happening there? 00:14:27.185 --> 00:14:31.560 STUDENT: Without ClpP, there's no actual degradation 00:14:31.560 --> 00:14:33.030 that goes on. 00:14:33.030 --> 00:14:35.920 PROFESSOR: Do we need to see degradation in this assay? 00:14:35.920 --> 00:14:40.510 That's true, but what is this assay giving us a readout on? 00:14:40.510 --> 00:14:42.580 Just unfolding. 00:14:42.580 --> 00:14:44.790 So what do we learn from that? 00:14:44.790 --> 00:14:45.290 Rebecca? 00:14:45.290 --> 00:14:47.790 STUDENT: ClpX needs to be found to ClpP 00:14:47.790 --> 00:14:51.612 to be in the correct confirmation to unfold. 00:14:51.612 --> 00:14:52.900 PROFESSOR: Yes, yes. 00:14:52.900 --> 00:14:55.150 So this indicates that ClpX and ClpP 00:14:55.150 --> 00:14:59.590 need to be in complex in order to allow unfolding to occur. 00:14:59.590 --> 00:15:01.480 So thinking to the cellular environment, 00:15:01.480 --> 00:15:02.330 does not make sense? 00:15:06.838 --> 00:15:08.130 Yeah, I'm seeing nodding heads. 00:15:08.130 --> 00:15:09.750 Yes, right. 00:15:09.750 --> 00:15:12.450 So we wouldn't want just ClpX to be able to bind 00:15:12.450 --> 00:15:18.360 and unfold anything it comes into contact with there. 00:15:18.360 --> 00:15:20.370 And in terms of this inhibitor, we're 00:15:20.370 --> 00:15:22.740 seeing that it's not unfolding very well. 00:15:22.740 --> 00:15:24.720 So this inhibitor is for the protease. 00:15:24.720 --> 00:15:31.980 Just for that structure, effectively, 00:15:31.980 --> 00:15:35.380 what we have here-- 00:15:41.270 --> 00:15:51.270 you actually saw this in the lecture slides from last time. 00:15:51.270 --> 00:15:54.110 So this is DFP. 00:15:54.110 --> 00:15:58.170 And effectively, what it does is it 00:15:58.170 --> 00:16:05.190 will modify a serine side chain to give us this species here. 00:16:05.190 --> 00:16:07.260 And that will block proteolytic activity. 00:16:13.110 --> 00:16:15.120 So how did these data compare? 00:16:18.700 --> 00:16:22.860 How does the denaturation and degradation data compare? 00:16:22.860 --> 00:16:26.250 And so we can look at what was done. 00:16:26.250 --> 00:16:29.380 And effectively, what we want to ask 00:16:29.380 --> 00:16:34.600 is, how did the steady state kinetic data compare? 00:16:34.600 --> 00:16:37.390 And so steady state experiments were done, of course, 00:16:37.390 --> 00:16:39.250 with varying substrate. 00:16:39.250 --> 00:16:41.260 And the data were re-plotted. 00:16:41.260 --> 00:16:44.480 And so those data are shown here. 00:16:44.480 --> 00:16:47.590 And what we're looking at on the y-axis 00:16:47.590 --> 00:16:51.430 is the loss of substrates-- so GFP ssrA 00:16:51.430 --> 00:16:55.150 versus the concentration of substrate. 00:16:55.150 --> 00:16:57.580 And what we see is that in circles, 00:16:57.580 --> 00:16:59.650 we have the fluorescence data. 00:16:59.650 --> 00:17:03.920 And in triangles, we have the data from radioactivity. 00:17:06.849 --> 00:17:09.040 So what does this analysis tell us? 00:17:28.068 --> 00:17:30.110 STUDENT: The data set doesn't look that complete. 00:17:30.110 --> 00:17:32.420 But it looks like they're on about the same time scale. 00:17:32.420 --> 00:17:34.760 PROFESSOR: They look very similar. 00:17:34.760 --> 00:17:38.000 We're getting the same steady state kinetic parameters 00:17:38.000 --> 00:17:41.370 for both analyses here. 00:17:41.370 --> 00:17:43.280 And yes, it might be nice to have more data. 00:17:43.280 --> 00:17:45.560 But that's just not available. 00:17:45.560 --> 00:17:48.705 So all of these data can be fit to the same kcat and km. 00:17:51.620 --> 00:17:56.570 So what do these data tell us about a rate determining step, 00:17:56.570 --> 00:17:58.730 for instance? 00:17:58.730 --> 00:17:59.495 Not very much. 00:18:02.690 --> 00:18:07.190 And we also haven't yet thought about this issue 00:18:07.190 --> 00:18:08.660 of translocation. 