WEBVTT 00:00:00.500 --> 00:00:03.270 The following content is provided under a Creative 00:00:03.270 --> 00:00:04.630 Commons license. 00:00:04.630 --> 00:00:07.140 Your support will help MIT OpenCourseWare 00:00:07.140 --> 00:00:11.470 continue to offer high quality educational resources for free. 00:00:11.470 --> 00:00:14.100 To make a donation, or view additional materials 00:00:14.100 --> 00:00:16.980 from hundreds of MIT courses, visit MIT 00:00:16.980 --> 00:00:19.000 open courseware at ocw.mit.edu. 00:00:24.447 --> 00:00:26.280 JOANNE STUBBE: Recitation 2 and recitation 3 00:00:26.280 --> 00:00:27.420 are on the same paper. 00:00:27.420 --> 00:00:30.780 You only have to read one paper that Liz has been discussing 00:00:30.780 --> 00:00:34.740 in class, the Rodnina paper. 00:00:34.740 --> 00:00:39.860 The paper was published in 1999, OK? 00:00:39.860 --> 00:00:43.920 And it's still, I would say, a seminal paper. 00:00:43.920 --> 00:00:47.460 And what they propose or what you read about their model 00:00:47.460 --> 00:00:52.740 is still the working hypothesis in the field. 00:00:52.740 --> 00:00:57.660 But if you go and Google the ribosome in elongation, 00:00:57.660 --> 00:01:01.020 you will find out that in the last 10 years 00:01:01.020 --> 00:01:03.780 there are hundreds of papers now taking 00:01:03.780 --> 00:01:09.570 pot shots at this model using modern technological 00:01:09.570 --> 00:01:14.700 mechanisms, like single-molecule spectroscopy, Cryo-EM. 00:01:14.700 --> 00:01:18.930 So they're flushing things out, but so still the basic model 00:01:18.930 --> 00:01:19.480 holds. 00:01:19.480 --> 00:01:22.627 So we continue to go through this because, in my opinion, 00:01:22.627 --> 00:01:24.960 all the machines that you're going to be talking about-- 00:01:24.960 --> 00:01:27.460 and this is part of the course-- 00:01:27.460 --> 00:01:31.820 have complex behavior like this with numerous substrates 00:01:31.820 --> 00:01:33.460 and many, many steps. 00:01:33.460 --> 00:01:37.290 And so hopefully one thing you got out of this paper 00:01:37.290 --> 00:01:40.680 is that kinetics are important. 00:01:40.680 --> 00:01:44.570 OK, so today what I want to do, I'm going to ask you questions. 00:01:44.570 --> 00:01:46.320 I'm going to put some things on the board. 00:01:46.320 --> 00:01:48.720 We get you at talking points. 00:01:48.720 --> 00:01:50.310 I'm going to ask you some questions. 00:01:50.310 --> 00:01:53.250 And then the discussion will continue 00:01:53.250 --> 00:01:58.875 into the next recitation on the same exact same topic. 00:01:58.875 --> 00:02:00.660 But kinetics are important. 00:02:00.660 --> 00:02:03.420 But to do kinetics, what do you have to have? 00:02:03.420 --> 00:02:06.400 What's required to do kinetics if you look at this model? 00:02:06.400 --> 00:02:10.240 So this is the model out of your paper. 00:02:10.240 --> 00:02:12.240 If you want to do kinetics, what do you need? 00:02:17.820 --> 00:02:20.600 Not only that, you have to speak loud because I'm deaf anyhow. 00:02:20.600 --> 00:02:22.657 What do you need? 00:02:22.657 --> 00:02:23.990 AUDIENCE: To do kinetic studies? 00:02:23.990 --> 00:02:24.675 JOANNE STUBBE: Yeah, to do kinetic studies. 00:02:24.675 --> 00:02:26.425 AUDIENCE: [INAUDIBLE] a detection method 00:02:26.425 --> 00:02:26.920 in very controlled conditions. 00:02:26.920 --> 00:02:29.409 JOANNE STUBBE: Yeah, so you have to have an assay, OK? 00:02:29.409 --> 00:02:30.950 And you'll see that everything you're 00:02:30.950 --> 00:02:32.810 doing over the course of the semester 00:02:32.810 --> 00:02:35.060 requires development of an assay. 00:02:35.060 --> 00:02:38.810 And I would say the more complex you get the more complex 00:02:38.810 --> 00:02:39.600 these machines. 00:02:39.600 --> 00:02:41.225 And that's what people are studying now 00:02:41.225 --> 00:02:46.920 as opposed to if you looked at it Liz's lecture on tRNA 00:02:46.920 --> 00:02:49.520 synthetases, you saw a simple reaction, OK? 00:02:49.520 --> 00:02:51.990 That assay was developed decades ago. 00:02:51.990 --> 00:02:55.290 But when you get into these more complicated machines, 00:02:55.290 --> 00:02:59.227 you have to be really pretty creative to develop an assay. 00:02:59.227 --> 00:03:00.560 And you need to have substrates. 00:03:00.560 --> 00:03:02.510 You need to get them from somewhere. 00:03:02.510 --> 00:03:04.770 And then you need to do kinetics. 00:03:04.770 --> 00:03:07.730 And so today, what I want to do is 00:03:07.730 --> 00:03:12.680 go through the kinetics part of this, asking you questions 00:03:12.680 --> 00:03:14.060 as we go along. 00:03:14.060 --> 00:03:16.310 And I'm going to start. 00:03:16.310 --> 00:03:18.870 So kinetics, in my opinion, is a key tool. 00:03:23.356 --> 00:03:29.550 So we're using kinetics as a tool to study machines. 00:03:29.550 --> 00:03:31.680 And the machine we're studying is-- 00:03:31.680 --> 00:03:34.660 and have been studying is, is the ribosome. 00:03:34.660 --> 00:03:39.530 OK, so how many of you have had an introductory last lab 00:03:39.530 --> 00:03:42.590 course where you did kinetics? 00:03:42.590 --> 00:03:44.100 Only one? 00:03:44.100 --> 00:03:45.160 Two? 00:03:45.160 --> 00:03:47.390 OK, because steady state kinetics 00:03:47.390 --> 00:03:49.760 is where you start for everything, OK? 00:03:49.760 --> 00:03:51.230 And I find when I-- 00:03:51.230 --> 00:03:52.820 I've been teaching for many years-- 00:03:52.820 --> 00:03:54.819 that there are certain things about steady state 00:03:54.819 --> 00:03:57.600 kinetics that people don't seem to get. 00:03:57.600 --> 00:04:00.440 And furthermore, were steady state kinetics 00:04:00.440 --> 00:04:02.600 important in this paper you had to read? 00:04:02.600 --> 00:04:04.010 Can anybody tell me? 00:04:04.010 --> 00:04:06.650 Did you get anything about steady state kinetics? 00:04:06.650 --> 00:04:09.236 Did you think about it? 00:04:09.236 --> 00:04:11.390 This will tell me how closely you read the paper. 00:04:14.673 --> 00:04:17.490 No? 00:04:17.490 --> 00:04:18.360 No one? 00:04:18.360 --> 00:04:22.010 OK, so this paper is hard and this is a paper 00:04:22.010 --> 00:04:24.290 that, even though I read it probably 20 times, 00:04:24.290 --> 00:04:26.820 I still learn stuff every time I read it. 00:04:26.820 --> 00:04:29.360 So you can't read a paper once. 00:04:29.360 --> 00:04:32.900 There's huge amounts of information in this paper. 00:04:32.900 --> 00:04:37.440 And if you go back and look at it three weeks from now, 00:04:37.440 --> 00:04:40.070 you'll probably get a lot more because we're continually 00:04:40.070 --> 00:04:43.130 filling in pieces of information from you 00:04:43.130 --> 00:04:44.290 in this complex system. 00:04:44.290 --> 00:04:44.990 Yeah? 00:04:44.990 --> 00:04:47.880 AUDIENCE: The part, I think, related to the steady state 00:04:47.880 --> 00:04:51.892 kinetics they measure Kcat, and Km, and their ratio. 00:04:51.892 --> 00:04:54.350 JOANNE STUBBE: Right, so that that's where the steady state 00:04:54.350 --> 00:04:55.640 kinetics is. 00:04:55.640 --> 00:04:58.100 And so if it goes to the question 00:04:58.100 --> 00:05:01.400 of what can you learn from steady state kinetics, OK? 00:05:01.400 --> 00:05:05.130 So let me just put down a simple system, 00:05:05.130 --> 00:05:06.890 which you've all seen if you take 00:05:06.890 --> 00:05:08.720 an introductory biochemistry course. 00:05:08.720 --> 00:05:15.770 People use this system because you don't have very many rate 00:05:15.770 --> 00:05:16.670 constants. 00:05:16.670 --> 00:05:21.620 So when I write down rate constants, I don't put K's. 00:05:21.620 --> 00:05:24.961 I just put 1, 2, 3 because it becomes hard to read anything, 00:05:24.961 --> 00:05:25.460 OK? 00:05:25.460 --> 00:05:28.930 So this is a simple system for any catalyst, 00:05:28.930 --> 00:05:35.220 OK, where some substrate could be EFTU, and tRNA, 00:05:35.220 --> 00:05:39.560 and GTP binding to the ribosome, OK? 00:05:39.560 --> 00:05:42.920 You do some chemistry to form some product. 00:05:42.920 --> 00:05:45.500 OK, and then the product dissociates. 00:05:45.500 --> 00:05:49.620 So if you look at the rate of the reaction-- 00:05:49.620 --> 00:05:51.830 so this involves the assay. 00:05:51.830 --> 00:05:55.970 You have to develop an assay where you can monitor something 00:05:55.970 --> 00:05:58.110 as easily as possible. 00:05:58.110 --> 00:05:59.100 That's the key thing. 00:05:59.100 --> 00:06:02.180 So I think here is where your chemistry background plays 00:06:02.180 --> 00:06:05.150 an incredibly important role because you can 00:06:05.150 --> 00:06:08.030 be creative about your assays. 00:06:08.030 --> 00:06:12.380 And so and you look at this as a function of the concentration 00:06:12.380 --> 00:06:14.660 of your substrate. 00:06:14.660 --> 00:06:17.430 What does the spectrum look like? 00:06:17.430 --> 00:06:21.145 What does the graph look like? 00:06:21.145 --> 00:06:22.520 How would you describe the graph? 00:06:22.520 --> 00:06:24.470 This is something you've seen in 507. 00:06:24.470 --> 00:06:25.490 We're just going back. 00:06:25.490 --> 00:06:28.630 What does it look like? 00:06:28.630 --> 00:06:32.630 Right, exactly-- rectangular hyperbole. 00:06:32.630 --> 00:06:35.680 OK, and so I think what's important 00:06:35.680 --> 00:06:39.460 is that this kind of behavior has been observed over and over 00:06:39.460 --> 00:06:43.480 and over again since 1940s when this curve was first 00:06:43.480 --> 00:06:45.370 described by Michaelis and Menton 00:06:45.370 --> 00:06:48.110 with many variations on the theme. 00:06:48.110 --> 00:06:50.200 And so what you need to think about 00:06:50.200 --> 00:06:52.870 is you have two parts of the curve. 00:06:52.870 --> 00:06:55.060 What's happening up here? 00:06:55.060 --> 00:06:59.790 What is the dependence on the reaction on substrate? 00:06:59.790 --> 00:07:01.535 So we have an enzyme that's a catalyst. 00:07:01.535 --> 00:07:04.070 It doesn't matter whether you're an organic chemist, 00:07:04.070 --> 00:07:06.650 an inorganic chemist, a biochemist. 