1 00:00:00,500 --> 00:00:03,270 The following content is provided under a Creative 2 00:00:03,270 --> 00:00:04,630 Commons license. 3 00:00:04,630 --> 00:00:07,140 Your support will help MIT OpenCourseWare 4 00:00:07,140 --> 00:00:11,470 continue to offer high quality educational resources for free. 5 00:00:11,470 --> 00:00:14,100 To make a donation, or view additional materials 6 00:00:14,100 --> 00:00:16,980 from hundreds of MIT courses, visit MIT 7 00:00:16,980 --> 00:00:19,000 open courseware at ocw.mit.edu. 8 00:00:24,447 --> 00:00:26,280 JOANNE STUBBE: Recitation 2 and recitation 3 9 00:00:26,280 --> 00:00:27,420 are on the same paper. 10 00:00:27,420 --> 00:00:30,780 You only have to read one paper that Liz has been discussing 11 00:00:30,780 --> 00:00:34,740 in class, the Rodnina paper. 12 00:00:34,740 --> 00:00:39,860 The paper was published in 1999, OK? 13 00:00:39,860 --> 00:00:43,920 And it's still, I would say, a seminal paper. 14 00:00:43,920 --> 00:00:47,460 And what they propose or what you read about their model 15 00:00:47,460 --> 00:00:52,740 is still the working hypothesis in the field. 16 00:00:52,740 --> 00:00:57,660 But if you go and Google the ribosome in elongation, 17 00:00:57,660 --> 00:01:01,020 you will find out that in the last 10 years 18 00:01:01,020 --> 00:01:03,780 there are hundreds of papers now taking 19 00:01:03,780 --> 00:01:09,570 pot shots at this model using modern technological 20 00:01:09,570 --> 00:01:14,700 mechanisms, like single-molecule spectroscopy, Cryo-EM. 21 00:01:14,700 --> 00:01:18,930 So they're flushing things out, but so still the basic model 22 00:01:18,930 --> 00:01:19,480 holds. 23 00:01:19,480 --> 00:01:22,627 So we continue to go through this because, in my opinion, 24 00:01:22,627 --> 00:01:24,960 all the machines that you're going to be talking about-- 25 00:01:24,960 --> 00:01:27,460 and this is part of the course-- 26 00:01:27,460 --> 00:01:31,820 have complex behavior like this with numerous substrates 27 00:01:31,820 --> 00:01:33,460 and many, many steps. 28 00:01:33,460 --> 00:01:37,290 And so hopefully one thing you got out of this paper 29 00:01:37,290 --> 00:01:40,680 is that kinetics are important. 30 00:01:40,680 --> 00:01:44,570 OK, so today what I want to do, I'm going to ask you questions. 31 00:01:44,570 --> 00:01:46,320 I'm going to put some things on the board. 32 00:01:46,320 --> 00:01:48,720 We get you at talking points. 33 00:01:48,720 --> 00:01:50,310 I'm going to ask you some questions. 34 00:01:50,310 --> 00:01:53,250 And then the discussion will continue 35 00:01:53,250 --> 00:01:58,875 into the next recitation on the same exact same topic. 36 00:01:58,875 --> 00:02:00,660 But kinetics are important. 37 00:02:00,660 --> 00:02:03,420 But to do kinetics, what do you have to have? 38 00:02:03,420 --> 00:02:06,400 What's required to do kinetics if you look at this model? 39 00:02:06,400 --> 00:02:10,240 So this is the model out of your paper. 40 00:02:10,240 --> 00:02:12,240 If you want to do kinetics, what do you need? 41 00:02:17,820 --> 00:02:20,600 Not only that, you have to speak loud because I'm deaf anyhow. 42 00:02:20,600 --> 00:02:22,657 What do you need? 43 00:02:22,657 --> 00:02:23,990 AUDIENCE: To do kinetic studies? 44 00:02:23,990 --> 00:02:24,675 JOANNE STUBBE: Yeah, to do kinetic studies. 45 00:02:24,675 --> 00:02:26,425 AUDIENCE: [INAUDIBLE] a detection method 46 00:02:26,425 --> 00:02:26,920 in very controlled conditions. 47 00:02:26,920 --> 00:02:29,409 JOANNE STUBBE: Yeah, so you have to have an assay, OK? 48 00:02:29,409 --> 00:02:30,950 And you'll see that everything you're 49 00:02:30,950 --> 00:02:32,810 doing over the course of the semester 50 00:02:32,810 --> 00:02:35,060 requires development of an assay. 51 00:02:35,060 --> 00:02:38,810 And I would say the more complex you get the more complex 52 00:02:38,810 --> 00:02:39,600 these machines. 53 00:02:39,600 --> 00:02:41,225 And that's what people are studying now 54 00:02:41,225 --> 00:02:46,920 as opposed to if you looked at it Liz's lecture on tRNA 55 00:02:46,920 --> 00:02:49,520 synthetases, you saw a simple reaction, OK? 56 00:02:49,520 --> 00:02:51,990 That assay was developed decades ago. 57 00:02:51,990 --> 00:02:55,290 But when you get into these more complicated machines, 58 00:02:55,290 --> 00:02:59,227 you have to be really pretty creative to develop an assay. 59 00:02:59,227 --> 00:03:00,560 And you need to have substrates. 60 00:03:00,560 --> 00:03:02,510 You need to get them from somewhere. 61 00:03:02,510 --> 00:03:04,770 And then you need to do kinetics. 62 00:03:04,770 --> 00:03:07,730 And so today, what I want to do is 63 00:03:07,730 --> 00:03:12,680 go through the kinetics part of this, asking you questions 64 00:03:12,680 --> 00:03:14,060 as we go along. 65 00:03:14,060 --> 00:03:16,310 And I'm going to start. 66 00:03:16,310 --> 00:03:18,870 So kinetics, in my opinion, is a key tool. 67 00:03:23,356 --> 00:03:29,550 So we're using kinetics as a tool to study machines. 68 00:03:29,550 --> 00:03:31,680 And the machine we're studying is-- 69 00:03:31,680 --> 00:03:34,660 and have been studying is, is the ribosome. 70 00:03:34,660 --> 00:03:39,530 OK, so how many of you have had an introductory last lab 71 00:03:39,530 --> 00:03:42,590 course where you did kinetics? 72 00:03:42,590 --> 00:03:44,100 Only one? 73 00:03:44,100 --> 00:03:45,160 Two? 74 00:03:45,160 --> 00:03:47,390 OK, because steady state kinetics 75 00:03:47,390 --> 00:03:49,760 is where you start for everything, OK? 76 00:03:49,760 --> 00:03:51,230 And I find when I-- 77 00:03:51,230 --> 00:03:52,820 I've been teaching for many years-- 78 00:03:52,820 --> 00:03:54,819 that there are certain things about steady state 79 00:03:54,819 --> 00:03:57,600 kinetics that people don't seem to get. 80 00:03:57,600 --> 00:04:00,440 And furthermore, were steady state kinetics 81 00:04:00,440 --> 00:04:02,600 important in this paper you had to read? 82 00:04:02,600 --> 00:04:04,010 Can anybody tell me? 83 00:04:04,010 --> 00:04:06,650 Did you get anything about steady state kinetics? 84 00:04:06,650 --> 00:04:09,236 Did you think about it? 85 00:04:09,236 --> 00:04:11,390 This will tell me how closely you read the paper. 86 00:04:14,673 --> 00:04:17,490 No? 87 00:04:17,490 --> 00:04:18,360 No one? 88 00:04:18,360 --> 00:04:22,010 OK, so this paper is hard and this is a paper 89 00:04:22,010 --> 00:04:24,290 that, even though I read it probably 20 times, 90 00:04:24,290 --> 00:04:26,820 I still learn stuff every time I read it. 91 00:04:26,820 --> 00:04:29,360 So you can't read a paper once. 92 00:04:29,360 --> 00:04:32,900 There's huge amounts of information in this paper. 93 00:04:32,900 --> 00:04:37,440 And if you go back and look at it three weeks from now, 94 00:04:37,440 --> 00:04:40,070 you'll probably get a lot more because we're continually 95 00:04:40,070 --> 00:04:43,130 filling in pieces of information from you 96 00:04:43,130 --> 00:04:44,290 in this complex system. 97 00:04:44,290 --> 00:04:44,990 Yeah? 98 00:04:44,990 --> 00:04:47,880 AUDIENCE: The part, I think, related to the steady state 99 00:04:47,880 --> 00:04:51,892 kinetics they measure Kcat, and Km, and their ratio. 100 00:04:51,892 --> 00:04:54,350 JOANNE STUBBE: Right, so that that's where the steady state 101 00:04:54,350 --> 00:04:55,640 kinetics is. 102 00:04:55,640 --> 00:04:58,100 And so if it goes to the question 103 00:04:58,100 --> 00:05:01,400 of what can you learn from steady state kinetics, OK? 104 00:05:01,400 --> 00:05:05,130 So let me just put down a simple system, 105 00:05:05,130 --> 00:05:06,890 which you've all seen if you take 106 00:05:06,890 --> 00:05:08,720 an introductory biochemistry course. 107 00:05:08,720 --> 00:05:15,770 People use this system because you don't have very many rate 108 00:05:15,770 --> 00:05:16,670 constants. 109 00:05:16,670 --> 00:05:21,620 So when I write down rate constants, I don't put K's. 110 00:05:21,620 --> 00:05:24,961 I just put 1, 2, 3 because it becomes hard to read anything, 111 00:05:24,961 --> 00:05:25,460 OK? 112 00:05:25,460 --> 00:05:28,930 So this is a simple system for any catalyst, 113 00:05:28,930 --> 00:05:35,220 OK, where some substrate could be EFTU, and tRNA, 114 00:05:35,220 --> 00:05:39,560 and GTP binding to the ribosome, OK? 115 00:05:39,560 --> 00:05:42,920 You do some chemistry to form some product. 116 00:05:42,920 --> 00:05:45,500 OK, and then the product dissociates. 117 00:05:45,500 --> 00:05:49,620 So if you look at the rate of the reaction-- 118 00:05:49,620 --> 00:05:51,830 so this involves the assay. 119 00:05:51,830 --> 00:05:55,970 You have to develop an assay where you can monitor something 120 00:05:55,970 --> 00:05:58,110 as easily as possible. 121 00:05:58,110 --> 00:05:59,100 That's the key thing. 122 00:05:59,100 --> 00:06:02,180 So I think here is where your chemistry background plays 123 00:06:02,180 --> 00:06:05,150 an incredibly important role because you can 124 00:06:05,150 --> 00:06:08,030 be creative about your assays. 125 00:06:08,030 --> 00:06:12,380 And so and you look at this as a function of the concentration 126 00:06:12,380 --> 00:06:14,660 of your substrate. 127 00:06:14,660 --> 00:06:17,430 What does the spectrum look like? 128 00:06:17,430 --> 00:06:21,145 What does the graph look like? 129 00:06:21,145 --> 00:06:22,520 How would you describe the graph? 130 00:06:22,520 --> 00:06:24,470 This is something you've seen in 507. 131 00:06:24,470 --> 00:06:25,490 We're just going back. 132 00:06:25,490 --> 00:06:28,630 What does it look like? 133 00:06:28,630 --> 00:06:32,630 Right, exactly-- rectangular hyperbole. 134 00:06:32,630 --> 00:06:35,680 OK, and so I think what's important 135 00:06:35,680 --> 00:06:39,460 is that this kind of behavior has been observed over and over 136 00:06:39,460 --> 00:06:43,480 and over again since 1940s when this curve was first 137 00:06:43,480 --> 00:06:45,370 described by Michaelis and Menton 138 00:06:45,370 --> 00:06:48,110 with many variations on the theme. 139 00:06:48,110 --> 00:06:50,200 And so what you need to think about 140 00:06:50,200 --> 00:06:52,870 is you have two parts of the curve. 141 00:06:52,870 --> 00:06:55,060 What's happening up here? 142 00:06:55,060 --> 00:06:59,790 What is the dependence on the reaction on substrate? 143 00:06:59,790 --> 00:07:01,535 So we have an enzyme that's a catalyst. 144 00:07:01,535 --> 00:07:04,070 It doesn't matter whether you're an organic chemist, 145 00:07:04,070 --> 00:07:06,650 an inorganic chemist, a biochemist. 146 00:07:06,650 --> 00:07:08,480 All of these things can be described 147 00:07:08,480 --> 00:07:13,350 by this simple, simple cartoon. 