1 00:00:00,500 --> 00:00:02,830 The following content is provided under a Creative 2 00:00:02,830 --> 00:00:04,370 Commons license. 3 00:00:04,370 --> 00:00:06,670 Your support will help MIT OpenCourseWare 4 00:00:06,670 --> 00:00:11,030 continue to offer high quality educational resources for free. 5 00:00:11,030 --> 00:00:13,660 To make a donation or view additional materials 6 00:00:13,660 --> 00:00:17,610 from hundreds of MIT courses, visit MIT OpenCourseWare 7 00:00:17,610 --> 00:00:18,540 at ocw.mit.edu. 8 00:00:25,880 --> 00:00:29,090 ELIZABETH NOLAN: Where we'll spend the first part of today 9 00:00:29,090 --> 00:00:31,070 is finishing up where we left off 10 00:00:31,070 --> 00:00:33,080 last time with the experiments that 11 00:00:33,080 --> 00:00:36,440 were done to take a look at what types 12 00:00:36,440 --> 00:00:42,080 of polypeptides, the DNA, kDNA, J chaperone machinery interact 13 00:00:42,080 --> 00:00:43,670 with in E. coli. 14 00:00:43,670 --> 00:00:45,080 And once we finish up that, we'll 15 00:00:45,080 --> 00:00:49,410 transition into module 3, which is protein degradation. 16 00:00:49,410 --> 00:00:52,670 And most of today will just be some general background 17 00:00:52,670 --> 00:00:54,943 about proteases and protein degradation. 18 00:00:54,943 --> 00:00:56,360 And then on Wednesday, we'll begin 19 00:00:56,360 --> 00:00:59,150 to look at the macromolecular machines that are 20 00:00:59,150 --> 00:01:01,530 involved in those processes. 21 00:01:01,530 --> 00:01:02,210 OK. 22 00:01:02,210 --> 00:01:07,520 So last time we discussed DnaK, the chaperone, DnaJ, 23 00:01:07,520 --> 00:01:08,610 the co-chaperone. 24 00:01:08,610 --> 00:01:09,110 Right. 25 00:01:09,110 --> 00:01:13,730 So recall DnaJ went around and found some polypeptide 26 00:01:13,730 --> 00:01:15,770 in a non-native state and delivered it 27 00:01:15,770 --> 00:01:20,630 to DnaK, which can grip and hold on to the hydrophobic segments 28 00:01:20,630 --> 00:01:23,120 and somehow facilitate folding. 29 00:01:23,120 --> 00:01:27,260 And so where we left off were with experiments performed 30 00:01:27,260 --> 00:01:31,310 in a similar manner to what we saw for GroEL/GroES where 31 00:01:31,310 --> 00:01:36,720 pulse chase was done to label newly synthesized polypeptides. 32 00:01:36,720 --> 00:01:37,220 Right. 33 00:01:37,220 --> 00:01:41,000 So during the pulse period with this radio label methionine, 34 00:01:41,000 --> 00:01:43,760 newly synthesized polypeptides are labeled. 35 00:01:43,760 --> 00:01:46,850 And that allows us to see specifically 36 00:01:46,850 --> 00:01:49,910 what newly synthesized polypeptides DnaK, 37 00:01:49,910 --> 00:01:53,090 J are interacting with without the background 38 00:01:53,090 --> 00:01:54,920 of everything else in the cell. 39 00:01:54,920 --> 00:01:57,770 And why do we care about that? 40 00:01:57,770 --> 00:01:59,690 Imagine if we didn't somehow label 41 00:01:59,690 --> 00:02:02,380 to discriminate these newly synthesized polypeptides. 42 00:02:02,380 --> 00:02:02,880 Right. 43 00:02:02,880 --> 00:02:06,290 We can pull down many things in the precipitation, 44 00:02:06,290 --> 00:02:09,530 but we'd have no sense as to how long a given polypeptide 45 00:02:09,530 --> 00:02:11,090 existed in the cell. 46 00:02:11,090 --> 00:02:13,460 So maybe it was newly synthesized. 47 00:02:13,460 --> 00:02:16,160 Maybe it had been around a long time and something happened 48 00:02:16,160 --> 00:02:19,400 to it such that it wasn't in a native fold and DnaK interacted 49 00:02:19,400 --> 00:02:19,920 with it. 50 00:02:19,920 --> 00:02:20,420 OK. 51 00:02:20,420 --> 00:02:23,000 So that's the key point with these pulse chase 52 00:02:23,000 --> 00:02:25,950 and this labeling for a short time period. 