00:07:06.650 --> 00:07:08.480 All of these things can be described 00:07:08.480 --> 00:07:13.350 by this simple, simple cartoon. 00:07:13.350 --> 00:07:15.920 So what's happening up here? 00:07:15.920 --> 00:07:19.489 What's happening in this part of your graph? 00:07:19.489 --> 00:07:20.530 AUDIENCE: It's saturated. 00:07:20.530 --> 00:07:22.321 JOANNE STUBBE: Yeah, see, you're saturated. 00:07:22.321 --> 00:07:24.390 So you're zero water and substrate, OK? 00:07:24.390 --> 00:07:28.760 And then what's happening over here? 00:07:28.760 --> 00:07:31.200 Your first order N substrate, OK? 00:07:31.200 --> 00:07:33.310 So from those observations, people 00:07:33.310 --> 00:07:38.940 derived equations, a general equation. 00:07:38.940 --> 00:07:41.790 So the rate of product formation, 00:07:41.790 --> 00:07:44.910 whatever you're assay is that you're using, 00:07:44.910 --> 00:07:50.230 is equal to Vmax times a concentration of substrate 00:07:50.230 --> 00:07:54.140 over Km plus the concentration of substrate. 00:07:54.140 --> 00:07:57.700 OK, so you've all seen this before. 00:07:57.700 --> 00:08:01.750 And if you look at this one simple case, 00:08:01.750 --> 00:08:05.760 and you look at what is Vmax equal to-- can anybody 00:08:05.760 --> 00:08:13.394 tell me what are the rate constants within Vmax? 00:08:13.394 --> 00:08:16.850 So Kcat times the concentration of enzyme. 00:08:16.850 --> 00:08:19.360 OK, so Vmax, and what does that mean? 00:08:19.360 --> 00:08:23.720 Kcat we'll see in a minute, is the turnover number 00:08:23.720 --> 00:08:25.490 times the concentration of enzyme. 00:08:25.490 --> 00:08:27.990 That means all your catalysts have stuff on it. 00:08:27.990 --> 00:08:29.050 It can't go any faster. 00:08:29.050 --> 00:08:31.550 It doesn't matter if you add more, more, and more substrate. 00:08:31.550 --> 00:08:32.466 You have no catalysts. 00:08:32.466 --> 00:08:35.559 So that's what's limiting the reaction. 00:08:35.559 --> 00:08:42.140 So if you derive this equation using steady state assumptions, 00:08:42.140 --> 00:08:44.390 what are the four sets of equations 00:08:44.390 --> 00:08:48.612 you need to be able to derive this expression? 00:08:48.612 --> 00:08:50.360 Can anybody tell me? 00:08:50.360 --> 00:08:53.420 What are the conditions you need to do? 00:08:53.420 --> 00:08:57.570 So what's the goal of deriving this equation, first of all? 00:08:57.570 --> 00:08:59.690 And then what are the assumptions you make? 00:09:02.350 --> 00:09:05.390 OK, so you want to be able to describe what 00:09:05.390 --> 00:09:07.550 you see experimentally, OK? 00:09:07.550 --> 00:09:09.410 So the first thing you have to do 00:09:09.410 --> 00:09:12.080 is be able to measure it experimentally, OK? 00:09:12.080 --> 00:09:14.960 So you have to have something in terms 00:09:14.960 --> 00:09:18.530 of an experimentally measurable parameter. 00:09:18.530 --> 00:09:23.690 And if you look at e, es, ep, which one of these 00:09:23.690 --> 00:09:27.620 are going to be measurable? 00:09:27.620 --> 00:09:29.957 AUDIENCE: Going to be the substrate and the product. 00:09:29.957 --> 00:09:31.790 JOANNE STUBBE: OK, so substrate and product. 00:09:31.790 --> 00:09:33.030 Yeah, you can measure substrate. 00:09:33.030 --> 00:09:34.030 You can measure product. 00:09:34.030 --> 00:09:37.320 But I'm talking about e. 00:09:37.320 --> 00:09:41.360 OK, so we have the e, we have an es, in this case we have an ep, 00:09:41.360 --> 00:09:46.660 most of the times you have 20 more e, equilibria. 00:09:46.660 --> 00:09:49.794 So which one can you measure experimentally? 00:09:49.794 --> 00:09:52.510 AUDIENCE: [INAUDIBLE]. 00:09:52.510 --> 00:09:55.242 JOANNE STUBBE: Pardon me? 00:09:55.242 --> 00:09:56.450 AUDIENCE: [INAUDIBLE] enzyme. 00:09:56.450 --> 00:09:59.300 JOANNE STUBBE: Yeah, so you can measure the total enzyme. 00:09:59.300 --> 00:10:03.140 OK, so that's this the enzyme conservation equation. 00:10:03.140 --> 00:10:05.900 So you have-- I'm not going to draw this all out. 00:10:05.900 --> 00:10:08.660 This is a review that you've already seen, presumably. 00:10:08.660 --> 00:10:10.507 So that's the conservation equation. 00:10:10.507 --> 00:10:12.590 How do you measure the concentration of an enzyme? 00:10:15.326 --> 00:10:17.150 AUDIENCE: UV vis. 00:10:17.150 --> 00:10:19.580 JOANNE STUBBE: UV vis. 00:10:19.580 --> 00:10:21.890 What amino acids absorb in the visible? 00:10:24.860 --> 00:10:25.800 AUDIENCE: Tryptophan. 00:10:25.800 --> 00:10:26.380 JOANNE STUBBE: In the visible. 00:10:26.380 --> 00:10:27.631 AUDIENCE: Oh, in the visible? 00:10:27.631 --> 00:10:28.130 None. 00:10:28.130 --> 00:10:28.510 JOANNE STUBBE: None. 00:10:28.510 --> 00:10:29.770 So don't say UV vis. 00:10:29.770 --> 00:10:31.100 Say UV, OK? 00:10:31.100 --> 00:10:34.910 So this is key to being able to sort things out. 00:10:34.910 --> 00:10:41.330 So what are the amino acid side chains that absorb in the UV? 00:10:41.330 --> 00:10:43.287 This comes back to-- you need to-- 00:10:43.287 --> 00:10:44.680 AUDIENCE: Tryptophan, tyrosine. 00:10:44.680 --> 00:10:45.340 JOANNE STUBBE: Right. 00:10:45.340 --> 00:10:47.256 So tryptophan and tyrocine are the major ones. 00:10:47.256 --> 00:10:49.060 Then phenylalanine is much smaller. 00:10:49.060 --> 00:10:51.250 So you can measure this. 00:10:51.250 --> 00:10:54.640 But, in general, you can't measure all the other forms. 00:10:54.640 --> 00:10:57.520 OK, so you know this, and that's required 00:10:57.520 --> 00:11:01.030 to be able to get this expression that describes 00:11:01.030 --> 00:11:02.890 this rectangular hyperbole. 00:11:02.890 --> 00:11:06.070 What about the substrate concentration? 00:11:06.070 --> 00:11:09.190 Under normal assays, if you've done an assay in the lab, 00:11:09.190 --> 00:11:11.020 how is the reaction set up? 00:11:14.868 --> 00:11:16.610 How much enzyme do you have in there? 00:11:16.610 --> 00:11:19.475 How much substrate do you have in there? 00:11:19.475 --> 00:11:21.244 AUDIENCE: A lot of substrate. 00:11:21.244 --> 00:11:22.660 JOANNE STUBBE: A lot of substrate. 00:11:22.660 --> 00:11:24.610 And what conditions are you under, 00:11:24.610 --> 00:11:29.470 perhaps, if you have a lot of substrate, over here 00:11:29.470 --> 00:11:31.059 in this graph? 00:11:31.059 --> 00:11:32.600 AUDIENCE: You have to saturate your-- 00:11:32.600 --> 00:11:34.475 JOANNE STUBBE: Yeah, well, you don't have to, 00:11:34.475 --> 00:11:37.150 but you would be saturated if you had a lot of substrate. 00:11:37.150 --> 00:11:38.890 How much enzyme do you have in there? 00:11:38.890 --> 00:11:40.424 A lot or a little? 00:11:40.424 --> 00:11:41.215 AUDIENCE: A little. 00:11:41.215 --> 00:11:42.381 JOANNE STUBBE: A little, OK? 00:11:42.381 --> 00:11:46.900 So the enzyme, the concentration of the substrate 00:11:46.900 --> 00:11:49.731 is much, much greater than the concentration of the enzyme, 00:11:49.731 --> 00:11:50.230 OK? 00:11:50.230 --> 00:11:52.930 So that's a typical steady state assay 00:11:52.930 --> 00:11:57.610 when you go to determine the rate of your reaction. 00:11:57.610 --> 00:11:59.361 So because the concentration of the enzyme 00:11:59.361 --> 00:12:01.276 is much, much greater than the concentration-- 00:12:01.276 --> 00:12:03.200 the concentration of the substrate is much, 00:12:03.200 --> 00:12:05.290 much greater than the concentration of the enzyme, 00:12:05.290 --> 00:12:07.630 you don't have to worry about substrate 00:12:07.630 --> 00:12:09.550 being bound in these forms. 00:12:09.550 --> 00:12:13.180 So the second equation you routinely use 00:12:13.180 --> 00:12:16.750 is called the substrate conservation equation, 00:12:16.750 --> 00:12:20.260 because it doesn't change, because the amount of this es 00:12:20.260 --> 00:12:23.990 on the enzyme, which is tiny, you don't need to measure it. 00:12:23.990 --> 00:12:25.570 So this is the second. 00:12:25.570 --> 00:12:27.880 So these are both conservation equations. 00:12:32.600 --> 00:12:37.660 OK, so we just said we were doing steady state kinetics, 00:12:37.660 --> 00:12:38.350 OK? 00:12:38.350 --> 00:12:41.020 So now you need to be able to make the steady state 00:12:41.020 --> 00:12:43.500 assumption, which hopefully all of you know. 00:12:43.500 --> 00:12:48.250 So the rate of change of some intermediate with respect 00:12:48.250 --> 00:12:52.780 to time is equal to 0, that is we're under a set of conditions 00:12:52.780 --> 00:12:55.420 where the rate of formation is equal to the rate 00:12:55.420 --> 00:12:58.720 of disappearance of whatever this species is. 00:12:58.720 --> 00:13:00.730 And what is the fourth equation we 00:13:00.730 --> 00:13:04.429 need to be able to set up this? 00:13:04.429 --> 00:13:06.220 What is the fourth thing, which is probably 00:13:06.220 --> 00:13:08.152 the most straightforward? 00:13:08.152 --> 00:13:09.610 And, again, it needs to be in terms 00:13:09.610 --> 00:13:13.882 of experimentally measurable parameters. 00:13:13.882 --> 00:13:16.280 What are we measuring in our reaction? 00:13:16.280 --> 00:13:19.160 AUDIENCE: You said the position from vs 00:13:19.160 --> 00:13:21.080 to [INAUDIBLE] is irreversible. 00:13:21.080 --> 00:13:26.330 JOANNE STUBBE: No, you I could have done this. 00:13:26.330 --> 00:13:28.355 And what would that have done to my equation? 00:13:28.355 --> 00:13:30.517 It just would have put in more rate constants. 00:13:30.517 --> 00:13:33.100 I'm going to show you what the rate constants are in a minute. 00:13:33.100 --> 00:13:36.120 There's nothing-- in fact, almost no enzyme reactions 00:13:36.120 --> 00:13:37.520 are irreversible. 00:13:37.520 --> 00:13:39.940 If you look, you can find reversibility 00:13:39.940 --> 00:13:41.050 in almost all reactions. 00:13:41.050 --> 00:13:47.110 This is-- so why do people write equations like this? 00:13:47.110 --> 00:13:50.580 They like irreversible reactions because it makes 00:13:50.580 --> 00:13:52.900 the kinetic derivation simpler. 