1 00:00:00,000 --> 00:00:02,400 The following content is provided under a Creative 2 00:00:02,400 --> 00:00:03,810 Commons license. 3 00:00:03,810 --> 00:00:06,840 Your support will help MIT OpenCourseWare continue to 4 00:00:06,840 --> 00:00:10,520 offer high quality educational resources for free. 5 00:00:10,520 --> 00:00:13,390 To make a donation or view additional materials from 6 00:00:13,390 --> 00:00:17,580 hundreds of MIT courses, visit MIT OpenCourseWare at 7 00:00:17,580 --> 00:00:20,800 ocw.mit.edu. 8 00:00:20,800 --> 00:00:26,940 PROFESSOR: So today we're going to do an example of 9 00:00:26,940 --> 00:00:34,780 using some of the equilibrium concepts that we've learned to 10 00:00:34,780 --> 00:00:36,370 drug design. 11 00:00:36,370 --> 00:00:38,890 And it's going to be an example that's out in the 12 00:00:38,890 --> 00:00:39,410 literature. 13 00:00:39,410 --> 00:00:44,210 And potentially a very big deal if you can do 14 00:00:44,210 --> 00:00:46,220 drug design this way. 15 00:00:46,220 --> 00:00:49,920 And it's an example of how, remember how I told you that 16 00:00:49,920 --> 00:00:52,680 if you have the Gibbs free energy, you have everything 17 00:00:52,680 --> 00:00:56,730 and how clueless I was as a graduate student, and when I 18 00:00:56,730 --> 00:01:00,130 look back I think how silly it was for me not to realize how 19 00:01:00,130 --> 00:01:01,050 important it was. 20 00:01:01,050 --> 00:01:04,750 Well, this is an example where people calculate delta G's or 21 00:01:04,750 --> 00:01:08,720 Gibbs free energy changes for binding of proteins to 22 00:01:08,720 --> 00:01:10,450 receptors on cells, or ligands. 23 00:01:10,450 --> 00:01:14,830 And from that, design drugs that work much better than the 24 00:01:14,830 --> 00:01:15,610 real thing. 25 00:01:15,610 --> 00:01:19,330 And it's all about calculating delta G. We're going to see 26 00:01:19,330 --> 00:01:23,580 how that is, and how that comes in with equilibrium. 27 00:01:23,580 --> 00:01:27,070 So the paper that this is based on was 28 00:01:27,070 --> 00:01:28,230 published in 2002. 29 00:01:28,230 --> 00:01:33,240 And since then there have been larger-scale 30 00:01:33,240 --> 00:01:34,600 trials, animal trials. 31 00:01:34,600 --> 00:01:39,010 And I believe there have been human trials of this concept, 32 00:01:39,010 --> 00:01:42,420 of this drug that they have designed. 33 00:01:42,420 --> 00:01:47,540 You've got the reference in the notes. 34 00:01:47,540 --> 00:01:51,580 And we're going to have to do a little bit of review of 35 00:01:51,580 --> 00:01:58,730 biology first, to figure out what's going on. 36 00:01:58,730 --> 00:02:08,340 And this particular process, this particular drug, is 37 00:02:08,340 --> 00:02:11,650 called the, I have it right here, 38 00:02:11,650 --> 00:02:13,920 granulocyte stimulating factor. 39 00:02:13,920 --> 00:02:15,880 Where was it in here? 40 00:02:15,880 --> 00:02:32,040 To give you the right name for it. 41 00:02:32,040 --> 00:02:35,680 There it is. 42 00:02:35,680 --> 00:02:40,300 It's a protein drug called GCSF. 43 00:02:40,300 --> 00:02:43,270 Granulocyte Colony Stimulating Factor. 44 00:02:43,270 --> 00:02:48,280 And it's there's wild tie for natural 45 00:02:48,280 --> 00:02:49,940 version of this protein. 46 00:02:49,940 --> 00:02:54,520 That is generated by normal tissue. 47 00:02:54,520 --> 00:03:01,230 And this protein goes to the blood, to the bone marrow. 48 00:03:01,230 --> 00:03:05,320 And it binds the receptors on cells that are in the blood 49 00:03:05,320 --> 00:03:07,800 and the bone marrow, and stimulates the growth of white 50 00:03:07,800 --> 00:03:13,650 blood cells, and stem cells, and also acts to tell the bone 51 00:03:13,650 --> 00:03:19,630 marrow to pump out these stem cells into the blood. 52 00:03:19,630 --> 00:03:26,260 And the problem is that if you have a chemotherapy patient, 53 00:03:26,260 --> 00:03:31,210 their bone marrow cells are largely destroyed through the 54 00:03:31,210 --> 00:03:32,370 chemotherapy. 55 00:03:32,370 --> 00:03:34,800 And so they have a problem with the white blood cell 56 00:03:34,800 --> 00:03:38,060 counts, and with stem cell counts and all that stuff. 57 00:03:38,060 --> 00:03:40,630 So one of the ways that you can try to reverse this 58 00:03:40,630 --> 00:03:45,460 problem is by stimulating, artificially stimulating the 59 00:03:45,460 --> 00:03:51,610 growth or the proliferation of these white blood cells. 60 00:03:51,610 --> 00:03:56,030 And one of the ways you could do that is by giving the 61 00:03:56,030 --> 00:04:00,180 patient a lot of this protein, granulocyte colony stimulating 62 00:04:00,180 --> 00:04:03,760 factor, to stimulate the output of white blood cells 63 00:04:03,760 --> 00:04:04,850 from the bone marrow. 