148 00:07:13,350 --> 00:07:15,920 So what's happening up here? 149 00:07:15,920 --> 00:07:19,489 What's happening in this part of your graph? 150 00:07:19,489 --> 00:07:20,530 AUDIENCE: It's saturated. 151 00:07:20,530 --> 00:07:22,321 JOANNE STUBBE: Yeah, see, you're saturated. 152 00:07:22,321 --> 00:07:24,390 So you're zero water and substrate, OK? 153 00:07:24,390 --> 00:07:28,760 And then what's happening over here? 154 00:07:28,760 --> 00:07:31,200 Your first order N substrate, OK? 155 00:07:31,200 --> 00:07:33,310 So from those observations, people 156 00:07:33,310 --> 00:07:38,940 derived equations, a general equation. 157 00:07:38,940 --> 00:07:41,790 So the rate of product formation, 158 00:07:41,790 --> 00:07:44,910 whatever you're assay is that you're using, 159 00:07:44,910 --> 00:07:50,230 is equal to Vmax times a concentration of substrate 160 00:07:50,230 --> 00:07:54,140 over Km plus the concentration of substrate. 161 00:07:54,140 --> 00:07:57,700 OK, so you've all seen this before. 162 00:07:57,700 --> 00:08:01,750 And if you look at this one simple case, 163 00:08:01,750 --> 00:08:05,760 and you look at what is Vmax equal to-- can anybody 164 00:08:05,760 --> 00:08:13,394 tell me what are the rate constants within Vmax? 165 00:08:13,394 --> 00:08:16,850 So Kcat times the concentration of enzyme. 166 00:08:16,850 --> 00:08:19,360 OK, so Vmax, and what does that mean? 167 00:08:19,360 --> 00:08:23,720 Kcat we'll see in a minute, is the turnover number 168 00:08:23,720 --> 00:08:25,490 times the concentration of enzyme. 169 00:08:25,490 --> 00:08:27,990 That means all your catalysts have stuff on it. 170 00:08:27,990 --> 00:08:29,050 It can't go any faster. 171 00:08:29,050 --> 00:08:31,550 It doesn't matter if you add more, more, and more substrate. 172 00:08:31,550 --> 00:08:32,466 You have no catalysts. 173 00:08:32,466 --> 00:08:35,559 So that's what's limiting the reaction. 174 00:08:35,559 --> 00:08:42,140 So if you derive this equation using steady state assumptions, 175 00:08:42,140 --> 00:08:44,390 what are the four sets of equations 176 00:08:44,390 --> 00:08:48,612 you need to be able to derive this expression? 177 00:08:48,612 --> 00:08:50,360 Can anybody tell me? 178 00:08:50,360 --> 00:08:53,420 What are the conditions you need to do? 179 00:08:53,420 --> 00:08:57,570 So what's the goal of deriving this equation, first of all? 180 00:08:57,570 --> 00:08:59,690 And then what are the assumptions you make? 181 00:09:02,350 --> 00:09:05,390 OK, so you want to be able to describe what 182 00:09:05,390 --> 00:09:07,550 you see experimentally, OK? 183 00:09:07,550 --> 00:09:09,410 So the first thing you have to do 184 00:09:09,410 --> 00:09:12,080 is be able to measure it experimentally, OK? 185 00:09:12,080 --> 00:09:14,960 So you have to have something in terms 186 00:09:14,960 --> 00:09:18,530 of an experimentally measurable parameter. 187 00:09:18,530 --> 00:09:23,690 And if you look at e, es, ep, which one of these 188 00:09:23,690 --> 00:09:27,620 are going to be measurable? 189 00:09:27,620 --> 00:09:29,957 AUDIENCE: Going to be the substrate and the product. 190 00:09:29,957 --> 00:09:31,790 JOANNE STUBBE: OK, so substrate and product. 191 00:09:31,790 --> 00:09:33,030 Yeah, you can measure substrate. 192 00:09:33,030 --> 00:09:34,030 You can measure product. 193 00:09:34,030 --> 00:09:37,320 But I'm talking about e. 194 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, 195 00:09:41,360 --> 00:09:46,660 most of the times you have 20 more e, equilibria. 196 00:09:46,660 --> 00:09:49,794 So which one can you measure experimentally? 197 00:09:49,794 --> 00:09:52,510 AUDIENCE: [INAUDIBLE]. 198 00:09:52,510 --> 00:09:55,242 JOANNE STUBBE: Pardon me? 199 00:09:55,242 --> 00:09:56,450 AUDIENCE: [INAUDIBLE] enzyme. 200 00:09:56,450 --> 00:09:59,300 JOANNE STUBBE: Yeah, so you can measure the total enzyme. 201 00:09:59,300 --> 00:10:03,140 OK, so that's this the enzyme conservation equation. 202 00:10:03,140 --> 00:10:05,900 So you have-- I'm not going to draw this all out. 203 00:10:05,900 --> 00:10:08,660 This is a review that you've already seen, presumably. 204 00:10:08,660 --> 00:10:10,507 So that's the conservation equation. 205 00:10:10,507 --> 00:10:12,590 How do you measure the concentration of an enzyme? 206 00:10:15,326 --> 00:10:17,150 AUDIENCE: UV vis. 207 00:10:17,150 --> 00:10:19,580 JOANNE STUBBE: UV vis. 208 00:10:19,580 --> 00:10:21,890 What amino acids absorb in the visible? 209 00:10:24,860 --> 00:10:25,800 AUDIENCE: Tryptophan. 210 00:10:25,800 --> 00:10:26,380 JOANNE STUBBE: In the visible. 211 00:10:26,380 --> 00:10:27,631 AUDIENCE: Oh, in the visible? 212 00:10:27,631 --> 00:10:28,130 None. 213 00:10:28,130 --> 00:10:28,510 JOANNE STUBBE: None. 214 00:10:28,510 --> 00:10:29,770 So don't say UV vis. 215 00:10:29,770 --> 00:10:31,100 Say UV, OK? 216 00:10:31,100 --> 00:10:34,910 So this is key to being able to sort things out. 217 00:10:34,910 --> 00:10:41,330 So what are the amino acid side chains that absorb in the UV? 218 00:10:41,330 --> 00:10:43,287 This comes back to-- you need to-- 219 00:10:43,287 --> 00:10:44,680 AUDIENCE: Tryptophan, tyrosine. 220 00:10:44,680 --> 00:10:45,340 JOANNE STUBBE: Right. 221 00:10:45,340 --> 00:10:47,256 So tryptophan and tyrocine are the major ones. 222 00:10:47,256 --> 00:10:49,060 Then phenylalanine is much smaller. 223 00:10:49,060 --> 00:10:51,250 So you can measure this. 224 00:10:51,250 --> 00:10:54,640 But, in general, you can't measure all the other forms. 225 00:10:54,640 --> 00:10:57,520 OK, so you know this, and that's required 226 00:10:57,520 --> 00:11:01,030 to be able to get this expression that describes 227 00:11:01,030 --> 00:11:02,890 this rectangular hyperbole. 228 00:11:02,890 --> 00:11:06,070 What about the substrate concentration? 229 00:11:06,070 --> 00:11:09,190 Under normal assays, if you've done an assay in the lab, 230 00:11:09,190 --> 00:11:11,020 how is the reaction set up? 231 00:11:14,868 --> 00:11:16,610 How much enzyme do you have in there? 232 00:11:16,610 --> 00:11:19,475 How much substrate do you have in there? 233 00:11:19,475 --> 00:11:21,244 AUDIENCE: A lot of substrate. 234 00:11:21,244 --> 00:11:22,660 JOANNE STUBBE: A lot of substrate. 235 00:11:22,660 --> 00:11:24,610 And what conditions are you under, 236 00:11:24,610 --> 00:11:29,470 perhaps, if you have a lot of substrate, over here 237 00:11:29,470 --> 00:11:31,059 in this graph? 238 00:11:31,059 --> 00:11:32,600 AUDIENCE: You have to saturate your-- 239 00:11:32,600 --> 00:11:34,475 JOANNE STUBBE: Yeah, well, you don't have to, 240 00:11:34,475 --> 00:11:37,150 but you would be saturated if you had a lot of substrate. 241 00:11:37,150 --> 00:11:38,890 How much enzyme do you have in there? 242 00:11:38,890 --> 00:11:40,424 A lot or a little? 243 00:11:40,424 --> 00:11:41,215 AUDIENCE: A little. 244 00:11:41,215 --> 00:11:42,381 JOANNE STUBBE: A little, OK? 245 00:11:42,381 --> 00:11:46,900 So the enzyme, the concentration of the substrate 246 00:11:46,900 --> 00:11:49,731 is much, much greater than the concentration of the enzyme, 247 00:11:49,731 --> 00:11:50,230 OK? 248 00:11:50,230 --> 00:11:52,930 So that's a typical steady state assay 249 00:11:52,930 --> 00:11:57,610 when you go to determine the rate of your reaction. 250 00:11:57,610 --> 00:11:59,361 So because the concentration of the enzyme 251 00:11:59,361 --> 00:12:01,276 is much, much greater than the concentration-- 252 00:12:01,276 --> 00:12:03,200 the concentration of the substrate is much, 253 00:12:03,200 --> 00:12:05,290 much greater than the concentration of the enzyme, 254 00:12:05,290 --> 00:12:07,630 you don't have to worry about substrate 255 00:12:07,630 --> 00:12:09,550 being bound in these forms. 256 00:12:09,550 --> 00:12:13,180 So the second equation you routinely use 257 00:12:13,180 --> 00:12:16,750 is called the substrate conservation equation, 258 00:12:16,750 --> 00:12:20,260 because it doesn't change, because the amount of this es 259 00:12:20,260 --> 00:12:23,990 on the enzyme, which is tiny, you don't need to measure it. 260 00:12:23,990 --> 00:12:25,570 So this is the second. 261 00:12:25,570 --> 00:12:27,880 So these are both conservation equations. 262 00:12:32,600 --> 00:12:37,660 OK, so we just said we were doing steady state kinetics, 263 00:12:37,660 --> 00:12:38,350 OK? 264 00:12:38,350 --> 00:12:41,020 So now you need to be able to make the steady state 265 00:12:41,020 --> 00:12:43,500 assumption, which hopefully all of you know. 266 00:12:43,500 --> 00:12:48,250 So the rate of change of some intermediate with respect 267 00:12:48,250 --> 00:12:52,780 to time is equal to 0, that is we're under a set of conditions 268 00:12:52,780 --> 00:12:55,420 where the rate of formation is equal to the rate 269 00:12:55,420 --> 00:12:58,720 of disappearance of whatever this species is. 270 00:12:58,720 --> 00:13:00,730 And what is the fourth equation we 271 00:13:00,730 --> 00:13:04,429 need to be able to set up this? 272 00:13:04,429 --> 00:13:06,220 What is the fourth thing, which is probably 273 00:13:06,220 --> 00:13:08,152 the most straightforward? 274 00:13:08,152 --> 00:13:09,610 And, again, it needs to be in terms 275 00:13:09,610 --> 00:13:13,882 of experimentally measurable parameters. 276 00:13:13,882 --> 00:13:16,280 What are we measuring in our reaction? 277 00:13:16,280 --> 00:13:19,160 AUDIENCE: You said the position from vs 278 00:13:19,160 --> 00:13:21,080 to [INAUDIBLE] is irreversible. 279 00:13:21,080 --> 00:13:26,330 JOANNE STUBBE: No, you I could have done this. 280 00:13:26,330 --> 00:13:28,355 And what would that have done to my equation? 281 00:13:28,355 --> 00:13:30,517 It just would have put in more rate constants. 282 00:13:30,517 --> 00:13:33,100 I'm going to show you what the rate constants are in a minute. 283 00:13:33,100 --> 00:13:36,120 There's nothing-- in fact, almost no enzyme reactions 284 00:13:36,120 --> 00:13:37,520 are irreversible. 285 00:13:37,520 --> 00:13:39,940 If you look, you can find reversibility 286 00:13:39,940 --> 00:13:41,050 in almost all reactions. 287 00:13:41,050 --> 00:13:47,110 This is-- so why do people write equations like this? 288 00:13:47,110 --> 00:13:50,580 They like irreversible reactions because it makes 289 00:13:50,580 --> 00:13:52,900 the kinetic derivation simpler. 290 00:13:52,900 --> 00:13:55,300 You don't have as many rate constants, OK? 291 00:13:55,300 --> 00:13:57,520 So, but what do you need now? 292 00:13:57,520 --> 00:13:59,020 We're monitoring the reaction? 293 00:13:59,020 --> 00:14:00,960 What are you going to monitor? 