53 00:02:25,950 --> 00:02:26,450 OK. 54 00:02:26,450 --> 00:02:30,110 So the researchers had an antibody to DnaK. 55 00:02:30,110 --> 00:02:32,720 They had to test its specificity as we 56 00:02:32,720 --> 00:02:35,060 discussed for GroEL/GroES. 57 00:02:35,060 --> 00:02:38,030 And then after immunoprecipitation, it's 58 00:02:38,030 --> 00:02:40,430 necessary to do the analysis. 59 00:02:40,430 --> 00:02:45,020 And so as I noted last time, in this particular study, 60 00:02:45,020 --> 00:02:47,480 the analysis were less sophisticated than what 61 00:02:47,480 --> 00:02:50,570 we saw for GroEL/GroES so they just 62 00:02:50,570 --> 00:02:53,090 used one dimensional SDF page, which 63 00:02:53,090 --> 00:02:55,370 we're all pretty familiar with. 64 00:02:55,370 --> 00:02:58,040 And they didn't extend it to mass spec. 65 00:02:58,040 --> 00:03:00,410 But with that said, there are a number 66 00:03:00,410 --> 00:03:04,710 of observations that are helpful that come from this study. 67 00:03:04,710 --> 00:03:07,370 So what we're going to do is examine their gels 68 00:03:07,370 --> 00:03:11,170 and see what conclusions we can come up with. 69 00:03:11,170 --> 00:03:12,140 OK. 70 00:03:12,140 --> 00:03:15,800 So this is their experiment number one. 71 00:03:15,800 --> 00:03:20,420 And what they did was look at the soluble crude cell 72 00:03:20,420 --> 00:03:24,510 extracts that were generated in this pulse chase experiment. 73 00:03:24,510 --> 00:03:25,310 OK. 74 00:03:25,310 --> 00:03:29,580 And so what do we see in terms of how the data is presented? 75 00:03:29,580 --> 00:03:30,080 Right. 76 00:03:30,080 --> 00:03:36,920 We have two lanes on the left, one and two, that are basically 77 00:03:36,920 --> 00:03:39,530 total cytoplasmic proteins. 78 00:03:39,530 --> 00:03:42,770 And then the lanes three through six on the right 79 00:03:42,770 --> 00:03:46,100 are four samples that were immunoprecipitated 80 00:03:46,100 --> 00:03:49,110 with this anti-DnaK antibody. 81 00:03:49,110 --> 00:03:49,610 OK. 82 00:03:49,610 --> 00:03:52,040 So something that was done in these experiments that 83 00:03:52,040 --> 00:03:55,760 was different than the GroEL/GroES work 84 00:03:55,760 --> 00:03:58,640 is that they use two different E. coli strains. 85 00:03:58,640 --> 00:04:01,130 So they used a wild type E. Coli strain. 86 00:04:01,130 --> 00:04:04,480 So that strain expresses DnaK. 87 00:04:04,480 --> 00:04:09,770 And they also used a mutant E. coli that is deficient in DnaK. 88 00:04:09,770 --> 00:04:12,620 So that's what this delta DnaK means. 89 00:04:12,620 --> 00:04:14,660 So they did some genetic manipulation 90 00:04:14,660 --> 00:04:16,990 and knocked out DnaK. 91 00:04:16,990 --> 00:04:17,490 OK. 92 00:04:17,490 --> 00:04:19,459 And as we learned in the introduction, 93 00:04:19,459 --> 00:04:23,510 these chaperone system is not essential. 94 00:04:23,510 --> 00:04:28,400 So what do we see if we work through this gel? 95 00:04:28,400 --> 00:04:33,470 And first, we just want to go over what the data show 96 00:04:33,470 --> 00:04:37,820 and then why that's important here. 97 00:04:37,820 --> 00:04:43,820 So if we compare lanes one and two, what do lanes one and two 98 00:04:43,820 --> 00:04:44,540 tell us? 99 00:04:48,710 --> 00:04:53,780 So these are the total cell lysates, soluble fraction, 100 00:04:53,780 --> 00:04:58,040 from either wild type E. Coli or delta DnaK. 101 00:04:58,040 --> 00:05:00,830 And why do we care to run these? 102 00:05:00,830 --> 00:05:04,760 So no immunoprecipitation. 103 00:05:04,760 --> 00:05:07,100 So I'll give you a start and then 104 00:05:07,100 --> 00:05:09,290 you all can contribute to the next ones. 105 00:05:09,290 --> 00:05:10,100 OK? 106 00:05:10,100 --> 00:05:14,600 So what I would say looking at these two lanes 107 00:05:14,600 --> 00:05:18,770 is first it looks like the total amount of protein 108 00:05:18,770 --> 00:05:20,690 and the distribution of these proteins 109 00:05:20,690 --> 00:05:26,230 is similar for both the wild type E. Coli and the delta DnaK 110 00:05:26,230 --> 00:05:27,080 knockout. 