64 00:04:04,850 --> 00:04:07,490 Whatever is left of the bone marrow. 65 00:04:07,490 --> 00:04:11,790 To rebuild it up. 66 00:04:11,790 --> 00:04:16,760 And so that's done with wild type, with protein. 67 00:04:16,760 --> 00:04:20,230 You can make the wild type protein. 68 00:04:20,230 --> 00:04:23,750 But if you had something that was basically the same thing 69 00:04:23,750 --> 00:04:28,080 but somehow mutated, where you made a few changes to the 70 00:04:28,080 --> 00:04:32,780 amino acid sequence, so that it worked a little bit better, 71 00:04:32,780 --> 00:04:37,750 then you might have a lot of people, a lot of patients. 72 00:04:37,750 --> 00:04:40,490 And that's what the basis of this paper is, that's 73 00:04:40,490 --> 00:04:40,970 referenced here. 74 00:04:40,970 --> 00:04:46,050 Is how to go about mutating this protein here to make it a 75 00:04:46,050 --> 00:04:47,700 drug that would be more effective 76 00:04:47,700 --> 00:04:49,640 then the natural protein. 77 00:04:49,640 --> 00:04:54,020 So that you can give it to patients. 78 00:04:54,020 --> 00:04:57,160 So now let me go back and tell you a little bit about this 79 00:04:57,160 --> 00:04:59,270 equilibrium that we're talking about. 80 00:04:59,270 --> 00:05:00,790 So we've been talking about equilibria of 81 00:05:00,790 --> 00:05:02,670 molecules coming together. 82 00:05:02,670 --> 00:05:05,820 And then creating new molecules, 83 00:05:05,820 --> 00:05:07,480 products and reactants. 84 00:05:07,480 --> 00:05:10,790 Well, when you're talking about ligands and receptors on 85 00:05:10,790 --> 00:05:12,883 cells, the same sort of ideas come in. 86 00:05:12,883 --> 00:05:14,720 The same equilibrium concepts come in. 87 00:05:14,720 --> 00:05:23,550 So if you have a cell membrane, the cell membrane 88 00:05:23,550 --> 00:05:25,820 could have a receptor in it. 89 00:05:25,820 --> 00:05:28,760 Which is a protein that extends through the membrane 90 00:05:28,760 --> 00:05:32,270 that's got some sort of pocket outside here. 91 00:05:32,270 --> 00:05:33,710 The membrane keeps on going. 92 00:05:33,710 --> 00:05:37,820 And you've got the blood on the outside here, or some of 93 00:05:37,820 --> 00:05:39,430 the tissue of the cells, and you've got the 94 00:05:39,430 --> 00:05:44,270 inside of the cell here. 95 00:05:44,270 --> 00:05:46,910 And this receptor is waiting for some ligand. 96 00:05:46,910 --> 00:05:53,290 A ligand being another protein that's floating around. 97 00:05:53,290 --> 00:05:58,430 That's specific for binding to this receptor here. 98 00:05:58,430 --> 00:06:00,800 And there's the ligand here. 99 00:06:00,800 --> 00:06:04,310 There's the receptor here. 100 00:06:04,310 --> 00:06:06,770 And every now and then one of these ligands will find a 101 00:06:06,770 --> 00:06:10,130 receptor and bind to it. 102 00:06:10,130 --> 00:06:14,250 So we write, then, in equilibrium, ligand plus 103 00:06:14,250 --> 00:06:19,330 receptor goes to complex. 104 00:06:19,330 --> 00:06:22,030 This is happening all the time on cells. 105 00:06:22,030 --> 00:06:25,310 There are millions of different kinds of receptors, 106 00:06:25,310 --> 00:06:28,170 millions, billions of kinds of ligands. 107 00:06:28,170 --> 00:06:30,710 Wild types, fake ones, et cetera et cetera. 108 00:06:30,710 --> 00:06:35,370 When you've got a binding event, the cell knows that's 109 00:06:35,370 --> 00:06:36,400 something has bound, usually. 110 00:06:36,400 --> 00:06:39,410 And that usually triggers a cascade of other things. 111 00:06:39,410 --> 00:06:41,030 It signals a cell to do a lot of things. 112 00:06:41,030 --> 00:06:47,220 So, for instance, in the case of the GCSF, you've got the 113 00:06:47,220 --> 00:06:49,430 receptor on the cell. 114 00:06:49,430 --> 00:06:52,630 And you've got this granulocyte colony signaling 115 00:06:52,630 --> 00:06:54,010 factor, that would be the ligand here. 116 00:06:54,010 --> 00:06:55,950 It binds to the receptor on the cell. 117 00:06:55,950 --> 00:06:59,440 That triggers the bone marrow cells to produce more 118 00:06:59,440 --> 00:07:02,780 proteins, which signals more things to happen, and 119 00:07:02,780 --> 00:07:06,280 eventually down the way, after a bunch of signaling 120 00:07:06,280 --> 00:07:09,440 processes, out come a burst of stem cells 121 00:07:09,440 --> 00:07:10,070 or white blood cells. 122 00:07:10,070 --> 00:07:14,040 It's a complicated process, and every step of the way 123 00:07:14,040 --> 00:07:15,590 needs to be done correctly. 124 00:07:15,590 --> 00:07:19,860 And for this process at least, this protein here, this ligand 125 00:07:19,860 --> 00:07:22,170 protein, triggers the cascade. 