00:13:52.900 --> 00:13:55.300 You don't have as many rate constants, OK? 00:13:55.300 --> 00:13:57.520 So, but what do you need now? 00:13:57.520 --> 00:13:59.020 We're monitoring the reaction? 00:13:59.020 --> 00:14:00.960 What are you going to monitor? 00:14:00.960 --> 00:14:02.847 So we know how much enzyme we have. 00:14:02.847 --> 00:14:03.680 We can measure that. 00:14:03.680 --> 00:14:05.304 We know how much substrate we can have. 00:14:05.304 --> 00:14:06.260 We can measure that. 00:14:06.260 --> 00:14:08.650 We know what the steady state assumption is, 00:14:08.650 --> 00:14:09.670 and we have an equation. 00:14:09.670 --> 00:14:10.750 So we can describe that. 00:14:10.750 --> 00:14:12.083 What's the other thing you need? 00:14:12.083 --> 00:14:13.990 It's the standard thing. 00:14:13.990 --> 00:14:16.330 How do you describe the rate of product formation? 00:14:19.110 --> 00:14:20.270 That's this guy over here. 00:14:24.030 --> 00:14:25.670 So what do you need? 00:14:25.670 --> 00:14:28.570 You need some kind of an equation 00:14:28.570 --> 00:14:31.570 that expresses just appearance of substrate, 00:14:31.570 --> 00:14:33.210 formation of products. 00:14:33.210 --> 00:14:36.420 So you need a way of measuring this. 00:14:36.420 --> 00:14:38.470 And you can do this many ways, even 00:14:38.470 --> 00:14:40.900 from a simple equation we've shown over here 00:14:40.900 --> 00:14:44.020 because a description of the rate of product formation 00:14:44.020 --> 00:14:48.250 is simply the net flux through any step in the pathway. 00:14:48.250 --> 00:14:50.860 And so what you see people writing 00:14:50.860 --> 00:14:53.500 is they immediately go to an irreversible step 00:14:53.500 --> 00:14:56.530 because it makes the algebra simpler. 00:14:56.530 --> 00:14:58.720 So k3 times the concentration of ep 00:14:58.720 --> 00:15:00.820 would be the net flux through this step. 00:15:00.820 --> 00:15:03.040 But I could write the net flux through this step 00:15:03.040 --> 00:15:04.940 and I would get the same answer. 00:15:04.940 --> 00:15:09.010 So it's the net flux through any step in the pathway. 00:15:09.010 --> 00:15:11.890 OK, so why am I going through all of this? 00:15:19.375 --> 00:15:21.230 OK, and the reason I'm going through this 00:15:21.230 --> 00:15:25.650 is because of this Kcat over km, which I just described to you. 00:15:25.650 --> 00:15:30.230 So one of the questions I asked you to think about when you're 00:15:30.230 --> 00:15:32.900 thinking about steady state kinetics 00:15:32.900 --> 00:15:36.290 is what are the two important parameters you get out 00:15:36.290 --> 00:15:40.530 of Michaelis Menton analysis? 00:15:40.530 --> 00:15:43.850 And the reason I ask this is because, in my opinion, 00:15:43.850 --> 00:15:45.560 it's not correct in most textbooks. 00:15:48.710 --> 00:15:52.200 So what are the two important parameters 00:15:52.200 --> 00:15:54.470 you get that you learned about that you probably even 00:15:54.470 --> 00:15:56.540 evaluated if you did something in the lab? 00:16:01.074 --> 00:16:01.699 AUDIENCE: Kcat. 00:16:01.699 --> 00:16:04.220 JOANNE STUBBE: Kcat is one of them. 00:16:04.220 --> 00:16:06.744 OK, and what's the other one? 00:16:06.744 --> 00:16:09.029 AUDIENCE: Km. 00:16:09.029 --> 00:16:12.070 JOANNE STUBBE: OK, so this is what everybody says, is km. 00:16:12.070 --> 00:16:14.350 And that's not correct, OK? 00:16:14.350 --> 00:16:18.245 So let me put down what the-- 00:16:18.245 --> 00:16:20.020 what did I do with it-- 00:16:20.020 --> 00:16:24.320 the values for the kinetic constants are here. 00:16:24.320 --> 00:16:28.006 So in this particular simple equation, 00:16:28.006 --> 00:16:33.286 it's Kcat is 2 times 3 over 2 plus 3. 00:16:33.286 --> 00:16:36.130 OK, so this is Kcat. 00:16:36.130 --> 00:16:39.780 And Km out of this analysis is 3. 00:16:39.780 --> 00:16:42.180 The numbers really aren't important. 00:16:42.180 --> 00:16:47.190 What I want you to see is that there 00:16:47.190 --> 00:16:50.290 are a huge number of first order rate constants 00:16:50.290 --> 00:16:54.700 in each of these parameters Km and Kcat, OK? 00:16:54.700 --> 00:16:56.669 Can you measure these? 00:16:56.669 --> 00:16:58.210 Can you measure these rate constants? 00:16:58.210 --> 00:17:00.970 That's what you want to know if you want to understand how this 00:17:00.970 --> 00:17:03.940 works, you would like to understand 00:17:03.940 --> 00:17:06.470 the reaction coordinate and what the rate constants are 00:17:06.470 --> 00:17:07.720 for every step in the pathway. 00:17:07.720 --> 00:17:09.760 That's what the whole Rodnina paper 00:17:09.760 --> 00:17:14.200 is about with the long range goal of understanding fidelity. 00:17:14.200 --> 00:17:16.869 Can we come up with a model for fidelity 00:17:16.869 --> 00:17:20.630 in the translational process that's contributed by EFTU? 00:17:24.033 --> 00:17:30.430 So can we measure these guys from an assay the concentration 00:17:30.430 --> 00:17:34.915 of the enzyme, The concentration of the substrate, 00:17:34.915 --> 00:17:38.291 the steady state assumption? 00:17:38.291 --> 00:17:39.240 What do you think? 00:17:43.950 --> 00:17:45.392 Don't be afraid. 00:17:45.392 --> 00:17:48.504 This is a discussion. 00:17:48.504 --> 00:17:49.870 What do you think? 00:17:49.870 --> 00:17:52.350 Can we measure? 00:17:52.350 --> 00:17:54.361 AUDIENCE: Does it depend how fast it is? 00:17:54.361 --> 00:17:55.110 JOANNE STUBBE: No. 00:17:55.110 --> 00:17:55.750 AUDIENCE: No? 00:17:55.750 --> 00:17:58.470 JOANNE STUBBE: No. 00:17:58.470 --> 00:18:00.240 It is dependent on how fast it is, 00:18:00.240 --> 00:18:02.460 but it doesn't matter how fast it 00:18:02.460 --> 00:18:06.840 is to answer this question, OK? 00:18:06.840 --> 00:18:08.310 Anybody else got another guess? 00:18:10.880 --> 00:18:11.380 What? 00:18:11.380 --> 00:18:12.190 Your name? 00:18:12.190 --> 00:18:12.610 AUDIENCE: Rebecca. 00:18:12.610 --> 00:18:13.030 JOANNE STUBBE: Rebecca. 00:18:13.030 --> 00:18:13.630 What's your name? 00:18:13.630 --> 00:18:14.010 AUDIENCE: Nicole. 00:18:14.010 --> 00:18:14.926 JOANNE STUBBE: Nicole. 00:18:14.926 --> 00:18:16.598 OK, yeah? 00:18:16.598 --> 00:18:18.065 AUDIENCE: Yeah. 00:18:18.065 --> 00:18:20.021 [INAUDIBLE] measure them [INAUDIBLE] 00:18:20.021 --> 00:18:23.444 we measure the initial rate, [INAUDIBLE] 00:18:23.444 --> 00:18:25.004 take that [INAUDIBLE]. 00:18:25.004 --> 00:18:26.920 JOANNE STUBBE: So you get Kcat and you get Km. 00:18:26.920 --> 00:18:28.420 That's not the question I asked. 00:18:28.420 --> 00:18:31.420 I asked, can you measure all the first order rate constants 00:18:31.420 --> 00:18:34.560 that make up Kcat and Km? 00:18:34.560 --> 00:18:35.460 No. 00:18:35.460 --> 00:18:37.500 So the problem with steady state kinetics 00:18:37.500 --> 00:18:39.690 is you can't really learn very much, OK? 00:18:39.690 --> 00:18:42.990 So what can you learn from steady state kinetics, 00:18:42.990 --> 00:18:44.835 and why do we keep looking at it? 00:18:44.835 --> 00:18:46.890 OK, why is it the first thing you've seen 00:18:46.890 --> 00:18:49.610 this with the tRNA synthetases? 00:18:49.610 --> 00:18:54.090 You saw Kcat over Km values charging with valine 00:18:54.090 --> 00:18:55.760 or isoleucine, right? 00:18:55.760 --> 00:18:58.650 In this paper, if you go back and look carefully 00:18:58.650 --> 00:19:00.540 at the discussion at the end of the paper-- 00:19:00.540 --> 00:19:03.420 so hopefully after this class you'll go back and you'll read 00:19:03.420 --> 00:19:04.590 that-- 00:19:04.590 --> 00:19:09.330 a lot of the discussion is about mechanisms of fidelity 00:19:09.330 --> 00:19:12.460 where they are thinking about these initial steps. 00:19:12.460 --> 00:19:17.760 And so these initial steps are really the selection steps 00:19:17.760 --> 00:19:20.330 of these things binding, OK? 00:19:20.330 --> 00:19:22.770 And if you go back and you look at the equation 00:19:22.770 --> 00:19:26.080 that they derive, it's amazingly complicated. 00:19:26.080 --> 00:19:26.580 Why? 00:19:26.580 --> 00:19:31.040 Because we have many more equilibria in our equation, 00:19:31.040 --> 00:19:36.540 but what you can get out of all this is Kcat and Kcat over Km. 00:19:36.540 --> 00:19:40.500 So Km really is not very informative 00:19:40.500 --> 00:19:44.760 at all because it's composed of a whole bunch of first order 00:19:44.760 --> 00:19:46.880 rate constants. 00:19:46.880 --> 00:19:49.920 It's always never equal to the dissociation constant, OK? 00:19:49.920 --> 00:19:52.287 So you can't-- so what it is mathematically, 00:19:52.287 --> 00:19:54.495 it's the concentration required to reach half maximum 00:19:54.495 --> 00:19:55.480 of velocity. 00:19:55.480 --> 00:19:57.710 So it doesn't really tell you anything. 00:19:57.710 --> 00:19:59.550 It's just half maximum of velocity. 00:19:59.550 --> 00:20:03.360 OK, so the two parameters that you need to think about-- 00:20:03.360 --> 00:20:05.070 and this goes back to the way you 00:20:05.070 --> 00:20:06.540 do experiments in the steady state 00:20:06.540 --> 00:20:08.190 versus the pre-steady state, which 00:20:08.190 --> 00:20:13.080 is what we're focusing on in this paper, 00:20:13.080 --> 00:20:16.880 is that you have two extremes when you do kinetics. 00:20:16.880 --> 00:20:18.480 And kinetics is something-- how do 00:20:18.480 --> 00:20:19.740 you learn how to do kinetics? 00:20:19.740 --> 00:20:21.180 You do them yourself. 00:20:21.180 --> 00:20:22.990 And you think about-- 00:20:22.990 --> 00:20:25.170 you think about what you think is going on. 00:20:25.170 --> 00:20:28.124 And then you make guesses about what's going on. 00:20:28.124 --> 00:20:30.540 And these are one of the types of experiments, when you're 00:20:30.540 --> 00:20:34.200 doing them you change your experimental design 00:20:34.200 --> 00:20:35.680 in the middle of your experiment. 00:20:35.680 --> 00:20:39.120 So it takes a lot of practice to get good at kinetics. 00:20:39.120 --> 00:20:40.920 But what you do with all kinetics, 00:20:40.920 --> 00:20:43.440 look at the extremes, the limits. 00:20:43.440 --> 00:20:47.830 So one extreme is the concentration of s 00:20:47.830 --> 00:20:49.870 goes to infinity. 