00:18:08.660 --> 00:18:10.700 We're just seeing the unfolding step 00:18:10.700 --> 00:18:14.810 and seeing the degradation step in this assay here. 00:18:14.810 --> 00:18:16.570 So we need some more information. 00:18:23.240 --> 00:18:25.050 So if we think about this, we have 00:18:25.050 --> 00:18:43.470 denaturation versus translocation degradation. 00:18:46.640 --> 00:18:50.070 And so far, we've been able to look at this and this. 00:18:50.070 --> 00:18:52.140 And our intuition tells us degradation 00:18:52.140 --> 00:18:53.790 by the protease should be very fast. 00:18:56.310 --> 00:19:00.960 So can we learn something about translocation 00:19:00.960 --> 00:19:07.200 which we weren't able to see in these experiments here? 00:19:07.200 --> 00:19:09.630 And so that's what we want to focus on now 00:19:09.630 --> 00:19:20.420 because there was no readout on this step from experiments one 00:19:20.420 --> 00:19:24.560 and two here. 00:19:24.560 --> 00:19:27.980 So is it possible to separate denaturation and translocation 00:19:27.980 --> 00:19:30.401 with some strategically designed substrates? 00:19:35.111 --> 00:19:37.990 STUDENT: From this experiment, can't we 00:19:37.990 --> 00:19:40.480 deduce that translocation step is 00:19:40.480 --> 00:19:43.380 much slower than denaturation? 00:19:43.380 --> 00:19:44.210 PROFESSOR: Can we? 00:19:44.210 --> 00:19:44.710 How? 00:19:47.810 --> 00:19:50.860 Yeah, there's just no readout because this loss 00:19:50.860 --> 00:19:53.920 in fluorescence is just telling us that the protein is folded 00:19:53.920 --> 00:19:55.180 or unfolded. 00:19:55.180 --> 00:19:56.650 And the degradation is just telling 00:19:56.650 --> 00:19:58.990 us what happens in the protease chamber. 00:19:58.990 --> 00:20:00.970 So what happens from that point-- 00:20:00.970 --> 00:20:07.450 unfolding to degradation-- in between, we don't know here. 00:20:07.450 --> 00:20:13.540 So what we need is a new set of substrates 00:20:13.540 --> 00:20:18.580 that are going to let us get at this 00:20:18.580 --> 00:20:23.050 and allow us to separate denaturation from translocation 00:20:23.050 --> 00:20:25.060 experimentally. 00:20:25.060 --> 00:20:28.240 And so what was the idea for doing this? 00:20:28.240 --> 00:20:33.280 The idea was to take some protein that's been studied 00:20:33.280 --> 00:20:36.190 and take that protein and a series of mutants 00:20:36.190 --> 00:20:38.830 of that protein that have also been studied. 00:20:38.830 --> 00:20:42.670 And the key here is that the mutants of the protein 00:20:42.670 --> 00:20:44.770 have varying instabilities-- 00:20:44.770 --> 00:20:48.160 so varying instabilities of the fold. 00:20:48.160 --> 00:20:51.370 And so you can imagine that there 00:20:51.370 --> 00:20:53.320 have been many studies of protein folding 00:20:53.320 --> 00:20:56.440 out there asking the consequences of making 00:20:56.440 --> 00:21:00.280 point mutations in a given protein fold on stability 00:21:00.280 --> 00:21:01.150 there. 00:21:01.150 --> 00:21:04.540 And so that's exactly what was done. 00:21:04.540 --> 00:21:22.750 So what we need is a new set of substrates to probe effectively 00:21:22.750 --> 00:21:40.140 denaturation and translocation in more detail here. 00:21:40.140 --> 00:21:46.260 And the key question is, is it possible 00:21:46.260 --> 00:21:59.120 to separate denaturation from translocation? 00:22:04.740 --> 00:22:20.140 And so what was done is to take an immunoglobulin-like domain 00:22:20.140 --> 00:22:22.810 from a protein found in striated muscle that 00:22:22.810 --> 00:22:25.990 has been the subject of many studies 00:22:25.990 --> 00:22:30.195 and mutants of this protein and to employ them in assays. 00:22:36.120 --> 00:22:49.230 So we're going to take a protein plus variants 00:22:49.230 --> 00:23:09.130 with varying stabilities and perform this assay 00:23:09.130 --> 00:23:10.720 and compare the data. 00:23:10.720 --> 00:23:17.920 And so here is the protein that was used as a model substrate. 