294 00:14:00,960 --> 00:14:02,847 So we know how much enzyme we have. 295 00:14:02,847 --> 00:14:03,680 We can measure that. 296 00:14:03,680 --> 00:14:05,304 We know how much substrate we can have. 297 00:14:05,304 --> 00:14:06,260 We can measure that. 298 00:14:06,260 --> 00:14:08,650 We know what the steady state assumption is, 299 00:14:08,650 --> 00:14:09,670 and we have an equation. 300 00:14:09,670 --> 00:14:10,750 So we can describe that. 301 00:14:10,750 --> 00:14:12,083 What's the other thing you need? 302 00:14:12,083 --> 00:14:13,990 It's the standard thing. 303 00:14:13,990 --> 00:14:16,330 How do you describe the rate of product formation? 304 00:14:19,110 --> 00:14:20,270 That's this guy over here. 305 00:14:24,030 --> 00:14:25,670 So what do you need? 306 00:14:25,670 --> 00:14:28,570 You need some kind of an equation 307 00:14:28,570 --> 00:14:31,570 that expresses just appearance of substrate, 308 00:14:31,570 --> 00:14:33,210 formation of products. 309 00:14:33,210 --> 00:14:36,420 So you need a way of measuring this. 310 00:14:36,420 --> 00:14:38,470 And you can do this many ways, even 311 00:14:38,470 --> 00:14:40,900 from a simple equation we've shown over here 312 00:14:40,900 --> 00:14:44,020 because a description of the rate of product formation 313 00:14:44,020 --> 00:14:48,250 is simply the net flux through any step in the pathway. 314 00:14:48,250 --> 00:14:50,860 And so what you see people writing 315 00:14:50,860 --> 00:14:53,500 is they immediately go to an irreversible step 316 00:14:53,500 --> 00:14:56,530 because it makes the algebra simpler. 317 00:14:56,530 --> 00:14:58,720 So k3 times the concentration of ep 318 00:14:58,720 --> 00:15:00,820 would be the net flux through this step. 319 00:15:00,820 --> 00:15:03,040 But I could write the net flux through this step 320 00:15:03,040 --> 00:15:04,940 and I would get the same answer. 321 00:15:04,940 --> 00:15:09,010 So it's the net flux through any step in the pathway. 322 00:15:09,010 --> 00:15:11,890 OK, so why am I going through all of this? 323 00:15:19,375 --> 00:15:21,230 OK, and the reason I'm going through this 324 00:15:21,230 --> 00:15:25,650 is because of this Kcat over km, which I just described to you. 325 00:15:25,650 --> 00:15:30,230 So one of the questions I asked you to think about when you're 326 00:15:30,230 --> 00:15:32,900 thinking about steady state kinetics 327 00:15:32,900 --> 00:15:36,290 is what are the two important parameters you get out 328 00:15:36,290 --> 00:15:40,530 of Michaelis Menton analysis? 329 00:15:40,530 --> 00:15:43,850 And the reason I ask this is because, in my opinion, 330 00:15:43,850 --> 00:15:45,560 it's not correct in most textbooks. 331 00:15:48,710 --> 00:15:52,200 So what are the two important parameters 332 00:15:52,200 --> 00:15:54,470 you get that you learned about that you probably even 333 00:15:54,470 --> 00:15:56,540 evaluated if you did something in the lab? 334 00:16:01,074 --> 00:16:01,699 AUDIENCE: Kcat. 335 00:16:01,699 --> 00:16:04,220 JOANNE STUBBE: Kcat is one of them. 336 00:16:04,220 --> 00:16:06,744 OK, and what's the other one? 337 00:16:06,744 --> 00:16:09,029 AUDIENCE: Km. 338 00:16:09,029 --> 00:16:12,070 JOANNE STUBBE: OK, so this is what everybody says, is km. 339 00:16:12,070 --> 00:16:14,350 And that's not correct, OK? 340 00:16:14,350 --> 00:16:18,245 So let me put down what the-- 341 00:16:18,245 --> 00:16:20,020 what did I do with it-- 342 00:16:20,020 --> 00:16:24,320 the values for the kinetic constants are here. 343 00:16:24,320 --> 00:16:28,006 So in this particular simple equation, 344 00:16:28,006 --> 00:16:33,286 it's Kcat is 2 times 3 over 2 plus 3. 345 00:16:33,286 --> 00:16:36,130 OK, so this is Kcat. 346 00:16:36,130 --> 00:16:39,780 And Km out of this analysis is 3. 347 00:16:39,780 --> 00:16:42,180 The numbers really aren't important. 348 00:16:42,180 --> 00:16:47,190 What I want you to see is that there 349 00:16:47,190 --> 00:16:50,290 are a huge number of first order rate constants 350 00:16:50,290 --> 00:16:54,700 in each of these parameters Km and Kcat, OK? 351 00:16:54,700 --> 00:16:56,669 Can you measure these? 352 00:16:56,669 --> 00:16:58,210 Can you measure these rate constants? 353 00:16:58,210 --> 00:17:00,970 That's what you want to know if you want to understand how this 354 00:17:00,970 --> 00:17:03,940 works, you would like to understand 355 00:17:03,940 --> 00:17:06,470 the reaction coordinate and what the rate constants are 356 00:17:06,470 --> 00:17:07,720 for every step in the pathway. 357 00:17:07,720 --> 00:17:09,760 That's what the whole Rodnina paper 358 00:17:09,760 --> 00:17:14,200 is about with the long range goal of understanding fidelity. 359 00:17:14,200 --> 00:17:16,869 Can we come up with a model for fidelity 360 00:17:16,869 --> 00:17:20,630 in the translational process that's contributed by EFTU? 361 00:17:24,033 --> 00:17:30,430 So can we measure these guys from an assay the concentration 362 00:17:30,430 --> 00:17:34,915 of the enzyme, The concentration of the substrate, 363 00:17:34,915 --> 00:17:38,291 the steady state assumption? 364 00:17:38,291 --> 00:17:39,240 What do you think? 365 00:17:43,950 --> 00:17:45,392 Don't be afraid. 366 00:17:45,392 --> 00:17:48,504 This is a discussion. 367 00:17:48,504 --> 00:17:49,870 What do you think? 368 00:17:49,870 --> 00:17:52,350 Can we measure? 369 00:17:52,350 --> 00:17:54,361 AUDIENCE: Does it depend how fast it is? 370 00:17:54,361 --> 00:17:55,110 JOANNE STUBBE: No. 371 00:17:55,110 --> 00:17:55,750 AUDIENCE: No? 372 00:17:55,750 --> 00:17:58,470 JOANNE STUBBE: No. 373 00:17:58,470 --> 00:18:00,240 It is dependent on how fast it is, 374 00:18:00,240 --> 00:18:02,460 but it doesn't matter how fast it 375 00:18:02,460 --> 00:18:06,840 is to answer this question, OK? 376 00:18:06,840 --> 00:18:08,310 Anybody else got another guess? 377 00:18:10,880 --> 00:18:11,380 What? 378 00:18:11,380 --> 00:18:12,190 Your name? 379 00:18:12,190 --> 00:18:12,610 AUDIENCE: Rebecca. 380 00:18:12,610 --> 00:18:13,030 JOANNE STUBBE: Rebecca. 381 00:18:13,030 --> 00:18:13,630 What's your name? 382 00:18:13,630 --> 00:18:14,010 AUDIENCE: Nicole. 383 00:18:14,010 --> 00:18:14,926 JOANNE STUBBE: Nicole. 384 00:18:14,926 --> 00:18:16,598 OK, yeah? 385 00:18:16,598 --> 00:18:18,065 AUDIENCE: Yeah. 386 00:18:18,065 --> 00:18:20,021 [INAUDIBLE] measure them [INAUDIBLE] 387 00:18:20,021 --> 00:18:23,444 we measure the initial rate, [INAUDIBLE] 388 00:18:23,444 --> 00:18:25,004 take that [INAUDIBLE]. 389 00:18:25,004 --> 00:18:26,920 JOANNE STUBBE: So you get Kcat and you get Km. 390 00:18:26,920 --> 00:18:28,420 That's not the question I asked. 391 00:18:28,420 --> 00:18:31,420 I asked, can you measure all the first order rate constants 392 00:18:31,420 --> 00:18:34,560 that make up Kcat and Km? 393 00:18:34,560 --> 00:18:35,460 No. 394 00:18:35,460 --> 00:18:37,500 So the problem with steady state kinetics 395 00:18:37,500 --> 00:18:39,690 is you can't really learn very much, OK? 396 00:18:39,690 --> 00:18:42,990 So what can you learn from steady state kinetics, 397 00:18:42,990 --> 00:18:44,835 and why do we keep looking at it? 398 00:18:44,835 --> 00:18:46,890 OK, why is it the first thing you've seen 399 00:18:46,890 --> 00:18:49,610 this with the tRNA synthetases? 400 00:18:49,610 --> 00:18:54,090 You saw Kcat over Km values charging with valine 401 00:18:54,090 --> 00:18:55,760 or isoleucine, right? 402 00:18:55,760 --> 00:18:58,650 In this paper, if you go back and look carefully 403 00:18:58,650 --> 00:19:00,540 at the discussion at the end of the paper-- 404 00:19:00,540 --> 00:19:03,420 so hopefully after this class you'll go back and you'll read 405 00:19:03,420 --> 00:19:04,590 that-- 406 00:19:04,590 --> 00:19:09,330 a lot of the discussion is about mechanisms of fidelity 407 00:19:09,330 --> 00:19:12,460 where they are thinking about these initial steps. 408 00:19:12,460 --> 00:19:17,760 And so these initial steps are really the selection steps 409 00:19:17,760 --> 00:19:20,330 of these things binding, OK? 410 00:19:20,330 --> 00:19:22,770 And if you go back and you look at the equation 411 00:19:22,770 --> 00:19:26,080 that they derive, it's amazingly complicated. 412 00:19:26,080 --> 00:19:26,580 Why? 413 00:19:26,580 --> 00:19:31,040 Because we have many more equilibria in our equation, 414 00:19:31,040 --> 00:19:36,540 but what you can get out of all this is Kcat and Kcat over Km. 415 00:19:36,540 --> 00:19:40,500 So Km really is not very informative 416 00:19:40,500 --> 00:19:44,760 at all because it's composed of a whole bunch of first order 417 00:19:44,760 --> 00:19:46,880 rate constants. 418 00:19:46,880 --> 00:19:49,920 It's always never equal to the dissociation constant, OK? 419 00:19:49,920 --> 00:19:52,287 So you can't-- so what it is mathematically, 420 00:19:52,287 --> 00:19:54,495 it's the concentration required to reach half maximum 421 00:19:54,495 --> 00:19:55,480 of velocity. 422 00:19:55,480 --> 00:19:57,710 So it doesn't really tell you anything. 423 00:19:57,710 --> 00:19:59,550 It's just half maximum of velocity. 424 00:19:59,550 --> 00:20:03,360 OK, so the two parameters that you need to think about-- 425 00:20:03,360 --> 00:20:05,070 and this goes back to the way you 426 00:20:05,070 --> 00:20:06,540 do experiments in the steady state 427 00:20:06,540 --> 00:20:08,190 versus the pre-steady state, which 428 00:20:08,190 --> 00:20:13,080 is what we're focusing on in this paper, 429 00:20:13,080 --> 00:20:16,880 is that you have two extremes when you do kinetics. 430 00:20:16,880 --> 00:20:18,480 And kinetics is something-- how do 431 00:20:18,480 --> 00:20:19,740 you learn how to do kinetics? 432 00:20:19,740 --> 00:20:21,180 You do them yourself. 433 00:20:21,180 --> 00:20:22,990 And you think about-- 434 00:20:22,990 --> 00:20:25,170 you think about what you think is going on. 435 00:20:25,170 --> 00:20:28,124 And then you make guesses about what's going on. 436 00:20:28,124 --> 00:20:30,540 And these are one of the types of experiments, when you're 437 00:20:30,540 --> 00:20:34,200 doing them you change your experimental design 438 00:20:34,200 --> 00:20:35,680 in the middle of your experiment. 439 00:20:35,680 --> 00:20:39,120 So it takes a lot of practice to get good at kinetics. 440 00:20:39,120 --> 00:20:40,920 But what you do with all kinetics, 441 00:20:40,920 --> 00:20:43,440 look at the extremes, the limits. 442 00:20:43,440 --> 00:20:47,830 So one extreme is the concentration of s 443 00:20:47,830 --> 00:20:49,870 goes to infinity. 