00:20:49.870 --> 00:20:53.100 OK, so if you look at that extreme, what do you have? 00:20:53.100 --> 00:20:55.770 If s goes to infinity, what happens to b? 00:20:59.620 --> 00:21:02.740 What happens to this equation? 00:21:02.740 --> 00:21:04.740 AUDIENCE: [INAUDIBLE]. 00:21:04.740 --> 00:21:08.400 JOANNE STUBBE: Yeah, so it goes to Vmax, or Kcat times 00:21:08.400 --> 00:21:09.570 the concentration of e. 00:21:09.570 --> 00:21:11.960 So you're up here, OK? 00:21:11.960 --> 00:21:13.740 And so what is Kcat? 00:21:13.740 --> 00:21:15.570 So you can get out of this Kcat. 00:21:15.570 --> 00:21:18.690 Why is Kcat an important parameter? 00:21:18.690 --> 00:21:20.130 Why do people care about Kcat? 00:21:27.826 --> 00:21:29.815 Hey, what's your name? 00:21:29.815 --> 00:21:30.440 AUDIENCE: Alex. 00:21:30.440 --> 00:21:32.300 JOANNE STUBBE: Alex. 00:21:32.300 --> 00:21:34.924 My nephew's name is Alex. 00:21:34.924 --> 00:21:37.730 I'll remember that, OK? 00:21:37.730 --> 00:21:40.540 You're stuck. 00:21:40.540 --> 00:21:42.740 What's Kcat? 00:21:42.740 --> 00:21:47.509 AUDIENCE: It's like how quickly the enzyme turns over-- 00:21:47.509 --> 00:21:48.800 JOANNE STUBBE: Per active site. 00:21:48.800 --> 00:21:50.650 So it's called the turnover number. 00:21:50.650 --> 00:21:51.930 OK, so what does it tell you. 00:21:51.930 --> 00:21:54.110 It tells you how good your catalyst is, OK? 00:21:54.110 --> 00:21:56.290 So that's pretty important. 00:21:56.290 --> 00:21:59.750 So this is the turnover number. 00:21:59.750 --> 00:22:02.030 And I would also say it's pretty-- 00:22:02.030 --> 00:22:07.100 in the age of recombinant production or proteins, 00:22:07.100 --> 00:22:10.880 where we never isolate proteins from the normal source-- 00:22:10.880 --> 00:22:14.960 we isolate them all from bacteria or from yeast-- 00:22:14.960 --> 00:22:18.230 Kcat becomes really important to know, OK? 00:22:18.230 --> 00:22:20.510 So how do you know what the real Kcat should 00:22:20.510 --> 00:22:25.070 be if you isolate your enzyme from a protein that's 00:22:25.070 --> 00:22:26.450 expressed in E. coli? 00:22:26.450 --> 00:22:28.100 Do you think you get the real Kcat? 00:22:34.530 --> 00:22:36.220 Have you ever thought about that? 00:22:36.220 --> 00:22:37.390 Most people haven't, OK? 00:22:37.390 --> 00:22:40.552 So you're not alone. 00:22:40.552 --> 00:22:44.180 What could happen if you expressed your protein 00:22:44.180 --> 00:22:48.410 in a bacteria, or in another model organism like yeast? 00:22:48.410 --> 00:22:49.886 AUDIENCE: [INAUDIBLE]. 00:22:49.886 --> 00:22:51.440 JOANNE STUBBE: Yeah, it might not 00:22:51.440 --> 00:22:53.150 have the appropriate-- it's probably 00:22:53.150 --> 00:22:54.650 not-- it could be post-translational 00:22:54.650 --> 00:22:55.280 modification. 00:22:55.280 --> 00:22:56.720 It could be co-factors. 00:22:56.720 --> 00:22:59.300 So there are examples in the literature of very, very 00:22:59.300 --> 00:23:02.600 smart scientists who have spent 25 years of their life studying 00:23:02.600 --> 00:23:06.800 an enzyme that was only 1% active. 00:23:06.800 --> 00:23:09.050 So this is, in this course-- and I 00:23:09.050 --> 00:23:10.560 think in general in biochemistry-- 00:23:10.560 --> 00:23:12.560 you've got to go back and forth between the cell 00:23:12.560 --> 00:23:15.120 and what you see in the test tube. 00:23:15.120 --> 00:23:21.352 So this Kcat, if the number is 0.00001 per second, 00:23:21.352 --> 00:23:23.810 you have to have some intuition that tells you, oh, my god. 00:23:23.810 --> 00:23:24.990 That's so slow. 00:23:24.990 --> 00:23:26.850 Something-- something is wrong. 00:23:26.850 --> 00:23:30.060 So this number of turnover is incredibly important. 00:23:30.060 --> 00:23:33.620 It gives you a feeling for how good your catalyst is. 00:23:33.620 --> 00:23:35.180 But the number we're really after 00:23:35.180 --> 00:23:38.450 is the second example and the other limit. 00:23:38.450 --> 00:23:43.410 And what happens is s goes to 0, what happens to this equation. 00:23:43.410 --> 00:23:45.410 So those are the two extremes, OK? 00:23:45.410 --> 00:23:48.020 So as s goes to 0, 00:23:48.020 --> 00:23:49.835 OK, that's the other part of this equation. 00:23:54.560 --> 00:23:57.340 What happens to the equation? 00:23:57.340 --> 00:23:59.870 The rate of product formation is equal to-- 00:23:59.870 --> 00:24:03.530 and I'll write Vmax as KT times the concentration 00:24:03.530 --> 00:24:05.780 of total enzyme, OK? 00:24:05.780 --> 00:24:06.860 I didn't write it down. 00:24:06.860 --> 00:24:09.700 Hopefully you all know that. 00:24:09.700 --> 00:24:14.230 So what you now get is Kcat over Km times 00:24:14.230 --> 00:24:17.360 the concentration of e times the concentration of s. 00:24:17.360 --> 00:24:22.210 So what is this guy, if you look at this equation? 00:24:22.210 --> 00:24:23.274 What's Kcat over Km? 00:24:23.274 --> 00:24:24.065 What are the units? 00:24:30.811 --> 00:24:32.190 Kinetics isn't that hard. 00:24:34.950 --> 00:24:36.960 These are pretty-- if you think this is hard, 00:24:36.960 --> 00:24:38.500 wait till you start getting-- 00:24:38.500 --> 00:24:41.085 we're not going to go into derivation of steady state, 00:24:41.085 --> 00:24:42.960 pre-steady state analysis. 00:24:42.960 --> 00:24:46.070 But this is pretty simple compared to pre-steady state 00:24:46.070 --> 00:24:46.830 analysis. 00:24:46.830 --> 00:24:48.510 So what's Kcat over Km? 00:24:48.510 --> 00:24:49.810 What are the units? 00:24:49.810 --> 00:24:51.100 AUDIENCE: [INAUDIBLE]. 00:24:51.100 --> 00:24:52.250 JOANNE STUBBE: Yeah. 00:24:52.250 --> 00:24:52.800 Yeah. 00:24:52.800 --> 00:24:54.380 So it's second order rate constant. 00:24:54.380 --> 00:24:55.570 So that's the key thing. 00:24:55.570 --> 00:24:57.160 So what are you looking at? 00:24:57.160 --> 00:24:58.800 You can look at that by this equation. 00:24:58.800 --> 00:25:02.070 What you're looking at is the enzyme combining 00:25:02.070 --> 00:25:04.150 with the substrate, OK? 00:25:04.150 --> 00:25:05.680 And that's what we care about. 00:25:05.680 --> 00:25:09.480 That's the specificity, specificity, or efficiency 00:25:09.480 --> 00:25:10.390 of your reaction. 00:25:10.390 --> 00:25:15.420 So if you have a tRNA loosing and an tRNA phenylalanine, 00:25:15.420 --> 00:25:19.120 they're both competing for binding to the substrate. 00:25:19.120 --> 00:25:22.530 So the important parameter to think about that selection-- 00:25:22.530 --> 00:25:26.340 and that's why that's important at the end of this paper-- 00:25:26.340 --> 00:25:28.710 relates to Kcat over Km. 00:25:28.710 --> 00:25:32.100 It's the specificity or efficiency number. 00:25:32.100 --> 00:25:35.980 And if any of you ever work in a pharmaceutical industry, 00:25:35.980 --> 00:25:38.010 you'll find out that, of course, you never-- 00:25:38.010 --> 00:25:39.630 and you're looking for inhibitors, 00:25:39.630 --> 00:25:40.950 you never look at Kcat. 00:25:40.950 --> 00:25:42.240 Why don't you look at Kcat? 00:25:42.240 --> 00:25:44.520 You always look at Kcat over Km. 00:25:44.520 --> 00:25:45.667 Why is that true? 00:25:45.667 --> 00:25:46.500 Can anybody tell me? 00:25:46.500 --> 00:25:49.590 If you were looking for a drug, if you were looking 00:25:49.590 --> 00:25:52.530 for an antibiotic, fusidic acid that we talked about 00:25:52.530 --> 00:25:59.830 today that inhibits the EFG that Liz talked about, 00:25:59.830 --> 00:26:01.520 how would you set up the experiment 00:26:01.520 --> 00:26:03.143 to look for inhibition? 00:26:07.980 --> 00:26:11.110 What would you do with your concentration of substrate? 00:26:11.110 --> 00:26:13.340 Do you want it high or do you want it low? 00:26:13.340 --> 00:26:14.719 AUDIENCE: You want it low. 00:26:14.719 --> 00:26:16.010 JOANNE STUBBE: You want it low. 00:26:16.010 --> 00:26:19.210 Why do you want it low? 00:26:19.210 --> 00:26:22.399 AUDIENCE: Because [INAUDIBLE]. 00:26:22.399 --> 00:26:24.190 JOANNE STUBBE: Yeah, so if you're inhibitor 00:26:24.190 --> 00:26:27.024 is binding to the same site, and you have a huge amount of this, 00:26:27.024 --> 00:26:29.440 no matter what you do, even if this was a great inhibitor, 00:26:29.440 --> 00:26:31.762 if you had 10,000 times the amount of this, 00:26:31.762 --> 00:26:33.470 you're never going to see any inhibition. 00:26:33.470 --> 00:26:35.439 So understanding these simple principles-- 00:26:35.439 --> 00:26:36.980 which I can tell you there are people 00:26:36.980 --> 00:26:38.870 that don't get this in drug companies-- 00:26:38.870 --> 00:26:40.730 are pretty important, OK? 00:26:40.730 --> 00:26:43.190 So Kcat and Kcat over Km, boring. 00:26:43.190 --> 00:26:44.570 But it's not really so boring. 00:26:44.570 --> 00:26:47.909 It's sort of central to everything 00:26:47.909 --> 00:26:50.450 that you'll be thinking about over the course of the semester 00:26:50.450 --> 00:26:52.426 and almost all the modules in some form, 00:26:52.426 --> 00:26:54.800 although we won't highlight it like we're highlighting it 00:26:54.800 --> 00:26:55.540 here. 00:26:55.540 --> 00:27:00.620 OK, so, again, the reason we care about Kcat over Km 00:27:00.620 --> 00:27:04.614 is this question of selectivity. 00:27:04.614 --> 00:27:09.470 And I urge you to go back and look in the methods 00:27:09.470 --> 00:27:10.990 section of your paper. 00:27:10.990 --> 00:27:14.540 Now, this paper is packed full of stuff, OK? so as I said, 00:27:14.540 --> 00:27:16.220 I read it 20 times. 00:27:16.220 --> 00:27:19.550 Every time I read it, I find out something new. 00:27:19.550 --> 00:27:21.800 And furthermore, I think the paper-- how many of you 00:27:21.800 --> 00:27:23.924 found it a tough slog to go through this paper? 00:27:23.924 --> 00:27:25.340 This is probably the hardest paper 00:27:25.340 --> 00:27:28.434 you're going to look at in my opinion? 00:27:28.434 --> 00:27:29.850 Did you think it was well written? 00:27:29.850 --> 00:27:31.265 Did you get the ideas? 