126 00:07:22,170 --> 00:07:24,720 And so this binding and unbinding of this protein then 127 00:07:24,720 --> 00:07:27,660 triggers the whole sequence of reactions. 128 00:07:27,660 --> 00:07:33,230 So this equilibrium becomes super-important then. 129 00:07:33,230 --> 00:07:33,810 OK. 130 00:07:33,810 --> 00:07:37,480 What else should we review about, I should have used a 131 00:07:37,480 --> 00:07:39,420 different board than this, but. 132 00:07:39,420 --> 00:07:42,220 This is going to get covered up. 133 00:07:42,220 --> 00:07:44,230 What else can we review about biology that would be 134 00:07:44,230 --> 00:07:44,630 interesting? 135 00:07:44,630 --> 00:07:50,800 So, other things that we will need to remember, need to 136 00:07:50,800 --> 00:07:54,220 know, is that these receptors on the surface of the cells 137 00:07:54,220 --> 00:07:57,970 aren't static. 138 00:07:57,970 --> 00:08:00,610 The cells recycle their receptors. 139 00:08:00,610 --> 00:08:03,300 Things can happen. 140 00:08:03,300 --> 00:08:04,480 Things get degraded. 141 00:08:04,480 --> 00:08:08,870 And so the cell is constantly taking these receptors, 142 00:08:08,870 --> 00:08:11,800 bringing them back inside the cell, merging them with 143 00:08:11,800 --> 00:08:16,180 lysosomes, where the pH is five, or 5.5 compared to the 144 00:08:16,180 --> 00:08:19,190 outside of the blood, which is 7.4. 145 00:08:19,190 --> 00:08:22,020 It breaks down the proteins into their amino acids, the 146 00:08:22,020 --> 00:08:24,980 cell can use the amino acids again to make more proteins. 147 00:08:24,980 --> 00:08:26,560 Make better, make new receptors. 148 00:08:26,560 --> 00:08:29,000 And that's how the cell recycles the receptors. 149 00:08:29,000 --> 00:08:33,690 So basically, you end up with the cell taking the receptor. 150 00:08:33,690 --> 00:08:40,550 Making a small sort of cavity around the receptor. 151 00:08:40,550 --> 00:08:41,940 So there's the cell sitting here. 152 00:08:41,940 --> 00:08:43,910 There's the inside of the cell. 153 00:08:43,910 --> 00:08:48,670 There's the receptor being engulfed by the cell, now. 154 00:08:48,670 --> 00:08:52,420 And it could have the ligand in on it, also. 155 00:08:52,420 --> 00:08:55,850 There's the ligand sitting right here. 156 00:08:55,850 --> 00:09:00,330 It's called an endocytotic event, or it's endocytosis of 157 00:09:00,330 --> 00:09:01,140 the receptor. 158 00:09:01,140 --> 00:09:02,670 Into the cell. 159 00:09:02,670 --> 00:09:07,300 And then once you're inside the cell, let's put the 160 00:09:07,300 --> 00:09:10,570 nucleus in the middle here, you've got things called 161 00:09:10,570 --> 00:09:14,210 lysosomes that are sitting nearby. 162 00:09:14,210 --> 00:09:16,730 There's a lysosome here. 163 00:09:16,730 --> 00:09:19,460 Lysosome. 164 00:09:19,460 --> 00:09:23,700 And there's your little vesicle that 165 00:09:23,700 --> 00:09:24,790 contains your receptor. 166 00:09:24,790 --> 00:09:30,900 Merges towards the lysosome, these two get together. 167 00:09:30,900 --> 00:09:44,140 Then you have your ligand, I'm running out of colors here. 168 00:09:44,140 --> 00:09:48,350 So there's the receptor and the ligand together in here. 169 00:09:48,350 --> 00:09:52,770 And then the pH here becomes 5.5, things break apart. 170 00:09:52,770 --> 00:09:55,970 And you've got to find another receptor, another ligand, to 171 00:09:55,970 --> 00:09:59,610 continue the process. 172 00:09:59,610 --> 00:10:03,180 Everybody knows this biology, or you know it well enough. 173 00:10:03,180 --> 00:10:06,520 OK, good. 174 00:10:06,520 --> 00:10:14,430 So let's go do this example. 175 00:10:14,430 --> 00:10:17,130 So this is the process of binding. 176 00:10:17,130 --> 00:10:19,940 We can have a delta G associated with this, delta G 177 00:10:19,940 --> 00:10:26,830 a, delta G0 is minus RT log K sub a. 178 00:10:26,830 --> 00:10:31,430 This is the association equilibrium. 179 00:10:31,430 --> 00:10:36,030 And you can have the reverse process, where the complex 180 00:10:36,030 --> 00:10:39,890 gets broken up into receptor plus a ligand. 181 00:10:39,890 --> 00:10:42,680 And then you have a delta G for this process here. 182 00:10:42,680 --> 00:10:47,800 So this is delta Ga, let's call it. 183 00:10:47,800 --> 00:10:55,590 This would be delta GD, which is the negative minus RT log K 184 00:10:55,590 --> 00:11:00,240 sub D. This is the dissociation process. 185 00:11:00,240 --> 00:11:06,240 And the dissociation process, K sub D, is equal to R, the 186 00:11:06,240 --> 00:11:09,100 concentration of the receptors times the concentration of the 187 00:11:09,100 --> 00:11:13,320 ligand, divided by the concentration of the complex. 