444 00:20:49,870 --> 00:20:53,100 OK, so if you look at that extreme, what do you have? 445 00:20:53,100 --> 00:20:55,770 If s goes to infinity, what happens to b? 446 00:20:59,620 --> 00:21:02,740 What happens to this equation? 447 00:21:02,740 --> 00:21:04,740 AUDIENCE: [INAUDIBLE]. 448 00:21:04,740 --> 00:21:08,400 JOANNE STUBBE: Yeah, so it goes to Vmax, or Kcat times 449 00:21:08,400 --> 00:21:09,570 the concentration of e. 450 00:21:09,570 --> 00:21:11,960 So you're up here, OK? 451 00:21:11,960 --> 00:21:13,740 And so what is Kcat? 452 00:21:13,740 --> 00:21:15,570 So you can get out of this Kcat. 453 00:21:15,570 --> 00:21:18,690 Why is Kcat an important parameter? 454 00:21:18,690 --> 00:21:20,130 Why do people care about Kcat? 455 00:21:27,826 --> 00:21:29,815 Hey, what's your name? 456 00:21:29,815 --> 00:21:30,440 AUDIENCE: Alex. 457 00:21:30,440 --> 00:21:32,300 JOANNE STUBBE: Alex. 458 00:21:32,300 --> 00:21:34,924 My nephew's name is Alex. 459 00:21:34,924 --> 00:21:37,730 I'll remember that, OK? 460 00:21:37,730 --> 00:21:40,540 You're stuck. 461 00:21:40,540 --> 00:21:42,740 What's Kcat? 462 00:21:42,740 --> 00:21:47,509 AUDIENCE: It's like how quickly the enzyme turns over-- 463 00:21:47,509 --> 00:21:48,800 JOANNE STUBBE: Per active site. 464 00:21:48,800 --> 00:21:50,650 So it's called the turnover number. 465 00:21:50,650 --> 00:21:51,930 OK, so what does it tell you. 466 00:21:51,930 --> 00:21:54,110 It tells you how good your catalyst is, OK? 467 00:21:54,110 --> 00:21:56,290 So that's pretty important. 468 00:21:56,290 --> 00:21:59,750 So this is the turnover number. 469 00:21:59,750 --> 00:22:02,030 And I would also say it's pretty-- 470 00:22:02,030 --> 00:22:07,100 in the age of recombinant production or proteins, 471 00:22:07,100 --> 00:22:10,880 where we never isolate proteins from the normal source-- 472 00:22:10,880 --> 00:22:14,960 we isolate them all from bacteria or from yeast-- 473 00:22:14,960 --> 00:22:18,230 Kcat becomes really important to know, OK? 474 00:22:18,230 --> 00:22:20,510 So how do you know what the real Kcat should 475 00:22:20,510 --> 00:22:25,070 be if you isolate your enzyme from a protein that's 476 00:22:25,070 --> 00:22:26,450 expressed in E. coli? 477 00:22:26,450 --> 00:22:28,100 Do you think you get the real Kcat? 478 00:22:34,530 --> 00:22:36,220 Have you ever thought about that? 479 00:22:36,220 --> 00:22:37,390 Most people haven't, OK? 480 00:22:37,390 --> 00:22:40,552 So you're not alone. 481 00:22:40,552 --> 00:22:44,180 What could happen if you expressed your protein 482 00:22:44,180 --> 00:22:48,410 in a bacteria, or in another model organism like yeast? 483 00:22:48,410 --> 00:22:49,886 AUDIENCE: [INAUDIBLE]. 484 00:22:49,886 --> 00:22:51,440 JOANNE STUBBE: Yeah, it might not 485 00:22:51,440 --> 00:22:53,150 have the appropriate-- it's probably 486 00:22:53,150 --> 00:22:54,650 not-- it could be post-translational 487 00:22:54,650 --> 00:22:55,280 modification. 488 00:22:55,280 --> 00:22:56,720 It could be co-factors. 489 00:22:56,720 --> 00:22:59,300 So there are examples in the literature of very, very 490 00:22:59,300 --> 00:23:02,600 smart scientists who have spent 25 years of their life studying 491 00:23:02,600 --> 00:23:06,800 an enzyme that was only 1% active. 492 00:23:06,800 --> 00:23:09,050 So this is, in this course-- and I 493 00:23:09,050 --> 00:23:10,560 think in general in biochemistry-- 494 00:23:10,560 --> 00:23:12,560 you've got to go back and forth between the cell 495 00:23:12,560 --> 00:23:15,120 and what you see in the test tube. 496 00:23:15,120 --> 00:23:21,352 So this Kcat, if the number is 0.00001 per second, 497 00:23:21,352 --> 00:23:23,810 you have to have some intuition that tells you, oh, my god. 498 00:23:23,810 --> 00:23:24,990 That's so slow. 499 00:23:24,990 --> 00:23:26,850 Something-- something is wrong. 500 00:23:26,850 --> 00:23:30,060 So this number of turnover is incredibly important. 501 00:23:30,060 --> 00:23:33,620 It gives you a feeling for how good your catalyst is. 502 00:23:33,620 --> 00:23:35,180 But the number we're really after 503 00:23:35,180 --> 00:23:38,450 is the second example and the other limit. 504 00:23:38,450 --> 00:23:43,410 And what happens is s goes to 0, what happens to this equation. 505 00:23:43,410 --> 00:23:45,410 So those are the two extremes, OK? 506 00:23:45,410 --> 00:23:48,020 So as s goes to 0, 507 00:23:48,020 --> 00:23:49,835 OK, that's the other part of this equation. 508 00:23:54,560 --> 00:23:57,340 What happens to the equation? 509 00:23:57,340 --> 00:23:59,870 The rate of product formation is equal to-- 510 00:23:59,870 --> 00:24:03,530 and I'll write Vmax as KT times the concentration 511 00:24:03,530 --> 00:24:05,780 of total enzyme, OK? 512 00:24:05,780 --> 00:24:06,860 I didn't write it down. 513 00:24:06,860 --> 00:24:09,700 Hopefully you all know that. 514 00:24:09,700 --> 00:24:14,230 So what you now get is Kcat over Km times 515 00:24:14,230 --> 00:24:17,360 the concentration of e times the concentration of s. 516 00:24:17,360 --> 00:24:22,210 So what is this guy, if you look at this equation? 517 00:24:22,210 --> 00:24:23,274 What's Kcat over Km? 518 00:24:23,274 --> 00:24:24,065 What are the units? 519 00:24:30,811 --> 00:24:32,190 Kinetics isn't that hard. 520 00:24:34,950 --> 00:24:36,960 These are pretty-- if you think this is hard, 521 00:24:36,960 --> 00:24:38,500 wait till you start getting-- 522 00:24:38,500 --> 00:24:41,085 we're not going to go into derivation of steady state, 523 00:24:41,085 --> 00:24:42,960 pre-steady state analysis. 524 00:24:42,960 --> 00:24:46,070 But this is pretty simple compared to pre-steady state 525 00:24:46,070 --> 00:24:46,830 analysis. 526 00:24:46,830 --> 00:24:48,510 So what's Kcat over Km? 527 00:24:48,510 --> 00:24:49,810 What are the units? 528 00:24:49,810 --> 00:24:51,100 AUDIENCE: [INAUDIBLE]. 529 00:24:51,100 --> 00:24:52,250 JOANNE STUBBE: Yeah. 530 00:24:52,250 --> 00:24:52,800 Yeah. 531 00:24:52,800 --> 00:24:54,380 So it's second order rate constant. 532 00:24:54,380 --> 00:24:55,570 So that's the key thing. 533 00:24:55,570 --> 00:24:57,160 So what are you looking at? 534 00:24:57,160 --> 00:24:58,800 You can look at that by this equation. 535 00:24:58,800 --> 00:25:02,070 What you're looking at is the enzyme combining 536 00:25:02,070 --> 00:25:04,150 with the substrate, OK? 537 00:25:04,150 --> 00:25:05,680 And that's what we care about. 538 00:25:05,680 --> 00:25:09,480 That's the specificity, specificity, or efficiency 539 00:25:09,480 --> 00:25:10,390 of your reaction. 540 00:25:10,390 --> 00:25:15,420 So if you have a tRNA loosing and an tRNA phenylalanine, 541 00:25:15,420 --> 00:25:19,120 they're both competing for binding to the substrate. 542 00:25:19,120 --> 00:25:22,530 So the important parameter to think about that selection-- 543 00:25:22,530 --> 00:25:26,340 and that's why that's important at the end of this paper-- 544 00:25:26,340 --> 00:25:28,710 relates to Kcat over Km. 545 00:25:28,710 --> 00:25:32,100 It's the specificity or efficiency number. 546 00:25:32,100 --> 00:25:35,980 And if any of you ever work in a pharmaceutical industry, 547 00:25:35,980 --> 00:25:38,010 you'll find out that, of course, you never-- 548 00:25:38,010 --> 00:25:39,630 and you're looking for inhibitors, 549 00:25:39,630 --> 00:25:40,950 you never look at Kcat. 550 00:25:40,950 --> 00:25:42,240 Why don't you look at Kcat? 551 00:25:42,240 --> 00:25:44,520 You always look at Kcat over Km. 552 00:25:44,520 --> 00:25:45,667 Why is that true? 553 00:25:45,667 --> 00:25:46,500 Can anybody tell me? 554 00:25:46,500 --> 00:25:49,590 If you were looking for a drug, if you were looking 555 00:25:49,590 --> 00:25:52,530 for an antibiotic, fusidic acid that we talked about 556 00:25:52,530 --> 00:25:59,830 today that inhibits the EFG that Liz talked about, 557 00:25:59,830 --> 00:26:01,520 how would you set up the experiment 558 00:26:01,520 --> 00:26:03,143 to look for inhibition? 559 00:26:07,980 --> 00:26:11,110 What would you do with your concentration of substrate? 560 00:26:11,110 --> 00:26:13,340 Do you want it high or do you want it low? 561 00:26:13,340 --> 00:26:14,719 AUDIENCE: You want it low. 562 00:26:14,719 --> 00:26:16,010 JOANNE STUBBE: You want it low. 563 00:26:16,010 --> 00:26:19,210 Why do you want it low? 564 00:26:19,210 --> 00:26:22,399 AUDIENCE: Because [INAUDIBLE]. 565 00:26:22,399 --> 00:26:24,190 JOANNE STUBBE: Yeah, so if you're inhibitor 566 00:26:24,190 --> 00:26:27,024 is binding to the same site, and you have a huge amount of this, 567 00:26:27,024 --> 00:26:29,440 no matter what you do, even if this was a great inhibitor, 568 00:26:29,440 --> 00:26:31,762 if you had 10,000 times the amount of this, 569 00:26:31,762 --> 00:26:33,470 you're never going to see any inhibition. 570 00:26:33,470 --> 00:26:35,439 So understanding these simple principles-- 571 00:26:35,439 --> 00:26:36,980 which I can tell you there are people 572 00:26:36,980 --> 00:26:38,870 that don't get this in drug companies-- 573 00:26:38,870 --> 00:26:40,730 are pretty important, OK? 574 00:26:40,730 --> 00:26:43,190 So Kcat and Kcat over Km, boring. 575 00:26:43,190 --> 00:26:44,570 But it's not really so boring. 576 00:26:44,570 --> 00:26:47,909 It's sort of central to everything 577 00:26:47,909 --> 00:26:50,450 that you'll be thinking about over the course of the semester 578 00:26:50,450 --> 00:26:52,426 and almost all the modules in some form, 579 00:26:52,426 --> 00:26:54,800 although we won't highlight it like we're highlighting it 580 00:26:54,800 --> 00:26:55,540 here. 581 00:26:55,540 --> 00:27:00,620 OK, so, again, the reason we care about Kcat over Km 582 00:27:00,620 --> 00:27:04,614 is this question of selectivity. 583 00:27:04,614 --> 00:27:09,470 And I urge you to go back and look in the methods 584 00:27:09,470 --> 00:27:10,990 section of your paper. 585 00:27:10,990 --> 00:27:14,540 Now, this paper is packed full of stuff, OK? so as I said, 586 00:27:14,540 --> 00:27:16,220 I read it 20 times. 587 00:27:16,220 --> 00:27:19,550 Every time I read it, I find out something new. 588 00:27:19,550 --> 00:27:21,800 And furthermore, I think the paper-- how many of you 589 00:27:21,800 --> 00:27:23,924 found it a tough slog to go through this paper? 590 00:27:23,924 --> 00:27:25,340 This is probably the hardest paper 591 00:27:25,340 --> 00:27:28,434 you're going to look at in my opinion? 592 00:27:28,434 --> 00:27:29,850 Did you think it was well written? 593 00:27:29,850 --> 00:27:31,265 Did you get the ideas? 