00:27:34.352 --> 00:27:37.386 OK, Did you all get the ideas or not, 00:27:37.386 --> 00:27:38.760 or where you completely confused, 00:27:38.760 --> 00:27:40.343 or you didn't spend enough time on it? 00:27:40.343 --> 00:27:42.624 How much time did you have to spend on it? 00:27:42.624 --> 00:27:44.025 AUDIENCE: Probably about an hour. 00:27:44.025 --> 00:27:45.150 JOANNE STUBBE: OK, an hour. 00:27:45.150 --> 00:27:47.420 OK, so I would say-- 00:27:47.420 --> 00:27:50.500 I read the paper 45 times, and it takes me two hours 00:27:50.500 --> 00:27:52.130 to read a paper like this. 00:27:52.130 --> 00:27:55.766 OK, so again, it's a question of what level 00:27:55.766 --> 00:27:56.890 you want to look at things. 00:27:56.890 --> 00:27:59.350 And I think part of what this course is about 00:27:59.350 --> 00:28:02.340 is looking at experimental details. 00:28:02.340 --> 00:28:03.340 You're want to see that. 00:28:03.340 --> 00:28:07.330 And the problems set, you're going to see that in lecture. 00:28:07.330 --> 00:28:09.340 You're going to see that probably 00:28:09.340 --> 00:28:12.250 next time when we continue to look at the primary data 00:28:12.250 --> 00:28:13.990 that they collected, how important 00:28:13.990 --> 00:28:19.990 it is to look at the axes, and not just looking at it rapidly. 00:28:19.990 --> 00:28:23.150 You really have to think about what the data is telling you. 00:28:23.150 --> 00:28:28.570 So this paper is complicated from my point of view 00:28:28.570 --> 00:28:30.710 because it's based on-- 00:28:30.710 --> 00:28:32.620 it's based on 15 other papers. 00:28:32.620 --> 00:28:36.040 OK, so for you to really believe what they say, 00:28:36.040 --> 00:28:38.630 which is what you need to do as a scientist, 00:28:38.630 --> 00:28:42.220 how to critically evaluate somebody else's data, 00:28:42.220 --> 00:28:44.880 you need to really go back-- and we didn't ask you to do that-- 00:28:44.880 --> 00:28:49.742 and really critically evaluate the earlier experiments 00:28:49.742 --> 00:28:52.200 they've done, because some of the conclusions they've done, 00:28:52.200 --> 00:28:55.270 when we look at the primary data, I could have drawn-- 00:28:55.270 --> 00:28:57.130 without knowing all that primary data, 00:28:57.130 --> 00:29:00.110 I could have drawn a conclusion completely different. 00:29:00.110 --> 00:29:03.420 So you see something and you've got to explain it, OK? 00:29:03.420 --> 00:29:05.470 And so when you start out, you have no idea. 00:29:05.470 --> 00:29:06.980 You have a very simple model. 00:29:06.980 --> 00:29:09.490 And in general, the model's almost always 00:29:09.490 --> 00:29:11.024 get more and more complex. 00:29:11.024 --> 00:29:13.190 That's what you're going to see over and over again. 00:29:13.190 --> 00:29:16.660 You start out as simple as possible, and then things 00:29:16.660 --> 00:29:18.220 get more complex. 00:29:18.220 --> 00:29:24.760 OK, so what we want to do now is ask the question. 00:29:24.760 --> 00:29:27.250 And I've just told you, you can't 00:29:27.250 --> 00:29:29.530 evaluate these individual rate constants. 00:29:29.530 --> 00:29:32.080 We just don't have enough variables, OK? 00:29:32.080 --> 00:29:34.870 We don't have enough that we can measure, 00:29:34.870 --> 00:29:37.570 that we can change the substrate concentration we can change, 00:29:37.570 --> 00:29:39.490 which changes the rate of product formation. 00:29:39.490 --> 00:29:40.781 So those are the two variables. 00:29:40.781 --> 00:29:42.460 But we have many more unknowns. 00:29:42.460 --> 00:29:46.060 We have k1, k2, k minus 2, k2, et cetera. 00:29:46.060 --> 00:29:48.020 So we can't evaluate these things. 00:29:48.020 --> 00:29:50.380 So the question is, is there any way 00:29:50.380 --> 00:29:53.650 you can start getting the primary rate 00:29:53.650 --> 00:29:57.220 constant, the numbers to the primary rate constants, OK? 00:29:57.220 --> 00:30:00.460 And so one way that people do this nowadays-- 00:30:00.460 --> 00:30:05.050 and when this paper was done, this was not an easy task. 00:30:05.050 --> 00:30:08.890 OK, now because of molecular biology where you can get large 00:30:08.890 --> 00:30:11.860 amounts of protein, it has become much more of an easy 00:30:11.860 --> 00:30:14.530 task-- you can get a large amount of protein-- 00:30:14.530 --> 00:30:17.080 you want to turn to the pre-steady state. 00:30:17.080 --> 00:30:18.790 So what I want to do very briefly 00:30:18.790 --> 00:30:22.060 is discuss the pre-steady state. 00:30:22.060 --> 00:30:24.090 I asked you to think about-- 00:30:24.090 --> 00:30:25.550 I asked you draw this out. 00:30:25.550 --> 00:30:29.020 This is one of the talking points in the questions 00:30:29.020 --> 00:30:29.960 I handed out. 00:30:29.960 --> 00:30:34.220 But in the steady state, we're over here. 00:30:34.220 --> 00:30:37.330 And the pre-steady state is before we 00:30:37.330 --> 00:30:38.622 get to the steady state. 00:30:38.622 --> 00:30:40.080 And does anybody have any idea what 00:30:40.080 --> 00:30:43.900 timescale you are on in that region of the curve? 00:30:47.410 --> 00:30:48.222 Is it hours? 00:30:48.222 --> 00:30:49.180 AUDIENCE: Milliseconds? 00:30:49.180 --> 00:30:50.888 JOANNE STUBBE: Yes, so it's milliseconds. 00:30:50.888 --> 00:30:55.420 So, fortunately, this didn't necessarily have to be true-- 00:30:55.420 --> 00:30:58.790 most enzymatic reactions occur. 00:30:58.790 --> 00:31:02.950 the catalysis occurs in that time regime, or maybe 0.1 00:31:02.950 --> 00:31:05.050 milliseconds to milliseconds, allowing 00:31:05.050 --> 00:31:08.920 you to be able to use this method in an effort to try 00:31:08.920 --> 00:31:10.300 to understand what these-- 00:31:10.300 --> 00:31:12.110 evaluate what the rate constants are. 00:31:12.110 --> 00:31:16.510 And when you look at the table in the Rodnina paper, 00:31:16.510 --> 00:31:19.330 we're going to talk about where all those three constants came 00:31:19.330 --> 00:31:20.420 from, OK? 00:31:20.420 --> 00:31:22.430 Are they good or are they not good? 00:31:22.430 --> 00:31:25.120 But that's what you'd like to know for every system 00:31:25.120 --> 00:31:28.180 to really understand the question of fidelity, 00:31:28.180 --> 00:31:33.280 whether it's translation fidelity, DNA 00:31:33.280 --> 00:31:36.700 fidelity in replication, transcriptional fidelity. 00:31:36.700 --> 00:31:38.950 And you'll even see in Liz's section 00:31:38.950 --> 00:31:42.800 on polyketide syntases, which make natural products, 00:31:42.800 --> 00:31:46.130 you also have fidelity issues almost everywhere. 00:31:46.130 --> 00:31:48.280 So you'd like to be able to evaluate these things. 00:31:48.280 --> 00:31:50.446 And you can get a handle on this if you're a chemist 00:31:50.446 --> 00:31:53.680 and really care about the molecular details using 00:31:53.680 --> 00:31:54.710 potentially kinetics. 00:31:54.710 --> 00:31:58.630 So this is why kinetics is one of the first places 00:31:58.630 --> 00:32:01.870 that you actually start to think about what's 00:32:01.870 --> 00:32:03.520 going on in any reaction. 00:32:03.520 --> 00:32:07.930 OK, so let's say a few things about pre-steady state. 00:32:07.930 --> 00:32:10.550 I'm going to ask you a few questions, if I can remember 00:32:10.550 --> 00:32:12.120 what I'm going to ask you. 00:32:12.120 --> 00:32:18.360 OK, so OK, so let's suppose in this simple case, which I just 00:32:18.360 --> 00:32:26.250 covered up, this step is rate limiting, OK? 00:32:26.250 --> 00:32:27.600 So what is that step? 00:32:30.222 --> 00:32:32.980 Do you think it's common that a step like this-- 00:32:32.980 --> 00:32:34.270 so we have e plus s. 00:32:34.270 --> 00:32:36.760 And eventually, the enzyme gets recycled. 00:32:36.760 --> 00:32:38.780 I'm saying this is the rate-limiting step. 00:32:38.780 --> 00:32:42.000 Where is the chemical steps? 00:32:42.000 --> 00:32:44.632 Where are the chemical steps in this reaction? 00:32:44.632 --> 00:32:45.955 AUDIENCE: 2, 2. 00:32:45.955 --> 00:32:47.200 JOANNE STUBBE: Yeah, so k2. 00:32:47.200 --> 00:32:50.830 What are these steps over here, k1, and k minus 1, and k3? 00:32:50.830 --> 00:32:52.985 AUDIENCE: It's like association of the-- 00:32:52.985 --> 00:32:55.900 JOANNE STUBBE: Yeah, so the physical steps, OK? 00:32:55.900 --> 00:32:57.606 So as a chemist, and you're trying 00:32:57.606 --> 00:32:59.230 to understand what's going on, isn't it 00:32:59.230 --> 00:33:02.795 a problem if the rate limiting step is physical? 00:33:02.795 --> 00:33:05.440 It masks all the chemistry, OK? 00:33:05.440 --> 00:33:07.810 So what you see in this paper is they 00:33:07.810 --> 00:33:10.720 have to figure out clever ways to get around 00:33:10.720 --> 00:33:11.690 these kinds of issues. 00:33:11.690 --> 00:33:13.190 And you see that over and over again 00:33:13.190 --> 00:33:14.648 when you're studying enzyme systems 00:33:14.648 --> 00:33:18.680 because enzymes have have had billions of years to evolve. 00:33:18.680 --> 00:33:20.220 They are evolved. 00:33:20.220 --> 00:33:22.540 Their catalytic transformations are amazing. 00:33:22.540 --> 00:33:24.692 They go 10 to the 15th per second, right? 00:33:24.692 --> 00:33:25.900 That's totally mind boggling. 00:33:25.900 --> 00:33:28.390 Chemists can't come close. 00:33:28.390 --> 00:33:33.340 And so what happens then issued a limited by physical steps. 00:33:33.340 --> 00:33:36.250 So what we want to do is try and then 00:33:36.250 --> 00:33:39.310 look at the first part of this transformation. 00:33:39.310 --> 00:33:40.810 And basically, what we're then doing 00:33:40.810 --> 00:33:43.390 is using the enzyme sort of as a reagent. 00:33:43.390 --> 00:33:45.720 There are numbers of ways you can do this 00:33:45.720 --> 00:33:48.460 so that you can have a way of not looking 00:33:48.460 --> 00:33:50.410 at multiple turnovers because you can only 00:33:50.410 --> 00:33:53.920 look at one turnover if this is blocked 00:33:53.920 --> 00:33:55.870 in terms of product release. 00:33:55.870 --> 00:34:01.150 OK, so I think this product release 00:34:01.150 --> 00:34:03.600 is quite often the rate-limiting step 00:34:03.600 --> 00:34:05.440 in biological transformations. 