188 00:11:13,320 --> 00:11:19,140 And the lower K sub D is, the smaller this number is, small 189 00:11:19,140 --> 00:11:23,150 means that you're mostly on this side here, mostly in the 190 00:11:23,150 --> 00:11:27,250 complex, the tighter the binding. 191 00:11:27,250 --> 00:11:41,350 So small KD means tight binding. 192 00:11:41,350 --> 00:11:44,150 So if I want, in principle, then, if I want to design a 193 00:11:44,150 --> 00:11:51,360 drug that's going to signal this event here, I want K sub 194 00:11:51,360 --> 00:11:53,510 D for this ligand that I'm going to 195 00:11:53,510 --> 00:11:56,960 design to be very small. 196 00:11:56,960 --> 00:11:58,160 To be small. 197 00:11:58,160 --> 00:12:01,840 Small enough so that it binds strongly and does its job, so 198 00:12:01,840 --> 00:12:06,130 I don't need too much of it. 199 00:12:06,130 --> 00:12:11,450 Now, you need to do experiments to figure out 200 00:12:11,450 --> 00:12:12,540 what's going on. 201 00:12:12,540 --> 00:12:13,890 So how do you do these experiments? 202 00:12:13,890 --> 00:12:15,900 You need to be able to measure, then these K sub D's, 203 00:12:15,900 --> 00:12:20,630 experimentally, to see whether or not what you've designed on 204 00:12:20,630 --> 00:12:23,960 the computer, when you calculate delta G's on the 205 00:12:23,960 --> 00:12:27,260 computer you've got to know whether or not it's working. 206 00:12:27,260 --> 00:12:32,750 And this is still an experimental science. 207 00:12:32,750 --> 00:12:33,860 How does it work? 208 00:12:33,860 --> 00:12:38,020 So, usually you do the experiment with the ligand 209 00:12:38,020 --> 00:12:43,520 concentration very high. 210 00:12:43,520 --> 00:12:44,630 Very large. 211 00:12:44,630 --> 00:12:48,150 So that the concentration of the ligand at any time is 212 00:12:48,150 --> 00:12:50,320 basically the same thing as the concentration of the 213 00:12:50,320 --> 00:12:51,440 ligand you put in. 214 00:12:51,440 --> 00:12:55,470 So you overwhelm the system with ligands. 215 00:12:55,470 --> 00:12:59,450 So that L is much bigger than C or R, and so it doesn't 216 00:12:59,450 --> 00:13:02,090 matter which way the equilibrium is. 217 00:13:02,090 --> 00:13:04,370 L stays roughly the same. 218 00:13:04,370 --> 00:13:06,800 So you know, throughout the experiment, what 219 00:13:06,800 --> 00:13:08,400 concentration is. 220 00:13:08,400 --> 00:13:16,740 Then you get a bunch of cells. 221 00:13:16,740 --> 00:13:19,450 In a well or something, or a 96 well plate with a bunch of 222 00:13:19,450 --> 00:13:21,030 different kinds of ligands. 223 00:13:21,030 --> 00:13:26,820 And you can take your ligand, you can label it 224 00:13:26,820 --> 00:13:28,200 radioactively. 225 00:13:28,200 --> 00:13:33,380 So you can take your ligand as some long protein. 226 00:13:33,380 --> 00:13:39,100 And you can take an iodine 125, let's say, radioactive 227 00:13:39,100 --> 00:13:41,480 label on your ligand, on your protein. 228 00:13:41,480 --> 00:13:43,360 So you can keep track of it. 229 00:13:43,360 --> 00:13:45,460 The nice thing about radioactive labels, and which 230 00:13:45,460 --> 00:13:49,560 is why people use them in biology or bio-medicine. 231 00:13:49,560 --> 00:13:52,620 We use them to look at, for instance, bio-distribution of 232 00:13:52,620 --> 00:13:54,200 things in animals. 233 00:13:54,200 --> 00:13:56,800 We want to know where things are, and whether they all left 234 00:13:56,800 --> 00:13:59,190 the animal, or. 235 00:13:59,190 --> 00:14:01,950 Because you can use a Geiger counter and you 236 00:14:01,950 --> 00:14:06,440 can count the events. 237 00:14:06,440 --> 00:14:07,810 The radioactive events. 238 00:14:07,810 --> 00:14:13,620 And that gives you extremely quantitative analysis of where 239 00:14:13,620 --> 00:14:14,690 things are. 240 00:14:14,690 --> 00:14:18,510 So you take those radioactive ligand. 241 00:14:18,510 --> 00:14:20,940 And, L0, very large concentration. 242 00:14:20,940 --> 00:14:23,850 You expose this concentration to the cells. 243 00:14:23,850 --> 00:14:26,220 The cells have some receptors on the surface. 244 00:14:26,220 --> 00:14:28,940 There's a bunch of receptors on the surface of the cell. 245 00:14:28,940 --> 00:14:32,020 And some fraction of the receptors will have the ligand 246 00:14:32,020 --> 00:14:36,980 bound to them. 247 00:14:36,980 --> 00:14:37,840 So you incubate. 248 00:14:37,840 --> 00:14:39,930 You let it wait a while. 249 00:14:39,930 --> 00:14:45,180 Then you wash. 250 00:14:45,180 --> 00:14:47,600 So you get rid of all the excess ligand 251 00:14:47,600 --> 00:14:49,200 that's on top there. 