111 00:05:27,080 --> 00:05:27,580 OK. 112 00:05:27,580 --> 00:05:29,780 There's proteins that are distributed 113 00:05:29,780 --> 00:05:32,540 across a wide range of molecular weights, 114 00:05:32,540 --> 00:05:37,220 from below 14 kilodaltons to upwards of 100. 115 00:05:37,220 --> 00:05:38,060 OK. 116 00:05:38,060 --> 00:05:40,560 And why is this important to show? 117 00:05:40,560 --> 00:05:42,050 One, we want to see what the cell 118 00:05:42,050 --> 00:05:45,720 lysate looks like in the absence of immunoprecipitation. 119 00:05:45,720 --> 00:05:46,220 Right? 120 00:05:46,220 --> 00:05:49,520 And two, it's important to know whether or not 121 00:05:49,520 --> 00:05:54,920 knocking out DnaK has done anything to change those cells. 122 00:05:54,920 --> 00:05:57,200 And at least at the level here, it 123 00:05:57,200 --> 00:06:00,740 looks like in terms of the total cellular polypeptide pool, 124 00:06:00,740 --> 00:06:06,130 it's pretty much comparable in terms of total protein. 125 00:06:06,130 --> 00:06:10,770 So what happens now here where we 126 00:06:10,770 --> 00:06:14,040 have this immunoprecipitation? 127 00:06:14,040 --> 00:06:17,010 So we have four different lanes. 128 00:06:17,010 --> 00:06:21,030 We're going to focus on three, four, and five and ignore six. 129 00:06:21,030 --> 00:06:24,390 Basically, in three, we see immunoprecipitation 130 00:06:24,390 --> 00:06:29,340 from the wild type E. coli; in four, immunoprecipitation 131 00:06:29,340 --> 00:06:33,690 with wild type when the sample has been treated with SDS, 132 00:06:33,690 --> 00:06:36,000 so we need to think about why that was done 133 00:06:36,000 --> 00:06:38,490 and what that experiment shows; and then 134 00:06:38,490 --> 00:06:43,110 lane five in the delta DnaK knockout. 135 00:06:43,110 --> 00:06:47,250 So first of all, what does line three tell us? 136 00:06:49,950 --> 00:06:50,450 Kenny? 137 00:06:50,450 --> 00:06:53,280 AUDIENCE: Can you get enrichment of higher molecular weight 138 00:06:53,280 --> 00:06:54,690 proteins? 139 00:06:54,690 --> 00:07:01,080 And as the note says that 15 times more protein was loaded 140 00:07:01,080 --> 00:07:03,330 into this well, so I think that's just 141 00:07:03,330 --> 00:07:06,240 so you can see the signal. 142 00:07:06,240 --> 00:07:08,580 But I think that just shows to prove 143 00:07:08,580 --> 00:07:10,950 that the higher molecular weight proteins are 144 00:07:10,950 --> 00:07:14,110 more enriched in that lane. 145 00:07:14,110 --> 00:07:15,840 ELIZABETH NOLAN: Yeah. 146 00:07:15,840 --> 00:07:19,350 So are many proteins immunoprecipitated? 147 00:07:19,350 --> 00:07:20,005 AUDIENCE: Yes. 148 00:07:20,005 --> 00:07:20,880 ELIZABETH NOLAN: Yes. 149 00:07:20,880 --> 00:07:21,510 Right. 150 00:07:21,510 --> 00:07:24,970 We see many bands across a range of molecular weights. 151 00:07:24,970 --> 00:07:25,470 Right. 152 00:07:25,470 --> 00:07:29,010 And then as Kenny said, we're seeing much more intensity 153 00:07:29,010 --> 00:07:30,940 up here than down here. 154 00:07:30,940 --> 00:07:31,440 Right. 155 00:07:31,440 --> 00:07:35,550 So it looks like polypeptides in the range of about 20 to about 156 00:07:35,550 --> 00:07:39,750 60 kilodaltons are enriched. 157 00:07:39,750 --> 00:07:43,290 So maybe there's some preference in that size range here. 158 00:07:46,200 --> 00:07:48,820 So that's a good observation. 159 00:07:48,820 --> 00:07:50,670 What do we see in lane four? 160 00:07:54,510 --> 00:07:56,005 What happened for this sample? 