594 00:27:34,352 --> 00:27:37,386 OK, Did you all get the ideas or not, 595 00:27:37,386 --> 00:27:38,760 or where you completely confused, 596 00:27:38,760 --> 00:27:40,343 or you didn't spend enough time on it? 597 00:27:40,343 --> 00:27:42,624 How much time did you have to spend on it? 598 00:27:42,624 --> 00:27:44,025 AUDIENCE: Probably about an hour. 599 00:27:44,025 --> 00:27:45,150 JOANNE STUBBE: OK, an hour. 600 00:27:45,150 --> 00:27:47,420 OK, so I would say-- 601 00:27:47,420 --> 00:27:50,500 I read the paper 45 times, and it takes me two hours 602 00:27:50,500 --> 00:27:52,130 to read a paper like this. 603 00:27:52,130 --> 00:27:55,766 OK, so again, it's a question of what level 604 00:27:55,766 --> 00:27:56,890 you want to look at things. 605 00:27:56,890 --> 00:27:59,350 And I think part of what this course is about 606 00:27:59,350 --> 00:28:02,340 is looking at experimental details. 607 00:28:02,340 --> 00:28:03,340 You're want to see that. 608 00:28:03,340 --> 00:28:07,330 And the problems set, you're going to see that in lecture. 609 00:28:07,330 --> 00:28:09,340 You're going to see that probably 610 00:28:09,340 --> 00:28:12,250 next time when we continue to look at the primary data 611 00:28:12,250 --> 00:28:13,990 that they collected, how important 612 00:28:13,990 --> 00:28:19,990 it is to look at the axes, and not just looking at it rapidly. 613 00:28:19,990 --> 00:28:23,150 You really have to think about what the data is telling you. 614 00:28:23,150 --> 00:28:28,570 So this paper is complicated from my point of view 615 00:28:28,570 --> 00:28:30,710 because it's based on-- 616 00:28:30,710 --> 00:28:32,620 it's based on 15 other papers. 617 00:28:32,620 --> 00:28:36,040 OK, so for you to really believe what they say, 618 00:28:36,040 --> 00:28:38,630 which is what you need to do as a scientist, 619 00:28:38,630 --> 00:28:42,220 how to critically evaluate somebody else's data, 620 00:28:42,220 --> 00:28:44,880 you need to really go back-- and we didn't ask you to do that-- 621 00:28:44,880 --> 00:28:49,742 and really critically evaluate the earlier experiments 622 00:28:49,742 --> 00:28:52,200 they've done, because some of the conclusions they've done, 623 00:28:52,200 --> 00:28:55,270 when we look at the primary data, I could have drawn-- 624 00:28:55,270 --> 00:28:57,130 without knowing all that primary data, 625 00:28:57,130 --> 00:29:00,110 I could have drawn a conclusion completely different. 626 00:29:00,110 --> 00:29:03,420 So you see something and you've got to explain it, OK? 627 00:29:03,420 --> 00:29:05,470 And so when you start out, you have no idea. 628 00:29:05,470 --> 00:29:06,980 You have a very simple model. 629 00:29:06,980 --> 00:29:09,490 And in general, the model's almost always 630 00:29:09,490 --> 00:29:11,024 get more and more complex. 631 00:29:11,024 --> 00:29:13,190 That's what you're going to see over and over again. 632 00:29:13,190 --> 00:29:16,660 You start out as simple as possible, and then things 633 00:29:16,660 --> 00:29:18,220 get more complex. 634 00:29:18,220 --> 00:29:24,760 OK, so what we want to do now is ask the question. 635 00:29:24,760 --> 00:29:27,250 And I've just told you, you can't 636 00:29:27,250 --> 00:29:29,530 evaluate these individual rate constants. 637 00:29:29,530 --> 00:29:32,080 We just don't have enough variables, OK? 638 00:29:32,080 --> 00:29:34,870 We don't have enough that we can measure, 639 00:29:34,870 --> 00:29:37,570 that we can change the substrate concentration we can change, 640 00:29:37,570 --> 00:29:39,490 which changes the rate of product formation. 641 00:29:39,490 --> 00:29:40,781 So those are the two variables. 642 00:29:40,781 --> 00:29:42,460 But we have many more unknowns. 643 00:29:42,460 --> 00:29:46,060 We have k1, k2, k minus 2, k2, et cetera. 644 00:29:46,060 --> 00:29:48,020 So we can't evaluate these things. 645 00:29:48,020 --> 00:29:50,380 So the question is, is there any way 646 00:29:50,380 --> 00:29:53,650 you can start getting the primary rate 647 00:29:53,650 --> 00:29:57,220 constant, the numbers to the primary rate constants, OK? 648 00:29:57,220 --> 00:30:00,460 And so one way that people do this nowadays-- 649 00:30:00,460 --> 00:30:05,050 and when this paper was done, this was not an easy task. 650 00:30:05,050 --> 00:30:08,890 OK, now because of molecular biology where you can get large 651 00:30:08,890 --> 00:30:11,860 amounts of protein, it has become much more of an easy 652 00:30:11,860 --> 00:30:14,530 task-- you can get a large amount of protein-- 653 00:30:14,530 --> 00:30:17,080 you want to turn to the pre-steady state. 654 00:30:17,080 --> 00:30:18,790 So what I want to do very briefly 655 00:30:18,790 --> 00:30:22,060 is discuss the pre-steady state. 656 00:30:22,060 --> 00:30:24,090 I asked you to think about-- 657 00:30:24,090 --> 00:30:25,550 I asked you draw this out. 658 00:30:25,550 --> 00:30:29,020 This is one of the talking points in the questions 659 00:30:29,020 --> 00:30:29,960 I handed out. 660 00:30:29,960 --> 00:30:34,220 But in the steady state, we're over here. 661 00:30:34,220 --> 00:30:37,330 And the pre-steady state is before we 662 00:30:37,330 --> 00:30:38,622 get to the steady state. 663 00:30:38,622 --> 00:30:40,080 And does anybody have any idea what 664 00:30:40,080 --> 00:30:43,900 timescale you are on in that region of the curve? 665 00:30:47,410 --> 00:30:48,222 Is it hours? 666 00:30:48,222 --> 00:30:49,180 AUDIENCE: Milliseconds? 667 00:30:49,180 --> 00:30:50,888 JOANNE STUBBE: Yes, so it's milliseconds. 668 00:30:50,888 --> 00:30:55,420 So, fortunately, this didn't necessarily have to be true-- 669 00:30:55,420 --> 00:30:58,790 most enzymatic reactions occur. 670 00:30:58,790 --> 00:31:02,950 the catalysis occurs in that time regime, or maybe 0.1 671 00:31:02,950 --> 00:31:05,050 milliseconds to milliseconds, allowing 672 00:31:05,050 --> 00:31:08,920 you to be able to use this method in an effort to try 673 00:31:08,920 --> 00:31:10,300 to understand what these-- 674 00:31:10,300 --> 00:31:12,110 evaluate what the rate constants are. 675 00:31:12,110 --> 00:31:16,510 And when you look at the table in the Rodnina paper, 676 00:31:16,510 --> 00:31:19,330 we're going to talk about where all those three constants came 677 00:31:19,330 --> 00:31:20,420 from, OK? 678 00:31:20,420 --> 00:31:22,430 Are they good or are they not good? 679 00:31:22,430 --> 00:31:25,120 But that's what you'd like to know for every system 680 00:31:25,120 --> 00:31:28,180 to really understand the question of fidelity, 681 00:31:28,180 --> 00:31:33,280 whether it's translation fidelity, DNA 682 00:31:33,280 --> 00:31:36,700 fidelity in replication, transcriptional fidelity. 683 00:31:36,700 --> 00:31:38,950 And you'll even see in Liz's section 684 00:31:38,950 --> 00:31:42,800 on polyketide syntases, which make natural products, 685 00:31:42,800 --> 00:31:46,130 you also have fidelity issues almost everywhere. 686 00:31:46,130 --> 00:31:48,280 So you'd like to be able to evaluate these things. 687 00:31:48,280 --> 00:31:50,446 And you can get a handle on this if you're a chemist 688 00:31:50,446 --> 00:31:53,680 and really care about the molecular details using 689 00:31:53,680 --> 00:31:54,710 potentially kinetics. 690 00:31:54,710 --> 00:31:58,630 So this is why kinetics is one of the first places 691 00:31:58,630 --> 00:32:01,870 that you actually start to think about what's 692 00:32:01,870 --> 00:32:03,520 going on in any reaction. 693 00:32:03,520 --> 00:32:07,930 OK, so let's say a few things about pre-steady state. 694 00:32:07,930 --> 00:32:10,550 I'm going to ask you a few questions, if I can remember 695 00:32:10,550 --> 00:32:12,120 what I'm going to ask you. 696 00:32:12,120 --> 00:32:18,360 OK, so OK, so let's suppose in this simple case, which I just 697 00:32:18,360 --> 00:32:26,250 covered up, this step is rate limiting, OK? 698 00:32:26,250 --> 00:32:27,600 So what is that step? 699 00:32:30,222 --> 00:32:32,980 Do you think it's common that a step like this-- 700 00:32:32,980 --> 00:32:34,270 so we have e plus s. 701 00:32:34,270 --> 00:32:36,760 And eventually, the enzyme gets recycled. 702 00:32:36,760 --> 00:32:38,780 I'm saying this is the rate-limiting step. 703 00:32:38,780 --> 00:32:42,000 Where is the chemical steps? 704 00:32:42,000 --> 00:32:44,632 Where are the chemical steps in this reaction? 705 00:32:44,632 --> 00:32:45,955 AUDIENCE: 2, 2. 706 00:32:45,955 --> 00:32:47,200 JOANNE STUBBE: Yeah, so k2. 707 00:32:47,200 --> 00:32:50,830 What are these steps over here, k1, and k minus 1, and k3? 708 00:32:50,830 --> 00:32:52,985 AUDIENCE: It's like association of the-- 709 00:32:52,985 --> 00:32:55,900 JOANNE STUBBE: Yeah, so the physical steps, OK? 710 00:32:55,900 --> 00:32:57,606 So as a chemist, and you're trying 711 00:32:57,606 --> 00:32:59,230 to understand what's going on, isn't it 712 00:32:59,230 --> 00:33:02,795 a problem if the rate limiting step is physical? 713 00:33:02,795 --> 00:33:05,440 It masks all the chemistry, OK? 714 00:33:05,440 --> 00:33:07,810 So what you see in this paper is they 715 00:33:07,810 --> 00:33:10,720 have to figure out clever ways to get around 716 00:33:10,720 --> 00:33:11,690 these kinds of issues. 717 00:33:11,690 --> 00:33:13,190 And you see that over and over again 718 00:33:13,190 --> 00:33:14,648 when you're studying enzyme systems 719 00:33:14,648 --> 00:33:18,680 because enzymes have have had billions of years to evolve. 720 00:33:18,680 --> 00:33:20,220 They are evolved. 721 00:33:20,220 --> 00:33:22,540 Their catalytic transformations are amazing. 722 00:33:22,540 --> 00:33:24,692 They go 10 to the 15th per second, right? 723 00:33:24,692 --> 00:33:25,900 That's totally mind boggling. 724 00:33:25,900 --> 00:33:28,390 Chemists can't come close. 725 00:33:28,390 --> 00:33:33,340 And so what happens then issued a limited by physical steps. 726 00:33:33,340 --> 00:33:36,250 So what we want to do is try and then 727 00:33:36,250 --> 00:33:39,310 look at the first part of this transformation. 728 00:33:39,310 --> 00:33:40,810 And basically, what we're then doing 729 00:33:40,810 --> 00:33:43,390 is using the enzyme sort of as a reagent. 730 00:33:43,390 --> 00:33:45,720 There are numbers of ways you can do this 731 00:33:45,720 --> 00:33:48,460 so that you can have a way of not looking 732 00:33:48,460 --> 00:33:50,410 at multiple turnovers because you can only 733 00:33:50,410 --> 00:33:53,920 look at one turnover if this is blocked 734 00:33:53,920 --> 00:33:55,870 in terms of product release. 735 00:33:55,870 --> 00:34:01,150 OK, so I think this product release 736 00:34:01,150 --> 00:34:03,600 is quite often the rate-limiting step 737 00:34:03,600 --> 00:34:05,440 in biological transformations. 738 00:34:05,440 --> 00:34:08,920 And what have you seen from reading the Rodnina paper? 