00:23:17.920 --> 00:23:21.880 So shown here, this is the titin I27 domain 00:23:21.880 --> 00:23:25.060 that has an ssrA tag attached. 00:23:25.060 --> 00:23:28.720 OK so if we take a look at this protein that 00:23:28.720 --> 00:23:35.500 has a beta sandwich fold, we see that there's a disulfide bond. 00:23:35.500 --> 00:23:37.510 There's a single tryptophan residue. 00:23:37.510 --> 00:23:39.970 And this is helpful because tryptophan residues 00:23:39.970 --> 00:23:41.610 have intrinsic fluorescence that's 00:23:41.610 --> 00:23:44.050 sensitive to the environment. 00:23:44.050 --> 00:23:46.720 And we see it's buried in the inside here. 00:23:46.720 --> 00:23:49.480 So in a hydrophobic versus hydrophobic environment, 00:23:49.480 --> 00:23:51.220 the fluorescence will differ. 00:23:51.220 --> 00:23:56.680 And so we can use that as a readout of unfolding here. 00:23:56.680 --> 00:24:00.790 And this is just an example of data from a prior study 00:24:00.790 --> 00:24:05.380 where this protein and various mutants 00:24:05.380 --> 00:24:12.340 of the protein like here, valine 11P Y9P 00:24:12.340 --> 00:24:16.100 were studied for stability of the fold. 00:24:16.100 --> 00:24:18.190 So guanidinium, we learned that's the denaturant 00:24:18.190 --> 00:24:20.230 in the folding section. 00:24:20.230 --> 00:24:25.230 So these various point mutations have different stabilities. 00:24:25.230 --> 00:24:28.390 And we can see that in these denaturation curves here. 00:24:31.100 --> 00:24:35.050 So what was done in their experiments 00:24:35.050 --> 00:24:38.020 were very similar to what was done before. 00:24:38.020 --> 00:24:45.340 So we take this titin radio-labeled-- 00:24:45.340 --> 00:24:45.940 bless you. 00:24:45.940 --> 00:24:57.350 So this is experiment three with the ssrA tag. 00:25:00.230 --> 00:25:08.840 Incubate with ClpXP with ATP and asks what happened. 00:25:08.840 --> 00:25:11.240 And in terms of these substrates, 00:25:11.240 --> 00:25:23.300 we have the wild-type, we have the mutants, as shown up here. 00:25:23.300 --> 00:25:26.750 And we have CM, you'll see in the data, 00:25:26.750 --> 00:25:27.965 which is chemically modified. 00:25:35.790 --> 00:25:38.600 And these chemically modified variants 00:25:38.600 --> 00:25:40.970 are completely denatured-- we can consider them. 00:25:49.480 --> 00:25:52.660 And so effectively, what was done here 00:25:52.660 --> 00:26:00.970 with cysteine modification, with iodoacetamide. 00:26:04.760 --> 00:26:09.500 So we saw that in discussions-- introductory discussions-- 00:26:09.500 --> 00:26:12.290 about unnatural amino acid incorporation. 00:26:12.290 --> 00:26:16.140 So the disulfide bond is completely disrupted here. 00:26:16.140 --> 00:26:19.170 The disulfide can be reduced, the cysteines modified, 00:26:19.170 --> 00:26:22.550 and we get an unfolded version here for that. 00:26:26.990 --> 00:26:32.600 And here what do we find? 00:26:32.600 --> 00:26:36.440 So there's a number of different point mutants 00:26:36.440 --> 00:26:38.820 that are listed here. 00:26:38.820 --> 00:26:40.790 And we're just going to look at a few, 00:26:40.790 --> 00:26:42.610 in terms of what they found. 00:26:45.310 --> 00:26:49.180 So in terms of degradation assay, which 00:26:49.180 --> 00:27:11.010 is how they did this readout, we're 00:27:11.010 --> 00:27:15.960 going to have the percent titin remaining. 00:27:22.860 --> 00:27:28.860 So again, using radioactivity in the supernatant or pellet 00:27:28.860 --> 00:27:29.640 versus time-- 00:27:45.380 --> 00:27:46.220 what did they find? 00:27:46.220 --> 00:27:52.070 So if we take a look at a selection of the data-- 00:27:52.070 --> 00:27:54.230 just put three examples-- 00:27:57.600 --> 00:27:58.755 here, what do we have? 00:28:02.720 --> 00:28:03.950 Here, we have wild-type. 00:28:08.710 --> 00:28:10.720 Here, we have one of the mutants, B13P. 00:28:13.330 --> 00:28:16.480 And here, we have chemically modified wild-type. 00:28:23.350 --> 00:28:26.050 So what do these data tell us? 00:28:46.010 --> 00:28:48.006 STUDENT: Degradation is faster. 