252 00:14:49,200 --> 00:14:55,860 And then you take your petri dish, or your 96 well plate. 253 00:14:55,860 --> 00:14:59,610 And you read the radioactivity that's coming from the cells. 254 00:14:59,610 --> 00:15:01,930 And that signal, that radioactive signals, tells you 255 00:15:01,930 --> 00:15:06,910 exactly how many ligand you have on these cells. 256 00:15:06,910 --> 00:15:10,930 You knew what the cell concentration was initially. 257 00:15:10,930 --> 00:15:14,090 So that tells you what the concentration of ligands, of 258 00:15:14,090 --> 00:15:16,200 complexes, was. 259 00:15:16,200 --> 00:15:22,760 So this experiment then gets you, experimentally, gets you 260 00:15:22,760 --> 00:15:27,470 the concentration of C, the complex. 261 00:15:27,470 --> 00:15:29,530 So now this is something you know. 262 00:15:29,530 --> 00:15:31,610 You also know what L0 was, because that's 263 00:15:31,610 --> 00:15:33,410 what you put in. 264 00:15:33,410 --> 00:15:35,930 And that's enough for you to find out what KD is. 265 00:15:35,930 --> 00:15:38,430 And if you know what KD is, then you know 266 00:15:38,430 --> 00:15:42,080 what delta G0 is. 267 00:15:42,080 --> 00:15:49,880 And so generally, then, let's go ahead and do that. 268 00:15:49,880 --> 00:15:54,810 So we know what L is. 269 00:15:54,810 --> 00:16:01,750 We know what L0, C is, let me just do it on this board here. 270 00:16:01,750 --> 00:16:07,530 So we start with rewriting KD as equal to R times L divided 271 00:16:07,530 --> 00:16:09,160 by the complex concentration. 272 00:16:09,160 --> 00:16:15,680 And now L is basically L0, so we can use that approximation. 273 00:16:15,680 --> 00:16:17,100 So we have L0 sitting here. 274 00:16:17,100 --> 00:16:18,900 We still have the complex on the bottom, and that's 275 00:16:18,900 --> 00:16:20,960 something that we've experimentally discovered. 276 00:16:20,960 --> 00:16:25,860 And the concentration of receptors, this is the 277 00:16:25,860 --> 00:16:27,550 concentration of receptors that don't have 278 00:16:27,550 --> 00:16:28,480 anything bound to them. 279 00:16:28,480 --> 00:16:33,030 So it's these guys right here. 280 00:16:33,030 --> 00:16:36,620 That's equal to the concentration of receptors, 281 00:16:36,620 --> 00:16:40,360 the total number of receptors, minus those receptors that 282 00:16:40,360 --> 00:16:42,870 have a ligand bound to them. 283 00:16:42,870 --> 00:16:43,720 Complexes. 284 00:16:43,720 --> 00:16:46,570 Something we can 285 00:16:46,570 --> 00:16:49,110 experimentally define, or discover. 286 00:16:49,110 --> 00:16:57,190 So we replace this R here with RT minus C. And then we're all 287 00:16:57,190 --> 00:16:57,920 at equilibrium. 288 00:16:57,920 --> 00:17:01,990 So we're going to put a little equilibrium sign under these 289 00:17:01,990 --> 00:17:05,060 C's here. equilibrium. 290 00:17:05,060 --> 00:17:10,390 And then we can rearrange this equation so that, people like 291 00:17:10,390 --> 00:17:13,100 to have plots that are linear, in a way that is a linear 292 00:17:13,100 --> 00:17:18,980 plot, where the slope of the plot is the inverse of the 293 00:17:18,980 --> 00:17:22,320 equilibrium constant. 294 00:17:22,320 --> 00:17:27,480 So you do some massaging of this equation here. 295 00:17:27,480 --> 00:17:32,430 And you rewrite it in terms of C over L0. 296 00:17:32,430 --> 00:17:37,600 There's the equilibrium concentration of the complex. 297 00:17:37,600 --> 00:17:43,250 This is the total receptor concentration divided by the 298 00:17:43,250 --> 00:17:44,160 equilibrium constant. 299 00:17:44,160 --> 00:17:50,350 And then you have the equilibrium concentration of 300 00:17:50,350 --> 00:17:57,910 the complex divided by KD. 301 00:17:57,910 --> 00:18:01,920 And so you plot, then, this ratio. 302 00:18:01,920 --> 00:18:04,420 Which is an experimental ratio. 303 00:18:04,420 --> 00:18:08,920 You've just measured this concentration of complexes 304 00:18:08,920 --> 00:18:11,670 using this radioactivity, radioactive labeling 305 00:18:11,670 --> 00:18:13,210 experiment. 306 00:18:13,210 --> 00:18:16,450 You know what this is, because that's what you've put in. 307 00:18:16,450 --> 00:18:19,230 This is your x-axis on your plot. 308 00:18:19,230 --> 00:18:20,680 This is what you've measured. 309 00:18:20,680 --> 00:18:23,020 And this is going to be the slope. 310 00:18:23,020 --> 00:18:31,000 It's called a Scatchard plot. 311 00:18:31,000 --> 00:18:33,890 After Mr. Scatchard 312 00:18:33,890 --> 00:18:36,630 So you get a straight line. 313 00:18:36,630 --> 00:18:40,560 So we're plotting here the equilibrium 314 00:18:40,560 --> 00:18:42,410 constant of the complex. 