739 00:34:08,920 --> 00:34:12,179 Have you seen conformational changes 740 00:34:12,179 --> 00:34:16,105 in thinking about the kinetic model we had up there before, 741 00:34:16,105 --> 00:34:19,396 and Liz had on the slide? 742 00:34:19,396 --> 00:34:23,444 Have you seen conformational changes? 743 00:34:23,444 --> 00:34:25,979 Is that part of the mechanism? 744 00:34:25,979 --> 00:34:27,270 Are they fast or are they slow? 745 00:34:31,420 --> 00:34:34,030 AUDIENCE: Wasn't that part of their reasoning 746 00:34:34,030 --> 00:34:38,880 that the difference between if you have a cognitive 747 00:34:38,880 --> 00:34:41,750 versus if you have a mismatched? 748 00:34:41,750 --> 00:34:45,146 That influences the rate of the reaction 749 00:34:45,146 --> 00:34:48,790 based on how it can affect the conformational change? 750 00:34:48,790 --> 00:34:51,980 JOANNE STUBBE: Wait, so that's exactly what's going to happen. 751 00:34:51,980 --> 00:34:53,239 So there are multiple places. 752 00:34:53,239 --> 00:34:54,613 How are you going to discriminate 753 00:34:54,613 --> 00:34:56,267 between two amino acids? 754 00:34:56,267 --> 00:34:58,100 Cognate and near cognate, whatever they are, 755 00:34:58,100 --> 00:35:01,190 will get to the data. 756 00:35:01,190 --> 00:35:03,180 The question is, how do you do that? 757 00:35:03,180 --> 00:35:05,240 And one of the steps is-- we talked 758 00:35:05,240 --> 00:35:07,690 about today GTP hydrolysis. 759 00:35:07,690 --> 00:35:13,220 But GTP hydrolysis is limited by a conformational change. 760 00:35:13,220 --> 00:35:17,240 And then once that go, the hydrolysis is very fast. 761 00:35:17,240 --> 00:35:21,050 And so it looks like the rate constant for GTP hydrolysis is 762 00:35:21,050 --> 00:35:24,080 the same as the rate constant for the conformational change. 763 00:35:24,080 --> 00:35:25,850 Where else have we seen a confirmation 764 00:35:25,850 --> 00:35:28,630 change the accommodation? 765 00:35:28,630 --> 00:35:29,396 AUDIENCE: Peptide. 766 00:35:29,396 --> 00:35:31,271 JOANNE STUBBE: Yeah, so peptide confirmation. 767 00:35:31,271 --> 00:35:33,580 This is shown here is this little cartoon 768 00:35:33,580 --> 00:35:36,400 where this red ball is the amino acid. 769 00:35:36,400 --> 00:35:40,640 It needs to reorient itself so it can form a peptide bond. 770 00:35:40,640 --> 00:35:45,910 So confirmation changes are all over the place in entomology. 771 00:35:45,910 --> 00:35:48,670 And if you look at the ribosome, do 772 00:35:48,670 --> 00:35:51,340 you think it's easy to tell with those conformational changes 773 00:35:51,340 --> 00:35:55,078 are from a molecular point of view? 774 00:35:55,078 --> 00:35:58,800 What do you think? 775 00:35:58,800 --> 00:36:00,950 Do you think it's easy or hard? 776 00:36:06,105 --> 00:36:06,730 AUDIENCE: Hard. 777 00:36:06,730 --> 00:36:07,850 JOANNE STUBBE: Very hard. 778 00:36:07,850 --> 00:36:10,220 OK, so here-- one of the most amazing things 779 00:36:10,220 --> 00:36:13,160 about the ribosome-- you've got to think this is amazing. 780 00:36:13,160 --> 00:36:16,820 You have this called the anti-codon loop way down here 781 00:36:16,820 --> 00:36:17,690 on the [INAUDIBLE]. 782 00:36:17,690 --> 00:36:21,160 And the GTPase is 80 angstroms away. 783 00:36:21,160 --> 00:36:24,170 And somehow, twiddling-- you saw this in class today-- 784 00:36:24,170 --> 00:36:26,920 these guys to form the right confirmation 785 00:36:26,920 --> 00:36:30,470 is transferred 80 Angstroms. 786 00:36:30,470 --> 00:36:33,722 And that triggers the reaction, rapid and irreversible. 787 00:36:33,722 --> 00:36:35,180 And the reaction goes to the right. 788 00:36:35,180 --> 00:36:39,200 You see this over and over and over again in these machines. 789 00:36:39,200 --> 00:36:42,650 OK, so this is a really important observation. 790 00:36:42,650 --> 00:36:44,520 How does that happen? 791 00:36:44,520 --> 00:36:46,370 Well, I think what's mindboggling 792 00:36:46,370 --> 00:36:48,500 about the ribosome-- again if you Google 793 00:36:48,500 --> 00:36:50,930 ribosome and elongation, you'll see 794 00:36:50,930 --> 00:36:53,900 we have another 150 papers published where people 795 00:36:53,900 --> 00:36:56,660 are trying to sort out-- because we have cryoem structures, 796 00:36:56,660 --> 00:37:01,760 we have stagnant crystallographic structures, 797 00:37:01,760 --> 00:37:03,650 we have single molecule stuff now. 798 00:37:03,650 --> 00:37:06,350 On top of all this model we have from Rodnina, 799 00:37:06,350 --> 00:37:08,360 people are trying to sort all those out 800 00:37:08,360 --> 00:37:11,450 because they care about how it works in some detail. 801 00:37:11,450 --> 00:37:14,540 So who ever would have thought we could get to the stage 802 00:37:14,540 --> 00:37:15,660 where we-- 803 00:37:15,660 --> 00:37:18,380 you've seen the pictures you saw in class today. 804 00:37:18,380 --> 00:37:20,730 Those pictures-- when I was your age, 805 00:37:20,730 --> 00:37:23,280 do you know how many structures there were? 806 00:37:23,280 --> 00:37:25,040 Maybe three. 807 00:37:25,040 --> 00:37:26,480 OK, we had hemoglobin. 808 00:37:26,480 --> 00:37:27,570 We had chymotrypsin. 809 00:37:27,570 --> 00:37:29,100 There were no structures. 810 00:37:29,100 --> 00:37:30,260 And why was that true? 811 00:37:30,260 --> 00:37:32,510 Because we had no molecular biology. 812 00:37:32,510 --> 00:37:34,430 So I used to spend three-- 813 00:37:34,430 --> 00:37:35,097 I'm digressing. 814 00:37:35,097 --> 00:37:36,430 This happens to me all the time. 815 00:37:36,430 --> 00:37:37,790 You're going to hate me for this. 816 00:37:37,790 --> 00:37:39,248 I'm going to get hammered for this. 817 00:37:39,248 --> 00:37:43,370 But I used to spend three months in the cold room isolating 818 00:37:43,370 --> 00:37:45,770 a microgram or protein, OK? 819 00:37:45,770 --> 00:37:48,290 And then molecular biology came in. 820 00:37:48,290 --> 00:37:50,040 And it's still not easy. 821 00:37:50,040 --> 00:37:51,890 And Liz will tell you what the issues are 822 00:37:51,890 --> 00:37:53,210 with purification of protein. 823 00:37:53,210 --> 00:37:56,150 But you can get grams of protein now in a day, OK? 824 00:37:56,150 --> 00:37:57,470 So there's been a revolution. 825 00:37:57,470 --> 00:38:02,000 And that allowed these crystallographic-- 826 00:38:02,000 --> 00:38:04,400 a pure material that crystallized more readily. 827 00:38:04,400 --> 00:38:07,610 And then the technology on top of that has really 828 00:38:07,610 --> 00:38:10,514 revolutionized what you can do. 829 00:38:10,514 --> 00:38:11,930 I think it's a very exciting time. 830 00:38:11,930 --> 00:38:14,360 And I think any of you who want to be biochemists, 831 00:38:14,360 --> 00:38:17,220 or are thinking about drug design, 832 00:38:17,220 --> 00:38:19,590 you really need to learn how to look at structures. 833 00:38:19,590 --> 00:38:20,900 So that was the first module. 834 00:38:20,900 --> 00:38:22,430 It takes a lot of practice. 835 00:38:22,430 --> 00:38:24,650 You need to figure that all out. 836 00:38:24,650 --> 00:38:28,060 OK, so pre-steady state-- so we're going 837 00:38:28,060 --> 00:38:29,885 to look at pre-steady state. 838 00:38:29,885 --> 00:38:38,180 And the goal is to evaluate the individual rate constants. 839 00:38:41,200 --> 00:38:42,320 OK, so that's the goal. 840 00:38:42,320 --> 00:38:47,250 And you may or may not be able to achieve this goal. 841 00:38:47,250 --> 00:38:53,210 But this happens, we just said, on the millisecond timescale. 842 00:38:53,210 --> 00:38:55,760 And so one of the questions-- and we're 843 00:38:55,760 --> 00:38:57,500 doing this under single turnover. 844 00:39:01,260 --> 00:39:04,295 OK, so let's look at a simple-- 845 00:39:04,295 --> 00:39:06,420 and we've just talked about it in the steady state. 846 00:39:06,420 --> 00:39:07,860 The concentration of the substrate 847 00:39:07,860 --> 00:39:09,984 has to be much, much greater than the concentration 848 00:39:09,984 --> 00:39:10,650 of the enzyme. 849 00:39:10,650 --> 00:39:12,930 And the enzyme concentrations are really low. 850 00:39:12,930 --> 00:39:19,020 So let's say we have an enzyme concentration of 0.01 851 00:39:19,020 --> 00:39:21,870 micromolar, OK? 852 00:39:21,870 --> 00:39:23,610 So that's our enzyme concentration. 853 00:39:23,610 --> 00:39:25,193 And that would be typical if you would 854 00:39:25,193 --> 00:39:28,780 be using in a steady state assay if you have done those. 855 00:39:28,780 --> 00:39:32,160 And let's say that we're going to monitor this reaction 856 00:39:32,160 --> 00:39:35,351 by some kind of absorption change, a unique absorption 857 00:39:35,351 --> 00:39:35,850 change. 858 00:39:35,850 --> 00:39:40,750 So we're looking at absorption at some wavelength, OK? 859 00:39:40,750 --> 00:39:42,960 And let's say the extinction coefficient for this 860 00:39:42,960 --> 00:39:47,190 is 10 to the 4 per molar per centimeter. 861 00:39:47,190 --> 00:39:50,070 It would be ATP or coA. 862 00:39:50,070 --> 00:39:52,440 Then you can ask yourself the question, 863 00:39:52,440 --> 00:39:54,970 under these conditions, the change in absorption 864 00:39:54,970 --> 00:39:56,940 at whatever this wavelength is, is 865 00:39:56,940 --> 00:40:00,750 equal to the path length of light in centimeters times 10 866 00:40:00,750 --> 00:40:08,830 to the minus 8th molar times 10 to the fourth molar 867 00:40:08,830 --> 00:40:10,986 per centimeter. 868 00:40:10,986 --> 00:40:13,120 OK, so what would your change in absorption 869 00:40:13,120 --> 00:40:16,654 be if you were measuring this in a single turnover? 870 00:40:16,654 --> 00:40:21,690 It would be really, really small, 0.0001. 871 00:40:21,690 --> 00:40:23,520 Can you measure that? 872 00:40:23,520 --> 00:40:26,790 Maybe you could measure this if you took hundreds of samples 873 00:40:26,790 --> 00:40:28,930 and you did a statistical analysis on it. 874 00:40:28,930 --> 00:40:30,450 But it's really low. 875 00:40:30,450 --> 00:40:33,510 So what do you want to do then to do pretty steady state? 876 00:40:33,510 --> 00:40:36,800 What's the thing to change so that you 877 00:40:36,800 --> 00:40:38,490 will be able to see something? 878 00:40:38,490 --> 00:40:39,410 AUDIENCE: [INAUDIBLE]. 879 00:40:39,410 --> 00:40:43,110 JOANNE STUBBE: Yeah, so you increase. 880 00:40:43,110 --> 00:40:45,650 So when you have this, and you can't see something-- 881 00:40:45,650 --> 00:40:48,422 and, obviously, it depends on what this extinction 882 00:40:48,422 --> 00:40:50,630 coefficient is-- but this is a pretty high extinction 883 00:40:50,630 --> 00:40:52,480 coefficient. 