00:28:48.006 --> 00:28:49.004 It's [INAUDIBLE] 00:28:49.004 --> 00:28:50.420 PROFESSOR: Yeah. 00:28:50.420 --> 00:28:52.460 That's one thing we see here. 00:28:52.460 --> 00:28:55.850 So this chemically modified protein is denatured. 00:28:55.850 --> 00:28:59.540 And we see that the denatured protein is easier 00:28:59.540 --> 00:29:04.370 to degrade by ClpXP than the native protein. 00:29:04.370 --> 00:29:07.580 We also see that the mutant is more rapidly 00:29:07.580 --> 00:29:09.030 degraded than the wild-type. 00:29:09.030 --> 00:29:13.430 So ClpXP is having an easier time with this one here too. 00:29:13.430 --> 00:29:15.110 So there's an apparent correlation 00:29:15.110 --> 00:29:18.590 here between the ease of unfolding 00:29:18.590 --> 00:29:20.690 and the ease of degradation. 00:29:20.690 --> 00:29:23.480 A protein that's already unfolded or is relatively 00:29:23.480 --> 00:29:26.480 easy to fold is degraded more rapidly 00:29:26.480 --> 00:29:28.310 than the wild-type protein that has 00:29:28.310 --> 00:29:31.970 this beta sandwich fold here. 00:29:31.970 --> 00:29:37.790 If we think about the processes happening in each of these 00:29:37.790 --> 00:29:40.340 and we think back to that five-step model, 00:29:40.340 --> 00:29:41.790 what's happening? 00:29:41.790 --> 00:29:50.270 So here, we have denaturation plus translocation 00:29:50.270 --> 00:29:53.480 plus degradation. 00:29:53.480 --> 00:29:57.470 And likewise, here, we have these three parameters as well. 00:30:04.350 --> 00:30:07.830 And in this case, we don't have denaturation. 00:30:07.830 --> 00:30:14.250 We just have the translocation and the degradation here. 00:30:23.770 --> 00:30:26.310 STUDENT: Why are the rates linear here? 00:30:26.310 --> 00:30:29.640 And it was not linear in the previous one. 00:30:29.640 --> 00:30:31.230 PROFESSOR: Just imagine this is-- 00:30:31.230 --> 00:30:34.020 well, one is a completely different substrate. 00:30:34.020 --> 00:30:36.840 The time frame, I haven't given here. 00:30:36.840 --> 00:30:38.460 Don't worry about that. 00:30:38.460 --> 00:30:39.980 We're just looking at that one part. 00:30:44.850 --> 00:30:49.350 So here's the actual data from the report. 00:30:49.350 --> 00:30:54.900 And now, what we want to do is, using this whole family 00:30:54.900 --> 00:30:56.280 of substrates-- 00:30:56.280 --> 00:31:00.510 so the native I27 domain, the various point mutants, 00:31:00.510 --> 00:31:02.640 and these chemically modified forms, 00:31:02.640 --> 00:31:05.040 we want to look at the details of the steady state 00:31:05.040 --> 00:31:07.830 kinetic analysis. 00:31:07.830 --> 00:31:12.300 And we also want to look at what's going on with the ATPs. 00:31:12.300 --> 00:31:15.060 So what is the rate of ATP hydrolysis. 00:31:15.060 --> 00:31:18.690 And how many ATPs are hydrolyzed? 00:31:18.690 --> 00:31:21.570 We know nothing about that yet, in terms of the data that's 00:31:21.570 --> 00:31:24.690 been presented so far. 00:31:24.690 --> 00:31:28.440 So what we're going to do is take a look at this dataset 00:31:28.440 --> 00:31:31.710 and see what we learn here. 00:31:31.710 --> 00:31:33.580 So there's quite a bit of data in here. 00:31:33.580 --> 00:31:37.140 But we're just going to systematically work through. 00:31:37.140 --> 00:31:40.110 So what do we see? 00:31:40.110 --> 00:31:43.110 Here, we have all of the different I27 00:31:43.110 --> 00:31:46.110 domain-based substrates they used. 00:31:46.110 --> 00:31:50.550 And the table is divided basically in terms of 00:31:50.550 --> 00:31:53.760 whether or not the protein was chemically modified. 00:31:53.760 --> 00:31:56.040 So on top, we have wild type. 00:31:56.040 --> 00:31:57.880 And then we have these four-- 00:31:57.880 --> 00:31:59.990 or sorry, five-- point mutants. 