315 00:18:42,410 --> 00:18:45,320 And on this here we're plotting the ratio of the 316 00:18:45,320 --> 00:18:48,200 complex divided by L0. 317 00:18:48,200 --> 00:18:57,220 And we get this straight line like this, where the slope is 318 00:18:57,220 --> 00:19:01,590 one over KD. 319 00:19:01,590 --> 00:19:07,290 Minus one over KD. 320 00:19:07,290 --> 00:19:11,820 OK, now there's a couple of things that you can look at 321 00:19:11,820 --> 00:19:15,350 that are sometimes useful. 322 00:19:15,350 --> 00:19:20,090 In this analysis here. 323 00:19:20,090 --> 00:19:24,710 You can also rewrite this equation up here in terms of 324 00:19:24,710 --> 00:19:29,950 the ratio of C equilibrium divided by RT. 325 00:19:29,950 --> 00:19:34,630 So that's basically the ratio of receptors that have a 326 00:19:34,630 --> 00:19:36,870 ligand attached to them, divided by the total 327 00:19:36,870 --> 00:19:38,220 concentration of receptors. 328 00:19:38,220 --> 00:19:45,600 So if most of the receptors are empty, then this is a 329 00:19:45,600 --> 00:19:46,690 small number. 330 00:19:46,690 --> 00:19:48,860 Then most of the receptors are taken up, this is a number 331 00:19:48,860 --> 00:19:49,760 close to one. 332 00:19:49,760 --> 00:19:53,140 It can't be anywhere, it can't be ever bigger than one, 333 00:19:53,140 --> 00:19:55,320 because the biggest number of complexes you can get is the 334 00:19:55,320 --> 00:19:56,990 total number of receptors. 335 00:19:56,990 --> 00:19:59,410 So if you take this equation here and you massage it a 336 00:19:59,410 --> 00:20:10,630 little bit, one over one plus KD over L0, and that, you can 337 00:20:10,630 --> 00:20:14,410 also plot that. 338 00:20:14,410 --> 00:20:19,400 As a function of L0. 339 00:20:19,400 --> 00:20:21,390 How much ligands you put in. 340 00:20:21,390 --> 00:20:25,370 And you find this is something that saturates at one. 341 00:20:25,370 --> 00:20:27,390 So this ratio here is going to saturate at one. 342 00:20:27,390 --> 00:20:34,670 This is C equilibrium divided by total number of receptors. 343 00:20:34,670 --> 00:20:42,200 And so if L0 is small enough, if L0 is small enough, meaning 344 00:20:42,200 --> 00:21:05,690 that it's smaller than KD, so if L0 is much smaller then KD, 345 00:21:05,690 --> 00:21:14,390 then you can rearrange this ratio here so that C 346 00:21:14,390 --> 00:21:24,980 equilibrium divided by RT is roughly L0 over KD. 347 00:21:24,980 --> 00:21:27,180 So that's linear, with a slope of one over KD. 348 00:21:27,180 --> 00:21:33,670 So this slope here is one over KD is the slope. 349 00:21:33,670 --> 00:21:39,280 And as you get L0 to be quite large, bigger than KD, then 350 00:21:39,280 --> 00:21:40,330 this saturate to one. 351 00:21:40,330 --> 00:21:42,780 And this one over something very large become zero, and 352 00:21:42,780 --> 00:21:46,510 basically you end up with something close to one. 353 00:21:46,510 --> 00:21:49,030 So you saturate at one. 354 00:21:49,030 --> 00:21:51,240 So that's another way of doing this. 355 00:21:51,240 --> 00:21:54,020 But this is really what we want to concentrate here. 356 00:21:54,020 --> 00:21:56,400 The fact that you can get KD out of experimentally. 357 00:21:56,400 --> 00:22:00,970 If you have KD, you have delta G. 358 00:22:00,970 --> 00:22:05,330 So now let's go back and think about this whole process here. 359 00:22:05,330 --> 00:22:09,750 If we're going to design this drug here, this protein, 360 00:22:09,750 --> 00:22:11,440 artificially. 361 00:22:11,440 --> 00:22:13,450 So what you want, then, is you want something that's going to 362 00:22:13,450 --> 00:22:18,170 bind strongly enough to receptor, to stimulate the 363 00:22:18,170 --> 00:22:24,480 growth of granulocytes, or the colony of granulocytes. 364 00:22:24,480 --> 00:22:29,770 But when the cell decides to recycle the receptor, and 365 00:22:29,770 --> 00:22:34,840 destroy it, chew it apart in the lysosome here, you want 366 00:22:34,840 --> 00:22:38,220 this drug not to be degraded. 367 00:22:38,220 --> 00:22:41,280 Because you have to keep injecting in the patient. 368 00:22:41,280 --> 00:22:45,210 So you want this drug to release from the receptor, 369 00:22:45,210 --> 00:22:48,830 before the lysosome has a chance to chew it up. 370 00:22:48,830 --> 00:22:51,470 So that means that you want the equilibrium constant at pH 371 00:22:51,470 --> 00:22:58,120 5.5, you want that KD, to be much larger at 5.5 than you 372 00:22:58,120 --> 00:23:00,060 want it at 7.4. 373 00:23:00,060 --> 00:23:02,790 You want strong binding at pH 7.4, and you want weak 374 00:23:02,790 --> 00:23:05,020 binding at pH 5.5. 375 00:23:05,020 --> 00:23:07,980 That way the drug gets recycled. 