00:34:05.440 --> 00:34:08.920 And what have you seen from reading the Rodnina paper? 00:34:08.920 --> 00:34:12.179 Have you seen conformational changes 00:34:12.179 --> 00:34:16.105 in thinking about the kinetic model we had up there before, 00:34:16.105 --> 00:34:19.396 and Liz had on the slide? 00:34:19.396 --> 00:34:23.444 Have you seen conformational changes? 00:34:23.444 --> 00:34:25.979 Is that part of the mechanism? 00:34:25.979 --> 00:34:27.270 Are they fast or are they slow? 00:34:31.420 --> 00:34:34.030 AUDIENCE: Wasn't that part of their reasoning 00:34:34.030 --> 00:34:38.880 that the difference between if you have a cognitive 00:34:38.880 --> 00:34:41.750 versus if you have a mismatched? 00:34:41.750 --> 00:34:45.146 That influences the rate of the reaction 00:34:45.146 --> 00:34:48.790 based on how it can affect the conformational change? 00:34:48.790 --> 00:34:51.980 JOANNE STUBBE: Wait, so that's exactly what's going to happen. 00:34:51.980 --> 00:34:53.239 So there are multiple places. 00:34:53.239 --> 00:34:54.613 How are you going to discriminate 00:34:54.613 --> 00:34:56.267 between two amino acids? 00:34:56.267 --> 00:34:58.100 Cognate and near cognate, whatever they are, 00:34:58.100 --> 00:35:01.190 will get to the data. 00:35:01.190 --> 00:35:03.180 The question is, how do you do that? 00:35:03.180 --> 00:35:05.240 And one of the steps is-- we talked 00:35:05.240 --> 00:35:07.690 about today GTP hydrolysis. 00:35:07.690 --> 00:35:13.220 But GTP hydrolysis is limited by a conformational change. 00:35:13.220 --> 00:35:17.240 And then once that go, the hydrolysis is very fast. 00:35:17.240 --> 00:35:21.050 And so it looks like the rate constant for GTP hydrolysis is 00:35:21.050 --> 00:35:24.080 the same as the rate constant for the conformational change. 00:35:24.080 --> 00:35:25.850 Where else have we seen a confirmation 00:35:25.850 --> 00:35:28.630 change the accommodation? 00:35:28.630 --> 00:35:29.396 AUDIENCE: Peptide. 00:35:29.396 --> 00:35:31.271 JOANNE STUBBE: Yeah, so peptide confirmation. 00:35:31.271 --> 00:35:33.580 This is shown here is this little cartoon 00:35:33.580 --> 00:35:36.400 where this red ball is the amino acid. 00:35:36.400 --> 00:35:40.640 It needs to reorient itself so it can form a peptide bond. 00:35:40.640 --> 00:35:45.910 So confirmation changes are all over the place in entomology. 00:35:45.910 --> 00:35:48.670 And if you look at the ribosome, do 00:35:48.670 --> 00:35:51.340 you think it's easy to tell with those conformational changes 00:35:51.340 --> 00:35:55.078 are from a molecular point of view? 00:35:55.078 --> 00:35:58.800 What do you think? 00:35:58.800 --> 00:36:00.950 Do you think it's easy or hard? 00:36:06.105 --> 00:36:06.730 AUDIENCE: Hard. 00:36:06.730 --> 00:36:07.850 JOANNE STUBBE: Very hard. 00:36:07.850 --> 00:36:10.220 OK, so here-- one of the most amazing things 00:36:10.220 --> 00:36:13.160 about the ribosome-- you've got to think this is amazing. 00:36:13.160 --> 00:36:16.820 You have this called the anti-codon loop way down here 00:36:16.820 --> 00:36:17.690 on the [INAUDIBLE]. 00:36:17.690 --> 00:36:21.160 And the GTPase is 80 angstroms away. 00:36:21.160 --> 00:36:24.170 And somehow, twiddling-- you saw this in class today-- 00:36:24.170 --> 00:36:26.920 these guys to form the right confirmation 00:36:26.920 --> 00:36:30.470 is transferred 80 Angstroms. 00:36:30.470 --> 00:36:33.722 And that triggers the reaction, rapid and irreversible. 00:36:33.722 --> 00:36:35.180 And the reaction goes to the right. 00:36:35.180 --> 00:36:39.200 You see this over and over and over again in these machines. 00:36:39.200 --> 00:36:42.650 OK, so this is a really important observation. 00:36:42.650 --> 00:36:44.520 How does that happen? 00:36:44.520 --> 00:36:46.370 Well, I think what's mindboggling 00:36:46.370 --> 00:36:48.500 about the ribosome-- again if you Google 00:36:48.500 --> 00:36:50.930 ribosome and elongation, you'll see 00:36:50.930 --> 00:36:53.900 we have another 150 papers published where people 00:36:53.900 --> 00:36:56.660 are trying to sort out-- because we have cryoem structures, 00:36:56.660 --> 00:37:01.760 we have stagnant crystallographic structures, 00:37:01.760 --> 00:37:03.650 we have single molecule stuff now. 00:37:03.650 --> 00:37:06.350 On top of all this model we have from Rodnina, 00:37:06.350 --> 00:37:08.360 people are trying to sort all those out 00:37:08.360 --> 00:37:11.450 because they care about how it works in some detail. 00:37:11.450 --> 00:37:14.540 So who ever would have thought we could get to the stage 00:37:14.540 --> 00:37:15.660 where we-- 00:37:15.660 --> 00:37:18.380 you've seen the pictures you saw in class today. 00:37:18.380 --> 00:37:20.730 Those pictures-- when I was your age, 00:37:20.730 --> 00:37:23.280 do you know how many structures there were? 00:37:23.280 --> 00:37:25.040 Maybe three. 00:37:25.040 --> 00:37:26.480 OK, we had hemoglobin. 00:37:26.480 --> 00:37:27.570 We had chymotrypsin. 00:37:27.570 --> 00:37:29.100 There were no structures. 00:37:29.100 --> 00:37:30.260 And why was that true? 00:37:30.260 --> 00:37:32.510 Because we had no molecular biology. 00:37:32.510 --> 00:37:34.430 So I used to spend three-- 00:37:34.430 --> 00:37:35.097 I'm digressing. 00:37:35.097 --> 00:37:36.430 This happens to me all the time. 00:37:36.430 --> 00:37:37.790 You're going to hate me for this. 00:37:37.790 --> 00:37:39.248 I'm going to get hammered for this. 00:37:39.248 --> 00:37:43.370 But I used to spend three months in the cold room isolating 00:37:43.370 --> 00:37:45.770 a microgram or protein, OK? 00:37:45.770 --> 00:37:48.290 And then molecular biology came in. 00:37:48.290 --> 00:37:50.040 And it's still not easy. 00:37:50.040 --> 00:37:51.890 And Liz will tell you what the issues are 00:37:51.890 --> 00:37:53.210 with purification of protein. 00:37:53.210 --> 00:37:56.150 But you can get grams of protein now in a day, OK? 00:37:56.150 --> 00:37:57.470 So there's been a revolution. 00:37:57.470 --> 00:38:02.000 And that allowed these crystallographic-- 00:38:02.000 --> 00:38:04.400 a pure material that crystallized more readily. 00:38:04.400 --> 00:38:07.610 And then the technology on top of that has really 00:38:07.610 --> 00:38:10.514 revolutionized what you can do. 00:38:10.514 --> 00:38:11.930 I think it's a very exciting time. 00:38:11.930 --> 00:38:14.360 And I think any of you who want to be biochemists, 00:38:14.360 --> 00:38:17.220 or are thinking about drug design, 00:38:17.220 --> 00:38:19.590 you really need to learn how to look at structures. 00:38:19.590 --> 00:38:20.900 So that was the first module. 00:38:20.900 --> 00:38:22.430 It takes a lot of practice. 00:38:22.430 --> 00:38:24.650 You need to figure that all out. 00:38:24.650 --> 00:38:28.060 OK, so pre-steady state-- so we're going 00:38:28.060 --> 00:38:29.885 to look at pre-steady state. 00:38:29.885 --> 00:38:38.180 And the goal is to evaluate the individual rate constants. 00:38:41.200 --> 00:38:42.320 OK, so that's the goal. 00:38:42.320 --> 00:38:47.250 And you may or may not be able to achieve this goal. 00:38:47.250 --> 00:38:53.210 But this happens, we just said, on the millisecond timescale. 00:38:53.210 --> 00:38:55.760 And so one of the questions-- and we're 00:38:55.760 --> 00:38:57.500 doing this under single turnover. 00:39:01.260 --> 00:39:04.295 OK, so let's look at a simple-- 00:39:04.295 --> 00:39:06.420 and we've just talked about it in the steady state. 00:39:06.420 --> 00:39:07.860 The concentration of the substrate 00:39:07.860 --> 00:39:09.984 has to be much, much greater than the concentration 00:39:09.984 --> 00:39:10.650 of the enzyme. 00:39:10.650 --> 00:39:12.930 And the enzyme concentrations are really low. 00:39:12.930 --> 00:39:19.020 So let's say we have an enzyme concentration of 0.01 00:39:19.020 --> 00:39:21.870 micromolar, OK? 00:39:21.870 --> 00:39:23.610 So that's our enzyme concentration. 00:39:23.610 --> 00:39:25.193 And that would be typical if you would 00:39:25.193 --> 00:39:28.780 be using in a steady state assay if you have done those. 00:39:28.780 --> 00:39:32.160 And let's say that we're going to monitor this reaction 00:39:32.160 --> 00:39:35.351 by some kind of absorption change, a unique absorption 00:39:35.351 --> 00:39:35.850 change. 00:39:35.850 --> 00:39:40.750 So we're looking at absorption at some wavelength, OK? 00:39:40.750 --> 00:39:42.960 And let's say the extinction coefficient for this 00:39:42.960 --> 00:39:47.190 is 10 to the 4 per molar per centimeter. 00:39:47.190 --> 00:39:50.070 It would be ATP or coA. 00:39:50.070 --> 00:39:52.440 Then you can ask yourself the question, 00:39:52.440 --> 00:39:54.970 under these conditions, the change in absorption 00:39:54.970 --> 00:39:56.940 at whatever this wavelength is, is 00:39:56.940 --> 00:40:00.750 equal to the path length of light in centimeters times 10 00:40:00.750 --> 00:40:08.830 to the minus 8th molar times 10 to the fourth molar 00:40:08.830 --> 00:40:10.986 per centimeter. 00:40:10.986 --> 00:40:13.120 OK, so what would your change in absorption 00:40:13.120 --> 00:40:16.654 be if you were measuring this in a single turnover? 00:40:16.654 --> 00:40:21.690 It would be really, really small, 0.0001. 00:40:21.690 --> 00:40:23.520 Can you measure that? 00:40:23.520 --> 00:40:26.790 Maybe you could measure this if you took hundreds of samples 00:40:26.790 --> 00:40:28.930 and you did a statistical analysis on it. 00:40:28.930 --> 00:40:30.450 But it's really low. 00:40:30.450 --> 00:40:33.510 So what do you want to do then to do pretty steady state? 00:40:33.510 --> 00:40:36.800 What's the thing to change so that you 00:40:36.800 --> 00:40:38.490 will be able to see something? 00:40:38.490 --> 00:40:39.410 AUDIENCE: [INAUDIBLE]. 00:40:39.410 --> 00:40:43.110 JOANNE STUBBE: Yeah, so you increase. 00:40:43.110 --> 00:40:45.650 So when you have this, and you can't see something-- 00:40:45.650 --> 00:40:48.422 and, obviously, it depends on what this extinction 00:40:48.422 --> 00:40:50.630 coefficient is-- but this is a pretty high extinction 00:40:50.630 --> 00:40:52.480 coefficient. 