00:31:59.990 --> 00:32:01.710 And in this bottom half of the table, 00:32:01.710 --> 00:32:04.260 we have the chemically modified wild type 00:32:04.260 --> 00:32:07.710 and the chemically modified point mutants. 00:32:07.710 --> 00:32:11.580 So these begin with a fold, and depending on the mutation here, 00:32:11.580 --> 00:32:15.240 there's differing stability of that fold. 00:32:15.240 --> 00:32:17.160 And here, we have unfolded variants 00:32:17.160 --> 00:32:20.370 because the disulfide was disrupted. 00:32:20.370 --> 00:32:21.570 So what are we looking at? 00:32:21.570 --> 00:32:27.900 We have degradation, we have km, we have denaturation, 00:32:27.900 --> 00:32:30.600 and then we have the ATP S rate, and the number 00:32:30.600 --> 00:32:36.130 of ATPs per I27 domain degraded here. 00:32:36.130 --> 00:32:41.110 So the question is, what do we learn from each column of data? 00:32:41.110 --> 00:32:47.950 So if we take a look at these degradation rates here, 00:32:47.950 --> 00:32:48.840 what do we see? 00:32:54.020 --> 00:32:57.260 So what happens amongst the proteins that 00:32:57.260 --> 00:32:58.470 are not chemically modified? 00:33:05.280 --> 00:33:07.170 And don't try to over-analyze it, 00:33:07.170 --> 00:33:12.620 just look for what are the obvious differences here. 00:33:21.078 --> 00:33:21.995 So what's the slowest? 00:33:25.510 --> 00:33:26.740 Wild-type, right? 00:33:26.740 --> 00:33:29.770 Similar to what we saw here, and that makes sense 00:33:29.770 --> 00:33:33.340 because wild-type has the most stable fold, just 00:33:33.340 --> 00:33:35.240 based on what we saw here. 00:33:35.240 --> 00:33:38.290 And then what do we see for the mutants? 00:33:38.290 --> 00:33:41.040 There's variability. 00:33:41.040 --> 00:33:44.170 And all of these values are greater. 00:33:44.170 --> 00:33:47.440 How do they compare to chemically modified variants? 00:33:47.440 --> 00:33:48.760 And what do we see here? 00:33:52.110 --> 00:33:54.380 These are the fastest. 00:33:54.380 --> 00:33:57.770 And they're all pretty similar. 00:33:57.770 --> 00:34:01.130 So these data agree with what we drew up here. 00:34:05.180 --> 00:34:06.425 What about the km values? 00:34:12.920 --> 00:34:15.590 So are these all similar or different? 00:34:19.270 --> 00:34:21.066 All pretty similar, yeah. 00:34:21.066 --> 00:34:22.274 And why does that make sense? 00:34:25.199 --> 00:34:27.179 So that indicates that ClpX binds 00:34:27.179 --> 00:34:30.249 all of these substrates in a similar way. 00:34:36.830 --> 00:34:39.448 They all have the ssrA tag there. 00:34:43.810 --> 00:34:45.760 So we can't attribute any changes 00:34:45.760 --> 00:34:49.989 we're seeing in rate to this km value here. 00:34:49.989 --> 00:34:51.714 What about these denaturation rates? 00:34:54.840 --> 00:34:59.070 So we don't have any values for the chemically modified forms 00:34:59.070 --> 00:35:01.470 because they're already denatured. 00:35:01.470 --> 00:35:02.410 What do we see? 00:35:02.410 --> 00:35:05.500 We see the wild-type is more difficult to denature-- 00:35:05.500 --> 00:35:07.410 so the slower rate-- 00:35:07.410 --> 00:35:10.292 than these point mutations here. 00:35:10.292 --> 00:35:12.750 And you could imagine if you were the researcher going back 00:35:12.750 --> 00:35:14.340 and comparing these data to what's 00:35:14.340 --> 00:35:17.760 known about the relative stabilities of each fold 00:35:17.760 --> 00:35:20.340 from other data in the literature 00:35:20.340 --> 00:35:24.300 from studies like that guanidinium denaturation 00:35:24.300 --> 00:35:27.960 on the prior slide here. 00:35:27.960 --> 00:35:31.740 So what about the data in these columns? 00:35:31.740 --> 00:35:32.420 What do we see? 00:35:39.860 --> 00:35:42.260 So here, we're looking at ATPase activity. 00:35:54.460 --> 00:35:57.550 STUDENT: In that case, it's slower 00:35:57.550 --> 00:36:02.072 and less efficient for wild-type than chemically modified. 