376 00:23:07,980 --> 00:23:11,290 Can find, go back to the blood. 377 00:23:11,290 --> 00:23:14,760 Bind to a receptor again, generate the signaling events, 378 00:23:14,760 --> 00:23:16,310 gets engulfed by the cell. 379 00:23:16,310 --> 00:23:18,220 Releases before it has a chance to be 380 00:23:18,220 --> 00:23:19,300 chewed up, et cetera. 381 00:23:19,300 --> 00:23:22,990 The wild type will get chewed up. 382 00:23:22,990 --> 00:23:25,020 The regular kind will get chewed up, and so that's why 383 00:23:25,020 --> 00:23:27,400 you have to, with the patients you have to keep giving them 384 00:23:27,400 --> 00:23:28,750 this drug over and over again. 385 00:23:28,750 --> 00:23:34,620 Because it gets chewed up by the cells. 386 00:23:34,620 --> 00:23:38,530 So that's the design principle that these authors had in mind 387 00:23:38,530 --> 00:23:39,950 when they started their study. 388 00:23:39,950 --> 00:23:42,840 And so they knew what the sequence, what the amino acid 389 00:23:42,840 --> 00:23:46,470 sequence was, for this wild type drug, and they started 390 00:23:46,470 --> 00:23:48,720 doing point mutations. 391 00:23:48,720 --> 00:23:50,870 Changing one amino acid here and there. 392 00:23:50,870 --> 00:23:54,990 And cranking out the calculation to calculate delta 393 00:23:54,990 --> 00:23:59,740 G for binding of this protein to this receptor. 394 00:23:59,740 --> 00:24:02,990 At pH 7.4 and at pH 5.5, and getting 395 00:24:02,990 --> 00:24:05,120 differences of delta G's. 396 00:24:05,120 --> 00:24:11,770 So let me then review again. 397 00:24:11,770 --> 00:24:19,390 What is the motivation here. 398 00:24:19,390 --> 00:24:27,260 The motivation is to try to get the ratio, KD, at 5.5 399 00:24:27,260 --> 00:24:33,040 divided by KD at 7.4, pH 7.4. 400 00:24:33,040 --> 00:24:35,750 And you want this to be bigger than one. 401 00:24:35,750 --> 00:24:39,720 And really as large as possible. 402 00:24:39,720 --> 00:24:42,660 As possible, of course within limits. 403 00:24:42,660 --> 00:24:47,150 So we want this to bind at pH 7.4. 404 00:24:47,150 --> 00:24:57,940 And the point of comparison is the wild types. 405 00:24:57,940 --> 00:25:07,770 Which at 7.4 has a KD of 270, roughly. 406 00:25:07,770 --> 00:25:18,690 And at the ratio of pH 5.5 to 7.4 is 1.7. 407 00:25:18,690 --> 00:25:23,150 So it's a little bit weaker binding at 5.5. 408 00:25:23,150 --> 00:25:27,570 Remember, large KD means weak binding. 409 00:25:27,570 --> 00:25:30,890 Small KD means tight binding. 410 00:25:30,890 --> 00:25:34,820 So the fact that KD at 5.5 is bigger than KD at 7.5 means 411 00:25:34,820 --> 00:25:38,540 that it's slightly weaker binding at 5.5 than 7.4. 412 00:25:38,540 --> 00:25:43,570 So this is sort of the baseline that the protein 413 00:25:43,570 --> 00:25:46,120 designers had to deal with. 414 00:25:46,120 --> 00:25:53,800 So everything gets compared to this guy here. 415 00:25:53,800 --> 00:25:58,480 So they don't actually, in a calculation they don't 416 00:25:58,480 --> 00:26:00,990 actually measure this. 417 00:26:00,990 --> 00:26:03,920 What they do is, they look at delta G's. 418 00:26:03,920 --> 00:26:09,630 And so they look at differences of delta G's. 419 00:26:09,630 --> 00:26:16,750 They look at delta G0 for the binding of the 420 00:26:16,750 --> 00:26:18,590 ligand to the receptor. 421 00:26:18,590 --> 00:26:28,650 At 7.4 minus the delta G0 at pH 5.5, let's call this the 422 00:26:28,650 --> 00:26:38,070 delta delta G. Since you know delta G is minus RT log K, 423 00:26:38,070 --> 00:26:45,990 this is equal to minus the delta of log KD, which is log 424 00:26:45,990 --> 00:26:54,310 KD at 5.5 divided by KD at 7.4. 425 00:26:54,310 --> 00:26:58,460 So then they calculate delta delta G0, and it's completely 426 00:26:58,460 --> 00:27:04,060 related to this ratio that you measured in the experiment. 427 00:27:04,060 --> 00:27:12,570 And so for the wild type, this delta delta G is just 428 00:27:12,570 --> 00:27:15,620 basically the log of this number here. 429 00:27:15,620 --> 00:27:23,060 Is 0.53. 430 00:27:23,060 --> 00:27:26,540 So now they go ahead and do their calculation. 431 00:27:26,540 --> 00:27:31,640 And they find a couple of mutants. 432 00:27:31,640 --> 00:27:34,620 Where, and they focus on delta delta G0. 433 00:27:34,620 --> 00:27:37,980 They want something that's bigger than this. 434 00:27:37,980 --> 00:27:40,950 And then they'll worry about whether there are more 435 00:27:40,950 --> 00:27:42,540 problems associated with it. 436 00:27:42,540 --> 00:27:47,260 So they found two mutants, let's call 437 00:27:47,260 --> 00:27:58,660 them D110H and D113H. 438 00:27:58,660 --> 00:28:02,580 I think it's a histidine mutation, point mutation at 439 00:28:02,580 --> 00:28:10,835 110 and 113, where this ratio here was 8.3 and 17. 