00:40:52.480 --> 00:40:58.450 So what you do is you increase the concentration of enzyme. 00:40:58.450 --> 00:41:03.315 And if we increase it, say, 1,000 fold, then then 00:41:03.315 --> 00:41:05.670 so we're now at 10 to the minus 5. 00:41:05.670 --> 00:41:08.790 Then now what is the change in absorption? 00:41:08.790 --> 00:41:10.890 The change in absorption is 0.1, which 00:41:10.890 --> 00:41:13.920 you can measure fairly easily in any kind 00:41:13.920 --> 00:41:16.230 of current instrumentation. 00:41:16.230 --> 00:41:19.420 So the thing is you have to be able to see. 00:41:19.420 --> 00:41:22.080 So the key thing with pre-steady state, 00:41:22.080 --> 00:41:25.310 and the reason you need to have large amounts of enzyme, 00:41:25.310 --> 00:41:28.200 is you need to be able to see what you're monitoring. 00:41:28.200 --> 00:41:29.970 So it's all about sensitivity. 00:41:34.490 --> 00:41:37.290 You need to see. 00:41:37.290 --> 00:41:42.920 And this usually implies increasing the concentration 00:41:42.920 --> 00:41:43.860 of the enzyme. 00:41:43.860 --> 00:41:46.730 OK, so what's the problem if you increase the concentration 00:41:46.730 --> 00:41:47.380 of the enzyme? 00:41:49.950 --> 00:41:54.330 Say we normally are at 0.01 micromolar steady state. 00:41:54.330 --> 00:41:57.970 We now are at 1,000 times higher. 00:41:57.970 --> 00:42:03.946 What's going to happen that makes the analysis complicated? 00:42:08.230 --> 00:42:10.390 If you increase the concentration of the enzyme, 00:42:10.390 --> 00:42:11.434 what does that do? 00:42:11.434 --> 00:42:13.100 AUDIENCE: You're going to burn through-- 00:42:13.100 --> 00:42:14.307 [INTERPOSING VOICES] 00:42:14.307 --> 00:42:15.890 JOANNE STUBBE: You're going to-- yeah, 00:42:15.890 --> 00:42:17.690 it increases the rate of the reaction 00:42:17.690 --> 00:42:19.430 because the rate of the reaction is 00:42:19.430 --> 00:42:22.070 proportional to the concentration of your catalyst. 00:42:22.070 --> 00:42:23.720 If you don't remember anything else out 00:42:23.720 --> 00:42:26.660 of this course, or anything in chemistry, 00:42:26.660 --> 00:42:30.380 that's pretty important no matter what area of chemistry 00:42:30.380 --> 00:42:31.400 you're in. 00:42:31.400 --> 00:42:34.850 So now what happens is the reaction 00:42:34.850 --> 00:42:38.960 is going like a bat out of hell instead of pipetting by hand. 00:42:38.960 --> 00:42:41.030 By the time you pipetted and put this 00:42:41.030 --> 00:42:44.030 into however you're observing it in the spectrophotometer, 00:42:44.030 --> 00:42:46.290 reaction's over, OK? 00:42:46.290 --> 00:42:48.240 So that's what the issue is, OK? 00:42:48.240 --> 00:42:51.645 So the sensitivity is key. 00:42:51.645 --> 00:42:53.770 And then the second thing you need to think about-- 00:42:53.770 --> 00:42:55.719 so sensitivity is one thing. 00:42:55.719 --> 00:42:57.510 And the other thing you need to think about 00:42:57.510 --> 00:43:02.460 is, what are the limitations of this method? 00:43:02.460 --> 00:43:04.770 How fast can the rate come-- 00:43:04.770 --> 00:43:06.810 on the millisecond timescale, what 00:43:06.810 --> 00:43:09.780 are the limitations in terms of the rate constants 00:43:09.780 --> 00:43:11.710 you can actually measure? 00:43:11.710 --> 00:43:13.740 So when you're looking at these reactions, 00:43:13.740 --> 00:43:18.080 you're looking at, in general, first order reactions. 00:43:18.080 --> 00:43:20.700 So all of these take place on the enzyme. 00:43:20.700 --> 00:43:23.410 So everything is stuck on the enzyme. 00:43:23.410 --> 00:43:25.030 So it's all first order. 00:43:25.030 --> 00:43:28.800 So the half life of the reaction is, if you go back 00:43:28.800 --> 00:43:30.730 and you look at your introductory kinetics, 00:43:30.730 --> 00:43:35.520 is 0.693 divided by k observed. 00:43:35.520 --> 00:43:42.670 And so if you had, say, a rate constant of 500 per second, 00:43:42.670 --> 00:43:47.734 then that gives you a half life of 1.5 milliseconds, OK? 00:43:47.734 --> 00:43:50.150 So that means you have to be able to make your measurement 00:43:50.150 --> 00:43:52.230 faster than that, OK? 00:43:52.230 --> 00:43:54.380 So the instrumentation we're going to be using 00:43:54.380 --> 00:43:55.890 can't do that. 00:43:55.890 --> 00:43:58.330 So the instrumentation we're doing-- 00:43:58.330 --> 00:44:01.910 so this would give you a half life if you calculate this. 00:44:01.910 --> 00:44:04.740 I don't even remember what the number is. 00:44:04.740 --> 00:44:10.610 But the dead time of the instruments 00:44:10.610 --> 00:44:13.490 that you would be using to make pre-steady state kinetics 00:44:13.490 --> 00:44:16.940 is approximately 2 milliseconds. 00:44:16.940 --> 00:44:20.650 So by the time you could stop looking 00:44:20.650 --> 00:44:23.710 at the reaction in some form, you know more than 50% 00:44:23.710 --> 00:44:25.900 of the reaction is gone, OK? 00:44:25.900 --> 00:44:30.310 So the rate constant then limits also what you can measure. 00:44:30.310 --> 00:44:33.580 So we asked this question before-- how could you 00:44:33.580 --> 00:44:35.900 modify this rate constant? 00:44:35.900 --> 00:44:37.690 What could you actually do? 00:44:41.000 --> 00:44:42.590 How could you make it so you might 00:44:42.590 --> 00:44:45.290 be able to say your rate consent was 500 per second-- 00:44:45.290 --> 00:44:47.240 you missed more than half your reaction. 00:44:47.240 --> 00:44:50.120 What could you potentially do so that you could 00:44:50.120 --> 00:44:51.854 monitor more of the reaction? 00:44:51.854 --> 00:44:53.645 What's the parameter that you would change? 00:44:58.330 --> 00:44:59.300 Kinetics. 00:44:59.300 --> 00:45:00.210 Think about kinetics. 00:45:00.210 --> 00:45:02.588 What do you always control in kinetics? 00:45:02.588 --> 00:45:04.004 AUDIENCE: Substrate concentration. 00:45:04.004 --> 00:45:05.530 JOANNE STUBBE: OK, you can control 00:45:05.530 --> 00:45:07.210 substrate concentration, but that's not 00:45:07.210 --> 00:45:08.670 the one I'm looking for. 00:45:08.670 --> 00:45:09.610 AUDIENCE: Temperature? 00:45:09.610 --> 00:45:10.460 JOANNE STUBBE: Temperature. 00:45:10.460 --> 00:45:10.959 Yeah. 00:45:10.959 --> 00:45:15.370 So in our body, we're at 37 degrees. 00:45:15.370 --> 00:45:18.400 That really is where you want to be making 00:45:18.400 --> 00:45:20.290 all of your measurements. 00:45:20.290 --> 00:45:22.270 In reality, many of the measurements 00:45:22.270 --> 00:45:24.050 are right on the edge. 00:45:24.050 --> 00:45:26.210 And so if you read the papers carefully, 00:45:26.210 --> 00:45:29.260 you'll see that people do lower the temperature, 00:45:29.260 --> 00:45:31.150 and that the rate of the reaction 00:45:31.150 --> 00:45:34.309 is related to the temperature. 00:45:34.309 --> 00:45:36.350 What's the problem with lowering the temperature? 00:45:36.350 --> 00:45:38.100 These are all things just you got to think 00:45:38.100 --> 00:45:39.420 about in the back of your mind. 00:45:39.420 --> 00:45:42.040 They're all playoffs in terms of how bad you 00:45:42.040 --> 00:45:45.130 want your experimental data and what the issues are 00:45:45.130 --> 00:45:47.840 with interpretation of data. 00:45:47.840 --> 00:45:48.370 Yeah? 00:45:48.370 --> 00:45:48.870 Rebecca. 00:45:48.870 --> 00:45:50.058 AUDIENCE: It makes it difficult to compare 00:45:50.058 --> 00:45:50.654 the different values. 00:45:50.654 --> 00:45:52.211 And you might not know exactly what 00:45:52.211 --> 00:45:54.086 the relationship between temperature and rate 00:45:54.086 --> 00:45:55.515 is, like if scales linearly. 00:45:55.515 --> 00:45:56.530 JOANNE STUBBE: OK, so that's true. 00:45:56.530 --> 00:45:58.321 You could have a huge conformational change 00:45:58.321 --> 00:46:01.840 that doesn't have erroneous behavior. 00:46:01.840 --> 00:46:04.210 I think quite frequently, most enzymes, they're 00:46:04.210 --> 00:46:05.960 designed to work at 37 degrees. 00:46:05.960 --> 00:46:08.822 And when you start cooling them down, they do weird things. 00:46:08.822 --> 00:46:10.280 So you could make the measurements, 00:46:10.280 --> 00:46:11.660 but then you have this issue-- 00:46:11.660 --> 00:46:13.285 I think, which is what you were saying, 00:46:13.285 --> 00:46:15.010 of how do you extrapolate that? 00:46:15.010 --> 00:46:17.272 So a lot of times you will change the temperature 00:46:17.272 --> 00:46:19.730 because that's the only way you could make the measurement. 00:46:19.730 --> 00:46:21.700 But the caveat is, like with everything, 00:46:21.700 --> 00:46:25.480 that you need to think about what the consequences of that 00:46:25.480 --> 00:46:26.430 actually are. 00:46:26.430 --> 00:46:32.440 OK, so the methods that we're going to be using Liz already 00:46:32.440 --> 00:46:38.335 introduced you to in class, not today, but the previous time. 00:46:38.335 --> 00:46:41.200 And so what you want to do, since you can't pipette 00:46:41.200 --> 00:46:44.470 on the millisecond time scale by hand, 00:46:44.470 --> 00:46:46.600 you want to have an instrument that 00:46:46.600 --> 00:46:53.380 allows you to control the rate of reaction 00:46:53.380 --> 00:46:58.070 by-- you put two different things in your syringes. 00:46:58.070 --> 00:46:59.620 And then you have an instrument-- 00:46:59.620 --> 00:47:03.770 push the two syringes into a chamber where they're mixed. 00:47:03.770 --> 00:47:05.830 Do you know what the rate-limiting step 00:47:05.830 --> 00:47:07.440 in this process is? 00:47:07.440 --> 00:47:09.580 It's the mixing process, OK? 00:47:09.580 --> 00:47:13.360 So the mixing processes is 2-millisecond dead time. 00:47:13.360 --> 00:47:16.810 I don't know if any of you have ever mixed something viscus 00:47:16.810 --> 00:47:18.250 with something not so viscus? 00:47:18.250 --> 00:47:20.706 What do you see? 00:47:20.706 --> 00:47:24.640 Have you ever made up a solution of glycerol? 