00:36:02.072 --> 00:36:03.670 PROFESSOR: Yes. 00:36:03.670 --> 00:36:04.210 Yes. 00:36:04.210 --> 00:36:06.940 That's certainly the case. 00:36:06.940 --> 00:36:11.380 So, first, if we look at wild-type, and even 00:36:11.380 --> 00:36:13.570 for that matter, these single point variants, 00:36:13.570 --> 00:36:16.750 versus these chemically modified forms, 00:36:16.750 --> 00:36:24.510 we see that the wild-type has a value of about 150 per minute. 00:36:24.510 --> 00:36:26.310 And these are slightly higher. 00:36:26.310 --> 00:36:30.600 We see these are on the order of about 600 per minute. 00:36:30.600 --> 00:36:33.360 So in a way, these fall into two groups-- 00:36:33.360 --> 00:36:36.370 the chemically modified forms defined one group. 00:36:36.370 --> 00:36:38.070 And this wild-type and single point 00:36:38.070 --> 00:36:42.510 mutants define another group here. 00:36:42.510 --> 00:36:47.520 And the wild-type has the slowest ATPase right here. 00:36:47.520 --> 00:36:50.790 And then in terms of efficiency, as you mentioned-- 00:36:50.790 --> 00:36:55.260 maybe that's in terms of the number of ATPs degraded-- 00:36:55.260 --> 00:36:56.590 what do we see here? 00:36:56.590 --> 00:37:01.500 What is incredibly striking about these data? 00:37:01.500 --> 00:37:07.140 We're seeing about 600 ATPs for I27 domain degraded for this 00:37:07.140 --> 00:37:10.400 wild-type that's a huge number of ATPs-- 00:37:13.140 --> 00:37:17.010 so 600. 00:37:17.010 --> 00:37:20.610 What do we see for these denatured variants? 00:37:20.610 --> 00:37:25.680 They're all around 115 ATPs per substrate consumed here. 00:37:30.130 --> 00:37:33.650 So many, many ATPs are consumed here. 00:37:33.650 --> 00:37:37.820 Many ATPs are required to denature that native substrate. 00:37:37.820 --> 00:37:41.870 And it looks like many ATPs are required for translocation 00:37:41.870 --> 00:37:43.040 here. 00:37:43.040 --> 00:37:45.440 And if the substrate is less stable, what we see 00:37:45.440 --> 00:37:48.970 is that fewer ATPs are consumed. 00:37:48.970 --> 00:37:51.640 So these are all filled in within your notes. 00:37:51.640 --> 00:37:53.680 And there's some additional details here. 00:37:56.320 --> 00:38:00.550 So these data indicate that the easier the protein unfolds, 00:38:00.550 --> 00:38:02.740 the faster it's degraded. 00:38:02.740 --> 00:38:05.650 And just to reiterate, these denatured titins, 00:38:05.650 --> 00:38:08.230 we can think about ATP consumption 00:38:08.230 --> 00:38:10.900 as being indicative of that translocation event 00:38:10.900 --> 00:38:13.030 because they're already denatured. 00:38:13.030 --> 00:38:16.600 And for these native titin, the rate of ATP consumption 00:38:16.600 --> 00:38:19.180 is indicative of both the unfolding or denaturation 00:38:19.180 --> 00:38:22.980 process and the translocation process here for that. 00:38:26.660 --> 00:38:29.100 Here is just another way of plotting the data 00:38:29.100 --> 00:38:33.450 in the table, where they're just highlighting 00:38:33.450 --> 00:38:38.520 ATP hydrolysis and then the different types of substrates 00:38:38.520 --> 00:38:39.780 here. 00:38:39.780 --> 00:38:42.210 So we see the rate's highest for denatured 00:38:42.210 --> 00:38:44.130 and that it decreases with increasing 00:38:44.130 --> 00:38:49.890 stability of the substrate to degradation by ClpXP. 00:38:49.890 --> 00:38:52.740 Another interesting thing they found in these studies 00:38:52.740 --> 00:39:01.030 is that the ATP is consumed very linearly with time. 00:39:26.530 --> 00:39:37.860 So if we look at ATP consumed versus the average denaturation 00:39:37.860 --> 00:39:38.360 time-- 00:39:46.850 --> 00:39:56.150 here, wild-type, and down in this region, the mutants. 00:39:59.900 --> 00:40:02.360 So we have a linear relationship. 