440 00:28:10,835 --> 00:28:14,260 So, huge differences here. 441 00:28:14,260 --> 00:28:19,220 More than a factor of 20, or factor of 30 difference in the 442 00:28:19,220 --> 00:28:22,280 change in the binding efficiency, at least according 443 00:28:22,280 --> 00:28:27,540 to these delta delta G, between pH 5.5 and pH 7.4. 444 00:28:27,540 --> 00:28:31,610 That means that this protein here with the point mutation, 445 00:28:31,610 --> 00:28:35,940 with this one point mutation, if it binds as strongly to the 446 00:28:35,940 --> 00:28:40,100 receptor on the surface, as soon as the lysosome comes in 447 00:28:40,100 --> 00:28:46,430 and begins to decrease pH inside the cell, this ligand 448 00:28:46,430 --> 00:28:48,300 is going to come off. 449 00:28:48,300 --> 00:28:49,930 And it's going to be able to float away. 450 00:28:49,930 --> 00:28:52,550 Hopefully, before it gets recycled. 451 00:28:52,550 --> 00:28:53,750 Before it gets chewed up. 452 00:28:53,750 --> 00:28:57,320 So they can be used again. 453 00:28:57,320 --> 00:29:03,600 So that's good. 454 00:29:03,600 --> 00:29:07,950 Alright, so experiments were done. 455 00:29:07,950 --> 00:29:17,520 And on the D110H and the D113H. 456 00:29:17,520 --> 00:29:19,935 And KD was measured in the experiments. 457 00:29:19,935 --> 00:29:22,140 And remember, the wild type is 270. 458 00:29:22,140 --> 00:29:24,750 The KD's were at 370. 459 00:29:24,750 --> 00:29:28,620 And 320, with some error bar. 460 00:29:28,620 --> 00:29:33,590 And the different, the ratios of KD's were measured. 461 00:29:33,590 --> 00:29:37,160 There were 4.4 and 6.8. 462 00:29:37,160 --> 00:29:39,930 With some error bars. 463 00:29:39,930 --> 00:29:42,880 And they turned out to match reasonably well, at least as 464 00:29:42,880 --> 00:29:46,030 far as comparison between experiment and theory. 465 00:29:46,030 --> 00:29:49,020 Still not great for these sorts of calculations, because 466 00:29:49,020 --> 00:29:50,490 pretty involved. 467 00:29:50,490 --> 00:29:52,150 A lot of approximations go on in there. 468 00:29:52,150 --> 00:29:56,360 And it gives you a rough guide. 469 00:29:56,360 --> 00:29:59,160 So this 17 here is probably not quite right, because it 470 00:29:59,160 --> 00:30:01,300 doesn't quite translate to 6.8 here. 471 00:30:01,300 --> 00:30:04,040 This difference between 4.4 and 6.8 doesn't quite match 472 00:30:04,040 --> 00:30:06,270 the difference that they saw here in the calculation. 473 00:30:06,270 --> 00:30:07,940 But it's the right direction, right? 474 00:30:07,940 --> 00:30:11,090 And that's why you still need to do experiments. 475 00:30:11,090 --> 00:30:13,170 This number here is a little bit bigger 476 00:30:13,170 --> 00:30:13,990 than this number here. 477 00:30:13,990 --> 00:30:19,370 Which means that these don't bind quite as strongly. 478 00:30:19,370 --> 00:30:21,910 Because KD small means strong binding. 479 00:30:21,910 --> 00:30:24,380 That means the initial binding of the ligand to the receptor 480 00:30:24,380 --> 00:30:28,340 is not quite as good as the wild type. 481 00:30:28,340 --> 00:30:29,210 That's often the case. 482 00:30:29,210 --> 00:30:31,340 It's often not so easy to find something that binds as 483 00:30:31,340 --> 00:30:34,000 strongly as the wild version. 484 00:30:34,000 --> 00:30:36,360 But, it's good enough. 485 00:30:36,360 --> 00:30:39,540 And this ratio is really what clamps the deal 486 00:30:39,540 --> 00:30:43,550 in this case here. 487 00:30:43,550 --> 00:30:59,080 And so, these mutants, in fact these two mutants are the ones 488 00:30:59,080 --> 00:31:03,060 that have undergone the animal trials. 489 00:31:03,060 --> 00:31:06,770 That are in the pipeline. 490 00:31:06,770 --> 00:31:07,880 This is a big deal. 491 00:31:07,880 --> 00:31:12,400 This is a big deal because this is a huge, huge market. 492 00:31:12,400 --> 00:31:15,720 There's a very large number of people that are affected with 493 00:31:15,720 --> 00:31:16,480 chemotherapy. 494 00:31:16,480 --> 00:31:21,720 And this is basic thermodynamics here. 495 00:31:21,720 --> 00:31:24,990 It's basic thermodynamic calculation of a complicated 496 00:31:24,990 --> 00:31:32,980 molecule with some fairly simple equilibrium concepts. 497 00:31:32,980 --> 00:31:47,460 OK, any questions on this? 498 00:31:47,460 --> 00:31:53,180 OK, well, we're ended really early today. 499 00:31:53,180 --> 00:31:57,120 I don't have the phase transition ready, but Keith 500 00:31:57,120 --> 00:31:59,980 Nelson is going to start a phase transition next time. 501 00:31:59,980 --> 00:32:00,120