884 00:40:52,480 --> 00:40:58,450 So what you do is you increase the concentration of enzyme. 885 00:40:58,450 --> 00:41:03,315 And if we increase it, say, 1,000 fold, then then 886 00:41:03,315 --> 00:41:05,670 so we're now at 10 to the minus 5. 887 00:41:05,670 --> 00:41:08,790 Then now what is the change in absorption? 888 00:41:08,790 --> 00:41:10,890 The change in absorption is 0.1, which 889 00:41:10,890 --> 00:41:13,920 you can measure fairly easily in any kind 890 00:41:13,920 --> 00:41:16,230 of current instrumentation. 891 00:41:16,230 --> 00:41:19,420 So the thing is you have to be able to see. 892 00:41:19,420 --> 00:41:22,080 So the key thing with pre-steady state, 893 00:41:22,080 --> 00:41:25,310 and the reason you need to have large amounts of enzyme, 894 00:41:25,310 --> 00:41:28,200 is you need to be able to see what you're monitoring. 895 00:41:28,200 --> 00:41:29,970 So it's all about sensitivity. 896 00:41:34,490 --> 00:41:37,290 You need to see. 897 00:41:37,290 --> 00:41:42,920 And this usually implies increasing the concentration 898 00:41:42,920 --> 00:41:43,860 of the enzyme. 899 00:41:43,860 --> 00:41:46,730 OK, so what's the problem if you increase the concentration 900 00:41:46,730 --> 00:41:47,380 of the enzyme? 901 00:41:49,950 --> 00:41:54,330 Say we normally are at 0.01 micromolar steady state. 902 00:41:54,330 --> 00:41:57,970 We now are at 1,000 times higher. 903 00:41:57,970 --> 00:42:03,946 What's going to happen that makes the analysis complicated? 904 00:42:08,230 --> 00:42:10,390 If you increase the concentration of the enzyme, 905 00:42:10,390 --> 00:42:11,434 what does that do? 906 00:42:11,434 --> 00:42:13,100 AUDIENCE: You're going to burn through-- 907 00:42:13,100 --> 00:42:14,307 [INTERPOSING VOICES] 908 00:42:14,307 --> 00:42:15,890 JOANNE STUBBE: You're going to-- yeah, 909 00:42:15,890 --> 00:42:17,690 it increases the rate of the reaction 910 00:42:17,690 --> 00:42:19,430 because the rate of the reaction is 911 00:42:19,430 --> 00:42:22,070 proportional to the concentration of your catalyst. 912 00:42:22,070 --> 00:42:23,720 If you don't remember anything else out 913 00:42:23,720 --> 00:42:26,660 of this course, or anything in chemistry, 914 00:42:26,660 --> 00:42:30,380 that's pretty important no matter what area of chemistry 915 00:42:30,380 --> 00:42:31,400 you're in. 916 00:42:31,400 --> 00:42:34,850 So now what happens is the reaction 917 00:42:34,850 --> 00:42:38,960 is going like a bat out of hell instead of pipetting by hand. 918 00:42:38,960 --> 00:42:41,030 By the time you pipetted and put this 919 00:42:41,030 --> 00:42:44,030 into however you're observing it in the spectrophotometer, 920 00:42:44,030 --> 00:42:46,290 reaction's over, OK? 921 00:42:46,290 --> 00:42:48,240 So that's what the issue is, OK? 922 00:42:48,240 --> 00:42:51,645 So the sensitivity is key. 923 00:42:51,645 --> 00:42:53,770 And then the second thing you need to think about-- 924 00:42:53,770 --> 00:42:55,719 so sensitivity is one thing. 925 00:42:55,719 --> 00:42:57,510 And the other thing you need to think about 926 00:42:57,510 --> 00:43:02,460 is, what are the limitations of this method? 927 00:43:02,460 --> 00:43:04,770 How fast can the rate come-- 928 00:43:04,770 --> 00:43:06,810 on the millisecond timescale, what 929 00:43:06,810 --> 00:43:09,780 are the limitations in terms of the rate constants 930 00:43:09,780 --> 00:43:11,710 you can actually measure? 931 00:43:11,710 --> 00:43:13,740 So when you're looking at these reactions, 932 00:43:13,740 --> 00:43:18,080 you're looking at, in general, first order reactions. 933 00:43:18,080 --> 00:43:20,700 So all of these take place on the enzyme. 934 00:43:20,700 --> 00:43:23,410 So everything is stuck on the enzyme. 935 00:43:23,410 --> 00:43:25,030 So it's all first order. 936 00:43:25,030 --> 00:43:28,800 So the half life of the reaction is, if you go back 937 00:43:28,800 --> 00:43:30,730 and you look at your introductory kinetics, 938 00:43:30,730 --> 00:43:35,520 is 0.693 divided by k observed. 939 00:43:35,520 --> 00:43:42,670 And so if you had, say, a rate constant of 500 per second, 940 00:43:42,670 --> 00:43:47,734 then that gives you a half life of 1.5 milliseconds, OK? 941 00:43:47,734 --> 00:43:50,150 So that means you have to be able to make your measurement 942 00:43:50,150 --> 00:43:52,230 faster than that, OK? 943 00:43:52,230 --> 00:43:54,380 So the instrumentation we're going to be using 944 00:43:54,380 --> 00:43:55,890 can't do that. 945 00:43:55,890 --> 00:43:58,330 So the instrumentation we're doing-- 946 00:43:58,330 --> 00:44:01,910 so this would give you a half life if you calculate this. 947 00:44:01,910 --> 00:44:04,740 I don't even remember what the number is. 948 00:44:04,740 --> 00:44:10,610 But the dead time of the instruments 949 00:44:10,610 --> 00:44:13,490 that you would be using to make pre-steady state kinetics 950 00:44:13,490 --> 00:44:16,940 is approximately 2 milliseconds. 951 00:44:16,940 --> 00:44:20,650 So by the time you could stop looking 952 00:44:20,650 --> 00:44:23,710 at the reaction in some form, you know more than 50% 953 00:44:23,710 --> 00:44:25,900 of the reaction is gone, OK? 954 00:44:25,900 --> 00:44:30,310 So the rate constant then limits also what you can measure. 955 00:44:30,310 --> 00:44:33,580 So we asked this question before-- how could you 956 00:44:33,580 --> 00:44:35,900 modify this rate constant? 957 00:44:35,900 --> 00:44:37,690 What could you actually do? 958 00:44:41,000 --> 00:44:42,590 How could you make it so you might 959 00:44:42,590 --> 00:44:45,290 be able to say your rate consent was 500 per second-- 960 00:44:45,290 --> 00:44:47,240 you missed more than half your reaction. 961 00:44:47,240 --> 00:44:50,120 What could you potentially do so that you could 962 00:44:50,120 --> 00:44:51,854 monitor more of the reaction? 963 00:44:51,854 --> 00:44:53,645 What's the parameter that you would change? 964 00:44:58,330 --> 00:44:59,300 Kinetics. 965 00:44:59,300 --> 00:45:00,210 Think about kinetics. 966 00:45:00,210 --> 00:45:02,588 What do you always control in kinetics? 967 00:45:02,588 --> 00:45:04,004 AUDIENCE: Substrate concentration. 968 00:45:04,004 --> 00:45:05,530 JOANNE STUBBE: OK, you can control 969 00:45:05,530 --> 00:45:07,210 substrate concentration, but that's not 970 00:45:07,210 --> 00:45:08,670 the one I'm looking for. 971 00:45:08,670 --> 00:45:09,610 AUDIENCE: Temperature? 972 00:45:09,610 --> 00:45:10,460 JOANNE STUBBE: Temperature. 973 00:45:10,460 --> 00:45:10,959 Yeah. 974 00:45:10,959 --> 00:45:15,370 So in our body, we're at 37 degrees. 975 00:45:15,370 --> 00:45:18,400 That really is where you want to be making 976 00:45:18,400 --> 00:45:20,290 all of your measurements. 977 00:45:20,290 --> 00:45:22,270 In reality, many of the measurements 978 00:45:22,270 --> 00:45:24,050 are right on the edge. 979 00:45:24,050 --> 00:45:26,210 And so if you read the papers carefully, 980 00:45:26,210 --> 00:45:29,260 you'll see that people do lower the temperature, 981 00:45:29,260 --> 00:45:31,150 and that the rate of the reaction 982 00:45:31,150 --> 00:45:34,309 is related to the temperature. 983 00:45:34,309 --> 00:45:36,350 What's the problem with lowering the temperature? 984 00:45:36,350 --> 00:45:38,100 These are all things just you got to think 985 00:45:38,100 --> 00:45:39,420 about in the back of your mind. 986 00:45:39,420 --> 00:45:42,040 They're all playoffs in terms of how bad you 987 00:45:42,040 --> 00:45:45,130 want your experimental data and what the issues are 988 00:45:45,130 --> 00:45:47,840 with interpretation of data. 989 00:45:47,840 --> 00:45:48,370 Yeah? 990 00:45:48,370 --> 00:45:48,870 Rebecca. 991 00:45:48,870 --> 00:45:50,058 AUDIENCE: It makes it difficult to compare 992 00:45:50,058 --> 00:45:50,654 the different values. 993 00:45:50,654 --> 00:45:52,211 And you might not know exactly what 994 00:45:52,211 --> 00:45:54,086 the relationship between temperature and rate 995 00:45:54,086 --> 00:45:55,515 is, like if scales linearly. 996 00:45:55,515 --> 00:45:56,530 JOANNE STUBBE: OK, so that's true. 997 00:45:56,530 --> 00:45:58,321 You could have a huge conformational change 998 00:45:58,321 --> 00:46:01,840 that doesn't have erroneous behavior. 999 00:46:01,840 --> 00:46:04,210 I think quite frequently, most enzymes, they're 1000 00:46:04,210 --> 00:46:05,960 designed to work at 37 degrees. 1001 00:46:05,960 --> 00:46:08,822 And when you start cooling them down, they do weird things. 1002 00:46:08,822 --> 00:46:10,280 So you could make the measurements, 1003 00:46:10,280 --> 00:46:11,660 but then you have this issue-- 1004 00:46:11,660 --> 00:46:13,285 I think, which is what you were saying, 1005 00:46:13,285 --> 00:46:15,010 of how do you extrapolate that? 1006 00:46:15,010 --> 00:46:17,272 So a lot of times you will change the temperature 1007 00:46:17,272 --> 00:46:19,730 because that's the only way you could make the measurement. 1008 00:46:19,730 --> 00:46:21,700 But the caveat is, like with everything, 1009 00:46:21,700 --> 00:46:25,480 that you need to think about what the consequences of that 1010 00:46:25,480 --> 00:46:26,430 actually are. 1011 00:46:26,430 --> 00:46:32,440 OK, so the methods that we're going to be using Liz already 1012 00:46:32,440 --> 00:46:38,335 introduced you to in class, not today, but the previous time. 1013 00:46:38,335 --> 00:46:41,200 And so what you want to do, since you can't pipette 1014 00:46:41,200 --> 00:46:44,470 on the millisecond time scale by hand, 1015 00:46:44,470 --> 00:46:46,600 you want to have an instrument that 1016 00:46:46,600 --> 00:46:53,380 allows you to control the rate of reaction 1017 00:46:53,380 --> 00:46:58,070 by-- you put two different things in your syringes. 1018 00:46:58,070 --> 00:46:59,620 And then you have an instrument-- 1019 00:46:59,620 --> 00:47:03,770 push the two syringes into a chamber where they're mixed. 1020 00:47:03,770 --> 00:47:05,830 Do you know what the rate-limiting step 1021 00:47:05,830 --> 00:47:07,440 in this process is? 1022 00:47:07,440 --> 00:47:09,580 It's the mixing process, OK? 1023 00:47:09,580 --> 00:47:13,360 So the mixing processes is 2-millisecond dead time. 1024 00:47:13,360 --> 00:47:16,810 I don't know if any of you have ever mixed something viscus 1025 00:47:16,810 --> 00:47:18,250 with something not so viscus? 1026 00:47:18,250 --> 00:47:20,706 What do you see? 1027 00:47:20,706 --> 00:47:24,640 Have you ever made up a solution of glycerol? 1028 00:47:24,640 --> 00:47:26,580 No? 1029 00:47:26,580 --> 00:47:29,470 They probably give you all this in a kit nowadays. 1030 00:47:29,470 --> 00:47:31,320 You don't have to make up your solutions 1031 00:47:31,320 --> 00:47:34,730 of glycerol aluminum anymore. 