00:40:02.360 --> 00:40:06.980 And what came out of this is about 144 ATPs 00:40:06.980 --> 00:40:20.690 consumed per minute of unfolding from these experiments here. 00:40:27.320 --> 00:40:30.730 So what does this tell us about how ClpXP works-- 00:40:30.730 --> 00:40:32.450 how it works here? 00:40:37.400 --> 00:40:42.350 So basically, this machine has been 00:40:42.350 --> 00:40:46.720 described as having a relentless try and try again mechanism 00:40:46.720 --> 00:40:48.830 here. 00:40:48.830 --> 00:40:53.240 And it's effectively explained in this cartoon. 00:40:53.240 --> 00:40:58.200 So ClpP is omitted, but imagine it's there. 00:40:58.200 --> 00:41:00.950 So what's happening? 00:41:00.950 --> 00:41:04.340 We have some folded protein that's been condemned 00:41:04.340 --> 00:41:07.670 and has the ssrA tag attached. 00:41:07.670 --> 00:41:10.650 And so ClpXP needs to deal with it. 00:41:10.650 --> 00:41:13.200 There's the tag-mediated substrate binding. 00:41:13.200 --> 00:41:17.150 So the substrate binds, there can be ATP hydrolysis. 00:41:17.150 --> 00:41:23.070 And that results in ClpX trying to unfold the protein. 00:41:23.070 --> 00:41:27.140 But frequently, the substrate can get released. 00:41:27.140 --> 00:41:30.020 And this cycle of binding and pulling 00:41:30.020 --> 00:41:32.360 can happen many, many times. 00:41:32.360 --> 00:41:36.380 And that consumes a lot of ATPs here. 00:41:36.380 --> 00:41:38.630 And then at some point, there's going 00:41:38.630 --> 00:41:41.660 to be a successful unfolding event, which 00:41:41.660 --> 00:41:45.920 results in the polypeptide being translocated and entering 00:41:45.920 --> 00:41:49.340 the degradation chamber. 00:41:49.340 --> 00:41:52.520 So when thinking about a hard to denature substrate, 00:41:52.520 --> 00:41:55.640 you want to think about this substrate binding ClpX 00:41:55.640 --> 00:41:57.140 many times. 00:41:57.140 --> 00:41:59.390 There might be multiple instances of binding 00:41:59.390 --> 00:42:02.270 and release before it's successfully denatured 00:42:02.270 --> 00:42:04.220 and before translocation occurs. 00:42:04.220 --> 00:42:06.806 And so that uses a lot of ATPs. 00:42:06.806 --> 00:42:08.710 STUDENT: Does it all confine the substrate 00:42:08.710 --> 00:42:11.500 to many different places or just in one spot? 00:42:11.500 --> 00:42:16.340 PROFESSOR: So the ssr tag is what's 00:42:16.340 --> 00:42:18.950 going to allow it to bind to the pore. 00:42:18.950 --> 00:42:20.450 And recall, for instance, there can 00:42:20.450 --> 00:42:25.460 be the adapter protein SspB to help ssrA tag proteins make 00:42:25.460 --> 00:42:28.340 their way to the pore. 00:42:28.340 --> 00:42:33.260 So think of it less as some undesirable protein-protein 00:42:33.260 --> 00:42:35.750 interaction than a failed attempt 00:42:35.750 --> 00:42:41.120 at unfolding by this ATPase here. 00:42:41.120 --> 00:42:44.060 So why might ClpX want to do this? 00:42:52.690 --> 00:42:54.050 When we think about the cell-- 00:42:54.050 --> 00:42:55.120 just some possibilities? 00:42:55.120 --> 00:42:59.033 STUDENT: It would make sense, I guess, the more unstable 00:42:59.033 --> 00:43:00.950 the protein is, the easier it is to degrade it 00:43:00.950 --> 00:43:02.885 because proteins that are more unstable 00:43:02.885 --> 00:43:04.910 are already partially unfolded and are probably 00:43:04.910 --> 00:43:06.872 ones that need to be degraded. 00:43:06.872 --> 00:43:10.160 PROFESSOR: Yeah, so that's one way to think about this. 00:43:10.160 --> 00:43:12.110 And then maybe another way to phrase 00:43:12.110 --> 00:43:16.690 that is perhaps this helps to avoid jamming the protease. 00:43:16.690 --> 00:43:18.440 If there's things that need to be degraded 00:43:18.440 --> 00:43:21.290 versus other things, if you have something that's 00:43:21.290 --> 00:43:23.600 very difficult to degrade, you don't 00:43:23.600 --> 00:43:26.090 want that to block the protease such that something 00:43:26.090 --> 00:43:28.340 unfolded can't be dealt with. 00:43:28.340 --> 00:43:30.140 Also, just dealing with a mixture, 00:43:30.140 --> 00:43:32.690 that maybe ClpXP likes to get rid 00:43:32.690 --> 00:43:39.260 of the substrates that are easiest to degrade first. 