00:47:24.640 --> 00:47:26.580 No? 00:47:26.580 --> 00:47:29.470 They probably give you all this in a kit nowadays. 00:47:29.470 --> 00:47:31.320 You don't have to make up your solutions 00:47:31.320 --> 00:47:34.730 of glycerol aluminum anymore. 00:47:34.730 --> 00:47:36.730 So this goes back to experimental design. 00:47:36.730 --> 00:47:39.410 And I'm not here to teach you how to do experimental design. 00:47:39.410 --> 00:47:41.925 But if you had very high concentration of the enzyme-- 00:47:41.925 --> 00:47:44.050 because we need a lot to be able to see something-- 00:47:44.050 --> 00:47:46.080 and you're mixing it against substrate-- 00:47:46.080 --> 00:47:49.170 you have something very viscous and something not viscous-- 00:47:49.170 --> 00:47:52.840 and when you mix them it takes a lot longer 00:47:52.840 --> 00:47:56.140 to remove all the lines from the mixing process. 00:47:56.140 --> 00:47:59.950 So experimental design, you really 00:47:59.950 --> 00:48:01.780 need to do some thinking about that. 00:48:01.780 --> 00:48:05.980 Once it gets into the mixer, the liquid in the mixer 00:48:05.980 --> 00:48:08.403 pushes a third syringe back. 00:48:08.403 --> 00:48:11.590 It fills the syringe up with liquid. 00:48:11.590 --> 00:48:14.860 It hits some kind of a stop position, which 00:48:14.860 --> 00:48:16.865 then triggers detection, OK? 00:48:16.865 --> 00:48:18.240 So that's what you're looking at. 00:48:18.240 --> 00:48:22.640 And the beauty of this method is it's continuous. 00:48:22.640 --> 00:48:26.080 And so what do you have to do to be able to look at this? 00:48:26.080 --> 00:48:29.320 What did they do in the case of the Rodnina paper? 00:48:29.320 --> 00:48:32.980 What kind of method did they use? 00:48:32.980 --> 00:48:34.520 Did you think about that? 00:48:34.520 --> 00:48:36.440 They described it, but you might not 00:48:36.440 --> 00:48:39.780 have thought about it in terms of experimental design. 00:48:39.780 --> 00:48:41.287 How did they monitor their reaction, 00:48:41.287 --> 00:48:42.245 one of their reactions? 00:48:42.245 --> 00:48:44.340 AUDIENCE: [INAUDIBLE]. 00:48:44.340 --> 00:48:46.340 JOANNE STUBBE: Yeah, so they are going 00:48:46.340 --> 00:48:48.550 to be able to somehow tag-- 00:48:48.550 --> 00:48:51.220 and this is a key thing, is how do you tag something 00:48:51.220 --> 00:48:52.750 in the right place so you can see 00:48:52.750 --> 00:48:54.130 a unique fluorescent change? 00:48:54.130 --> 00:48:55.990 That's not so easy, OK? 00:48:55.990 --> 00:48:57.610 So you mix this. 00:48:57.610 --> 00:48:59.920 You can monitor this continuously 00:48:59.920 --> 00:49:01.210 by change in fluorescence. 00:49:01.210 --> 00:49:05.620 If you had something that has a visible absorption, 00:49:05.620 --> 00:49:08.785 could you use that? 00:49:08.785 --> 00:49:10.620 What would limit that? 00:49:10.620 --> 00:49:14.670 Say, if you looked at tRNA synthetases 00:49:14.670 --> 00:49:17.670 that you talked about in class two times ago, 00:49:17.670 --> 00:49:22.140 where you were looking at ATP that isolates the amino acid 00:49:22.140 --> 00:49:24.870 to form the adenylate, which then reacts with the tRNA, 00:49:24.870 --> 00:49:25.950 could you use-- 00:49:25.950 --> 00:49:28.170 ATP as an absorption at 260. 00:49:28.170 --> 00:49:32.490 Could you use that absorption change? 00:49:32.490 --> 00:49:35.640 Do you remember what that equation is? 00:49:35.640 --> 00:49:38.760 Do you remember installation of amino acid? 00:49:38.760 --> 00:49:41.677 You're going to see this again in polyketide syntases. 00:49:41.677 --> 00:49:43.260 It's used quite frequently in biology. 00:49:47.180 --> 00:49:49.360 Nobody has any idea? 00:49:49.360 --> 00:49:51.970 Nebraska, how about you? 00:49:51.970 --> 00:49:57.350 OK, so here we have amino acid plus ATP. 00:49:57.350 --> 00:49:58.310 I'm digressing. 00:49:58.310 --> 00:50:00.010 But if you learn this part, you've 00:50:00.010 --> 00:50:02.410 learned something out of all of this, 00:50:02.410 --> 00:50:04.570 that forms the acyl adenylate. 00:50:08.728 --> 00:50:11.625 OK, how did they monitor this reaction? 00:50:11.625 --> 00:50:14.884 You discussed this in class. 00:50:14.884 --> 00:50:16.300 How do they monitor this reaction? 00:50:18.905 --> 00:50:19.840 AUDIENCE: [INAUDIBLE]. 00:50:19.840 --> 00:50:21.465 JOANNE STUBBE: You need to talk louder. 00:50:21.465 --> 00:50:22.674 You need to be assertive, OK? 00:50:22.674 --> 00:50:23.589 AUDIENCE: [INAUDIBLE]. 00:50:23.589 --> 00:50:24.442 JOANNE STUBBE: Yeah. 00:50:24.442 --> 00:50:26.650 So we're going to talk about radioactivity next time. 00:50:26.650 --> 00:50:28.191 This will be one of the methods we're 00:50:28.191 --> 00:50:30.700 going to be introduced to. 00:50:30.700 --> 00:50:34.650 Why couldn't they use ATP? 00:50:34.650 --> 00:50:37.150 AUDIENCE: The absorbent's different between [INAUDIBLE].. 00:50:37.150 --> 00:50:38.590 JOANNE STUBBE: Yeah, they're the same. 00:50:38.590 --> 00:50:39.089 Yeah. 00:50:39.089 --> 00:50:42.010 So you have to have a difference in absorption 00:50:42.010 --> 00:50:43.930 to be able to measure the visible. 00:50:43.930 --> 00:50:48.190 So the total absorption is due to the adenosine moiety which 00:50:48.190 --> 00:50:49.720 is the same in both molecules. 00:50:49.720 --> 00:50:52.090 OK, so you can't do that, OK? 00:50:52.090 --> 00:50:53.170 So that's one. 00:50:53.170 --> 00:50:56.620 And then let me just do one more thing, and then we'll quit. 00:50:56.620 --> 00:50:59.770 I still have another minute according to my watch. 00:50:59.770 --> 00:51:03.100 OK, so the second method, which they also 00:51:03.100 --> 00:51:07.150 used in the Rodnina paper is rapid chemical quench, OK? 00:51:07.150 --> 00:51:08.890 So, again, you have two things. 00:51:08.890 --> 00:51:10.150 You mix them. 00:51:10.150 --> 00:51:13.210 There's some plunger that allows the mixing. 00:51:13.210 --> 00:51:16.120 And then this is a discontinuous method. 00:51:16.120 --> 00:51:18.370 So what happens is you mix. 00:51:18.370 --> 00:51:21.650 And then you have to stop the reaction, OK? 00:51:21.650 --> 00:51:24.850 So you have a third syringe where you mix in something 00:51:24.850 --> 00:51:27.102 to stop the reaction. 00:51:27.102 --> 00:51:29.560 And then you have to analyze what comes out the other side. 00:51:29.560 --> 00:51:32.470 And this is where they're going to use radioactivity. 00:51:32.470 --> 00:51:34.750 And so this is rapid chemical quench. 00:51:37.425 --> 00:51:42.390 And how can you monitor a rapid chemical quench experiment? 00:51:42.390 --> 00:51:45.280 What's the best way to stop the reaction? 00:51:45.280 --> 00:51:47.130 What did they do in this paper? 00:51:47.130 --> 00:51:48.930 How else could you stop the reaction? 00:51:48.930 --> 00:51:50.100 Anybody got any ideas? 00:51:56.409 --> 00:51:58.200 So what what's the first criteria if you're 00:51:58.200 --> 00:51:59.324 going to stop the reaction? 00:51:59.324 --> 00:52:03.440 What does it have to be able to do? 00:52:03.440 --> 00:52:05.160 You just can't throw in anything, right? 00:52:05.160 --> 00:52:08.721 What is the key criteria for successful stopping? 00:52:08.721 --> 00:52:10.304 AUDIENCE: Something that will turn off 00:52:10.304 --> 00:52:11.410 the catalytic activity? 00:52:11.410 --> 00:52:12.270 JOANNE STUBBE: Yeah. 00:52:12.270 --> 00:52:14.850 And it has to be able to do it on a millisecond timescale. 00:52:14.850 --> 00:52:17.070 So you need millisecond stopping. 00:52:20.954 --> 00:52:22.140 OK, how could you millisec? 00:52:22.140 --> 00:52:24.140 How could you stop something on the millisecond? 00:52:24.140 --> 00:52:24.980 What would you use? 00:52:24.980 --> 00:52:26.330 Anybody got any ideas? 00:52:26.330 --> 00:52:28.304 So this is not trivial, actually. 00:52:28.304 --> 00:52:29.720 AUDIENCE: You could change the pH? 00:52:29.720 --> 00:52:31.386 JOANNE STUBBE: Yeah, so changing the pH. 00:52:31.386 --> 00:52:33.540 But so you could go acid or base. 00:52:33.540 --> 00:52:35.250 Acid works. 00:52:35.250 --> 00:52:37.110 In general, base doesn't work. 00:52:37.110 --> 00:52:40.460 So if you read the handout that I've given you, it does work. 00:52:40.460 --> 00:52:42.500 But it's much, much, much slower. 00:52:42.500 --> 00:52:43.880 And every base is different. 00:52:43.880 --> 00:52:45.620 Acid works all the time. 00:52:45.620 --> 00:52:47.210 There's another thing that you can 00:52:47.210 --> 00:52:49.440 use that is quite frequently used, 00:52:49.440 --> 00:52:53.630 especially with polymerases that work on nucleic acids. 00:52:53.630 --> 00:52:55.070 And that's EDTA. 00:52:55.070 --> 00:53:01.010 So this is a chelator and EDTA chelates the metal, which 00:53:01.010 --> 00:53:03.420 is essential for viability. 00:53:03.420 --> 00:53:05.450 So that also-- the chelation can occur 00:53:05.450 --> 00:53:07.130 in the millisecond timescale. 00:53:07.130 --> 00:53:08.630 So what we're going to do next time, 00:53:08.630 --> 00:53:10.796 I've sort of introduced you to the pre-steady state. 00:53:10.796 --> 00:53:12.090 The next time we'll come in. 00:53:12.090 --> 00:53:14.270 And we're going to look at the actual experiments. 00:53:14.270 --> 00:53:15.560 We'll look at fluorescence. 00:53:15.560 --> 00:53:18.470 We'll look at radioactivity and how you measure radioactivity. 00:53:18.470 --> 00:53:20.150 We're going to look at antibiotics, 00:53:20.150 --> 00:53:21.380 like you talked about today. 00:53:21.380 --> 00:53:25.430 We're going to look at non-hydrolyzable GTP analogs. 00:53:25.430 --> 00:53:26.990 If you look carefully at this paper, 00:53:26.990 --> 00:53:29.540 it's amazing how many methods they used 00:53:29.540 --> 00:53:30.930 to come up with this model. 00:53:30.930 --> 00:53:33.160 And that's one of the take home messages 00:53:33.160 --> 00:53:36.230 that you have to use many, many methods. 00:53:36.230 --> 00:53:39.510 And then you never get an exact solution to your equations. 00:53:39.510 --> 00:53:41.990 It's numerical integration of all the data 00:53:41.990 --> 00:53:46.510 that leads you to the model that they've actually used, OK?