1032 00:47:34,730 --> 00:47:36,730 So this goes back to experimental design. 1033 00:47:36,730 --> 00:47:39,410 And I'm not here to teach you how to do experimental design. 1034 00:47:39,410 --> 00:47:41,925 But if you had very high concentration of the enzyme-- 1035 00:47:41,925 --> 00:47:44,050 because we need a lot to be able to see something-- 1036 00:47:44,050 --> 00:47:46,080 and you're mixing it against substrate-- 1037 00:47:46,080 --> 00:47:49,170 you have something very viscous and something not viscous-- 1038 00:47:49,170 --> 00:47:52,840 and when you mix them it takes a lot longer 1039 00:47:52,840 --> 00:47:56,140 to remove all the lines from the mixing process. 1040 00:47:56,140 --> 00:47:59,950 So experimental design, you really 1041 00:47:59,950 --> 00:48:01,780 need to do some thinking about that. 1042 00:48:01,780 --> 00:48:05,980 Once it gets into the mixer, the liquid in the mixer 1043 00:48:05,980 --> 00:48:08,403 pushes a third syringe back. 1044 00:48:08,403 --> 00:48:11,590 It fills the syringe up with liquid. 1045 00:48:11,590 --> 00:48:14,860 It hits some kind of a stop position, which 1046 00:48:14,860 --> 00:48:16,865 then triggers detection, OK? 1047 00:48:16,865 --> 00:48:18,240 So that's what you're looking at. 1048 00:48:18,240 --> 00:48:22,640 And the beauty of this method is it's continuous. 1049 00:48:22,640 --> 00:48:26,080 And so what do you have to do to be able to look at this? 1050 00:48:26,080 --> 00:48:29,320 What did they do in the case of the Rodnina paper? 1051 00:48:29,320 --> 00:48:32,980 What kind of method did they use? 1052 00:48:32,980 --> 00:48:34,520 Did you think about that? 1053 00:48:34,520 --> 00:48:36,440 They described it, but you might not 1054 00:48:36,440 --> 00:48:39,780 have thought about it in terms of experimental design. 1055 00:48:39,780 --> 00:48:41,287 How did they monitor their reaction, 1056 00:48:41,287 --> 00:48:42,245 one of their reactions? 1057 00:48:42,245 --> 00:48:44,340 AUDIENCE: [INAUDIBLE]. 1058 00:48:44,340 --> 00:48:46,340 JOANNE STUBBE: Yeah, so they are going 1059 00:48:46,340 --> 00:48:48,550 to be able to somehow tag-- 1060 00:48:48,550 --> 00:48:51,220 and this is a key thing, is how do you tag something 1061 00:48:51,220 --> 00:48:52,750 in the right place so you can see 1062 00:48:52,750 --> 00:48:54,130 a unique fluorescent change? 1063 00:48:54,130 --> 00:48:55,990 That's not so easy, OK? 1064 00:48:55,990 --> 00:48:57,610 So you mix this. 1065 00:48:57,610 --> 00:48:59,920 You can monitor this continuously 1066 00:48:59,920 --> 00:49:01,210 by change in fluorescence. 1067 00:49:01,210 --> 00:49:05,620 If you had something that has a visible absorption, 1068 00:49:05,620 --> 00:49:08,785 could you use that? 1069 00:49:08,785 --> 00:49:10,620 What would limit that? 1070 00:49:10,620 --> 00:49:14,670 Say, if you looked at tRNA synthetases 1071 00:49:14,670 --> 00:49:17,670 that you talked about in class two times ago, 1072 00:49:17,670 --> 00:49:22,140 where you were looking at ATP that isolates the amino acid 1073 00:49:22,140 --> 00:49:24,870 to form the adenylate, which then reacts with the tRNA, 1074 00:49:24,870 --> 00:49:25,950 could you use-- 1075 00:49:25,950 --> 00:49:28,170 ATP as an absorption at 260. 1076 00:49:28,170 --> 00:49:32,490 Could you use that absorption change? 1077 00:49:32,490 --> 00:49:35,640 Do you remember what that equation is? 1078 00:49:35,640 --> 00:49:38,760 Do you remember installation of amino acid? 1079 00:49:38,760 --> 00:49:41,677 You're going to see this again in polyketide syntases. 1080 00:49:41,677 --> 00:49:43,260 It's used quite frequently in biology. 1081 00:49:47,180 --> 00:49:49,360 Nobody has any idea? 1082 00:49:49,360 --> 00:49:51,970 Nebraska, how about you? 1083 00:49:51,970 --> 00:49:57,350 OK, so here we have amino acid plus ATP. 1084 00:49:57,350 --> 00:49:58,310 I'm digressing. 1085 00:49:58,310 --> 00:50:00,010 But if you learn this part, you've 1086 00:50:00,010 --> 00:50:02,410 learned something out of all of this, 1087 00:50:02,410 --> 00:50:04,570 that forms the acyl adenylate. 1088 00:50:08,728 --> 00:50:11,625 OK, how did they monitor this reaction? 1089 00:50:11,625 --> 00:50:14,884 You discussed this in class. 1090 00:50:14,884 --> 00:50:16,300 How do they monitor this reaction? 1091 00:50:18,905 --> 00:50:19,840 AUDIENCE: [INAUDIBLE]. 1092 00:50:19,840 --> 00:50:21,465 JOANNE STUBBE: You need to talk louder. 1093 00:50:21,465 --> 00:50:22,674 You need to be assertive, OK? 1094 00:50:22,674 --> 00:50:23,589 AUDIENCE: [INAUDIBLE]. 1095 00:50:23,589 --> 00:50:24,442 JOANNE STUBBE: Yeah. 1096 00:50:24,442 --> 00:50:26,650 So we're going to talk about radioactivity next time. 1097 00:50:26,650 --> 00:50:28,191 This will be one of the methods we're 1098 00:50:28,191 --> 00:50:30,700 going to be introduced to. 1099 00:50:30,700 --> 00:50:34,650 Why couldn't they use ATP? 1100 00:50:34,650 --> 00:50:37,150 AUDIENCE: The absorbent's different between [INAUDIBLE].. 1101 00:50:37,150 --> 00:50:38,590 JOANNE STUBBE: Yeah, they're the same. 1102 00:50:38,590 --> 00:50:39,089 Yeah. 1103 00:50:39,089 --> 00:50:42,010 So you have to have a difference in absorption 1104 00:50:42,010 --> 00:50:43,930 to be able to measure the visible. 1105 00:50:43,930 --> 00:50:48,190 So the total absorption is due to the adenosine moiety which 1106 00:50:48,190 --> 00:50:49,720 is the same in both molecules. 1107 00:50:49,720 --> 00:50:52,090 OK, so you can't do that, OK? 1108 00:50:52,090 --> 00:50:53,170 So that's one. 1109 00:50:53,170 --> 00:50:56,620 And then let me just do one more thing, and then we'll quit. 1110 00:50:56,620 --> 00:50:59,770 I still have another minute according to my watch. 1111 00:50:59,770 --> 00:51:03,100 OK, so the second method, which they also 1112 00:51:03,100 --> 00:51:07,150 used in the Rodnina paper is rapid chemical quench, OK? 1113 00:51:07,150 --> 00:51:08,890 So, again, you have two things. 1114 00:51:08,890 --> 00:51:10,150 You mix them. 1115 00:51:10,150 --> 00:51:13,210 There's some plunger that allows the mixing. 1116 00:51:13,210 --> 00:51:16,120 And then this is a discontinuous method. 1117 00:51:16,120 --> 00:51:18,370 So what happens is you mix. 1118 00:51:18,370 --> 00:51:21,650 And then you have to stop the reaction, OK? 1119 00:51:21,650 --> 00:51:24,850 So you have a third syringe where you mix in something 1120 00:51:24,850 --> 00:51:27,102 to stop the reaction. 1121 00:51:27,102 --> 00:51:29,560 And then you have to analyze what comes out the other side. 1122 00:51:29,560 --> 00:51:32,470 And this is where they're going to use radioactivity. 1123 00:51:32,470 --> 00:51:34,750 And so this is rapid chemical quench. 1124 00:51:37,425 --> 00:51:42,390 And how can you monitor a rapid chemical quench experiment? 1125 00:51:42,390 --> 00:51:45,280 What's the best way to stop the reaction? 1126 00:51:45,280 --> 00:51:47,130 What did they do in this paper? 1127 00:51:47,130 --> 00:51:48,930 How else could you stop the reaction? 1128 00:51:48,930 --> 00:51:50,100 Anybody got any ideas? 1129 00:51:56,409 --> 00:51:58,200 So what what's the first criteria if you're 1130 00:51:58,200 --> 00:51:59,324 going to stop the reaction? 1131 00:51:59,324 --> 00:52:03,440 What does it have to be able to do? 1132 00:52:03,440 --> 00:52:05,160 You just can't throw in anything, right? 1133 00:52:05,160 --> 00:52:08,721 What is the key criteria for successful stopping? 1134 00:52:08,721 --> 00:52:10,304 AUDIENCE: Something that will turn off 1135 00:52:10,304 --> 00:52:11,410 the catalytic activity? 1136 00:52:11,410 --> 00:52:12,270 JOANNE STUBBE: Yeah. 1137 00:52:12,270 --> 00:52:14,850 And it has to be able to do it on a millisecond timescale. 1138 00:52:14,850 --> 00:52:17,070 So you need millisecond stopping. 1139 00:52:20,954 --> 00:52:22,140 OK, how could you millisec? 1140 00:52:22,140 --> 00:52:24,140 How could you stop something on the millisecond? 1141 00:52:24,140 --> 00:52:24,980 What would you use? 1142 00:52:24,980 --> 00:52:26,330 Anybody got any ideas? 1143 00:52:26,330 --> 00:52:28,304 So this is not trivial, actually. 1144 00:52:28,304 --> 00:52:29,720 AUDIENCE: You could change the pH? 1145 00:52:29,720 --> 00:52:31,386 JOANNE STUBBE: Yeah, so changing the pH. 1146 00:52:31,386 --> 00:52:33,540 But so you could go acid or base. 1147 00:52:33,540 --> 00:52:35,250 Acid works. 1148 00:52:35,250 --> 00:52:37,110 In general, base doesn't work. 1149 00:52:37,110 --> 00:52:40,460 So if you read the handout that I've given you, it does work. 1150 00:52:40,460 --> 00:52:42,500 But it's much, much, much slower. 1151 00:52:42,500 --> 00:52:43,880 And every base is different. 1152 00:52:43,880 --> 00:52:45,620 Acid works all the time. 1153 00:52:45,620 --> 00:52:47,210 There's another thing that you can 1154 00:52:47,210 --> 00:52:49,440 use that is quite frequently used, 1155 00:52:49,440 --> 00:52:53,630 especially with polymerases that work on nucleic acids. 1156 00:52:53,630 --> 00:52:55,070 And that's EDTA. 1157 00:52:55,070 --> 00:53:01,010 So this is a chelator and EDTA chelates the metal, which 1158 00:53:01,010 --> 00:53:03,420 is essential for viability. 1159 00:53:03,420 --> 00:53:05,450 So that also-- the chelation can occur 1160 00:53:05,450 --> 00:53:07,130 in the millisecond timescale. 1161 00:53:07,130 --> 00:53:08,630 So what we're going to do next time, 1162 00:53:08,630 --> 00:53:10,796 I've sort of introduced you to the pre-steady state. 1163 00:53:10,796 --> 00:53:12,090 The next time we'll come in. 1164 00:53:12,090 --> 00:53:14,270 And we're going to look at the actual experiments. 1165 00:53:14,270 --> 00:53:15,560 We'll look at fluorescence. 1166 00:53:15,560 --> 00:53:18,470 We'll look at radioactivity and how you measure radioactivity. 1167 00:53:18,470 --> 00:53:20,150 We're going to look at antibiotics, 1168 00:53:20,150 --> 00:53:21,380 like you talked about today. 1169 00:53:21,380 --> 00:53:25,430 We're going to look at non-hydrolyzable GTP analogs. 1170 00:53:25,430 --> 00:53:26,990 If you look carefully at this paper, 1171 00:53:26,990 --> 00:53:29,540 it's amazing how many methods they used 1172 00:53:29,540 --> 00:53:30,930 to come up with this model. 1173 00:53:30,930 --> 00:53:33,160 And that's one of the take home messages 1174 00:53:33,160 --> 00:53:36,230 that you have to use many, many methods. 1175 00:53:36,230 --> 00:53:39,510 And then you never get an exact solution to your equations. 1176 00:53:39,510 --> 00:53:41,990 It's numerical integration of all the data 1177 00:53:41,990 --> 00:53:46,510 that leads you to the model that they've actually used, OK?