00:43:39.260 --> 00:43:45.050 So is it energetically wasteful there-- 00:43:45.050 --> 00:43:46.710 just to think about. 00:43:46.710 --> 00:43:48.710 On one hand, it might seem like it. 00:43:48.710 --> 00:43:52.040 So many ATPs-- just think back to the TCA cycle, for instance, 00:43:52.040 --> 00:43:54.470 and how many ATPs you get from one cycle 00:43:54.470 --> 00:43:58.220 there versus 600 ATPs being consumed here 00:43:58.220 --> 00:44:01.700 for that wild-type titin domain. 00:44:01.700 --> 00:44:05.450 But this makes sense because in the cell, 00:44:05.450 --> 00:44:08.600 it does have to deal with many different types of substrates. 00:44:08.600 --> 00:44:11.060 And these substrates can have varying structure 00:44:11.060 --> 00:44:14.480 and varying stabilities. 00:44:14.480 --> 00:44:18.320 So how does ClpX actually work? 00:44:18.320 --> 00:44:23.450 What's going on with this ATP hydrolysis? 00:44:23.450 --> 00:44:26.750 How are denaturation and translocation coupled? 00:44:26.750 --> 00:44:31.160 And how do we even think about this translocation process? 00:44:31.160 --> 00:44:32.810 Effectively, we saw the cartoons, 00:44:32.810 --> 00:44:35.510 where it looked like ClpX was somehow 00:44:35.510 --> 00:44:38.490 pulling on this polypeptide. 00:44:38.490 --> 00:44:45.860 And so we'll close with some discussion about that, 00:44:45.860 --> 00:44:50.460 which we'll continue on Monday. 00:44:50.460 --> 00:45:00.560 So effectively, we have our general paradigm 00:45:00.560 --> 00:45:12.510 of somehow having ATP hydrolysis leading 00:45:12.510 --> 00:45:19.610 to conformational change that provides some mechanical work. 00:45:24.530 --> 00:45:36.400 And so here in this system, conformational change in ClpX 00:45:36.400 --> 00:45:40.750 will drive unfolding and translocation. 00:45:49.270 --> 00:45:51.280 And of course, the big question is how? 00:45:54.450 --> 00:45:59.590 And so a key observation that's not intuitive with this system 00:45:59.590 --> 00:46:02.020 and that we'll build upon in the first 10 minutes or so 00:46:02.020 --> 00:46:08.120 of Monday is the fact that ClpX is a homohexamer. 00:46:08.120 --> 00:46:10.870 We saw that when we went over the structure. 00:46:10.870 --> 00:46:14.650 But this hexamer has some inherent asymmetry to it, 00:46:14.650 --> 00:46:19.690 despite the fact that each subunit is the same. 00:46:19.690 --> 00:46:30.480 So a key observation here-- 00:46:30.480 --> 00:46:33.360 ClpX is homohexamer. 00:46:38.140 --> 00:46:43.610 But it has inherent asymmetry. 00:46:50.530 --> 00:46:59.760 And this asymmetry arises from nucleotide ATP binding. 00:47:08.070 --> 00:47:11.760 And the observation from a variety of studies 00:47:11.760 --> 00:47:17.750 is that ATP binds to some of the ClpX subunits but not others. 00:47:17.750 --> 00:47:24.900 OK And also it can bind to different subunits 00:47:24.900 --> 00:47:27.825 with different affinities, just as another detail. 00:47:32.400 --> 00:47:35.790 And what we'll see is that this is also dynamic-- 00:47:35.790 --> 00:47:44.470 so just some subunits. 00:47:48.080 --> 00:47:51.980 So although we think about this as a homohexamer in terms 00:47:51.980 --> 00:47:56.240 of the ATP loading at different points, 00:47:56.240 --> 00:48:00.200 we don't have six ATPs bound. 00:48:00.200 --> 00:48:02.330 And where we'll begin on Monday is 00:48:02.330 --> 00:48:07.190 looking at individual ClpX subunits 00:48:07.190 --> 00:48:12.260 and then how the ClpX subunits work together 00:48:12.260 --> 00:48:17.810 and lessons learned from studies there. 00:48:17.810 --> 00:48:19.970 So effectively, this asymmetry is 00:48:19.970 --> 00:48:22.190 thought to be quite important, in terms 00:48:22.190 --> 00:48:25.460 of how ATP hydrolysis is allowing the movements 00:48:25.460 --> 00:48:27.910 and activity of the ATPase.