161 00:08:01,270 --> 00:08:03,820 So effectively, the crude cell lysate, 162 00:08:03,820 --> 00:08:06,340 those extracts were treated with SDS. 163 00:08:06,340 --> 00:08:08,093 AUDIENCE: They didn't bind anything? 164 00:08:08,093 --> 00:08:09,010 ELIZABETH NOLAN: Yeah. 165 00:08:09,010 --> 00:08:10,510 So nothing bound. 166 00:08:10,510 --> 00:08:11,890 Right. 167 00:08:11,890 --> 00:08:12,760 What do we see here? 168 00:08:12,760 --> 00:08:15,250 Just one band for DnaK. 169 00:08:15,250 --> 00:08:17,155 So why didn't DnaK bind anything? 170 00:08:19,892 --> 00:08:23,063 AUDIENCE: It's denatured by the SDS. 171 00:08:23,063 --> 00:08:23,980 ELIZABETH NOLAN: Yeah. 172 00:08:23,980 --> 00:08:25,030 Not the page... 173 00:08:25,030 --> 00:08:26,530 which is the sodium dodecyl sulfate. 174 00:08:26,530 --> 00:08:26,620 Right. 175 00:08:26,620 --> 00:08:28,688 It's a denaturant and it will denature things. 176 00:08:28,688 --> 00:08:29,980 They don't need to be in a gel. 177 00:08:29,980 --> 00:08:31,810 If you add that to a sample, you'll 178 00:08:31,810 --> 00:08:33,970 have denaturation, right? 179 00:08:33,970 --> 00:08:40,090 So when these samples were denatured, DnaK didn't bind. 180 00:08:40,090 --> 00:08:43,640 Do we think that the SDS denatured DnaK itself? 181 00:08:43,640 --> 00:08:44,140 Right. 182 00:08:44,140 --> 00:08:48,780 So we do see one band here. 183 00:08:48,780 --> 00:08:52,190 Is that surprising? 184 00:08:52,190 --> 00:08:56,440 AUDIENCE: No, because if the DnaK line is suggesting 185 00:08:56,440 --> 00:08:59,070 that that's the molecular weight of of DnaK, it's around there. 186 00:08:59,070 --> 00:09:02,260 And the antibody you're using to do immunoprecipitation... 187 00:09:02,260 --> 00:09:04,560 I mean, would likely probably sub the other bind. 188 00:09:04,560 --> 00:09:05,477 ELIZABETH NOLAN: Yeah. 189 00:09:05,477 --> 00:09:07,370 So the antibody was still able to bind. 190 00:09:07,370 --> 00:09:07,870 Right. 191 00:09:07,870 --> 00:09:10,350 What kind of gel is this? 192 00:09:10,350 --> 00:09:13,016 Well, it's SDS page, but how is it being monitored? 193 00:09:15,992 --> 00:09:19,293 AUDIENCE: It's a [INAUDIBLE] so it's a biodome radiogram. 194 00:09:19,293 --> 00:09:20,210 ELIZABETH NOLAN: Yeah. 195 00:09:20,210 --> 00:09:22,050 We're looking at radioactivity too 196 00:09:22,050 --> 00:09:24,420 so just to keep that in mind for the ban. 197 00:09:24,420 --> 00:09:25,080 Right. 198 00:09:25,080 --> 00:09:27,600 That's what's allowing us to see. 199 00:09:27,600 --> 00:09:28,505 What about lane five? 200 00:09:31,350 --> 00:09:33,750 AUDIENCE: It shows that in the delta DnaK line 201 00:09:33,750 --> 00:09:36,470 that nothing's pulled down by the immunoprecipitation. 202 00:09:36,470 --> 00:09:37,428 ELIZABETH NOLAN: Right. 203 00:09:37,428 --> 00:09:37,993 So no DnaK. 204 00:09:37,993 --> 00:09:38,910 Nothing's pulled down. 205 00:09:38,910 --> 00:09:42,140 This is a very helpful control, because imagine 206 00:09:42,140 --> 00:09:45,020 if you did see bands, that would indicate that there's 207 00:09:45,020 --> 00:09:48,170 some lack of selectivity with this immunoprecipitation step. 208 00:09:48,170 --> 00:09:50,540 So I think that's quite a nice experiment they added 209 00:09:50,540 --> 00:09:53,840 into this piece of work here. 210 00:09:53,840 --> 00:09:54,710 OK. 211 00:09:54,710 --> 00:10:00,320 So moving on to their next experiment, 212 00:10:00,320 --> 00:10:03,050 what happens during the chase if we look at different time 213 00:10:03,050 --> 00:10:05,090 points during the chase period? 214 00:10:05,090 --> 00:10:08,240 So this is similar again to what was done with the GroEL/GroES 215 00:10:08,240 --> 00:10:09,500 study. 216 00:10:09,500 --> 00:10:13,130 So what we're looking at is a one DSDS page. 217 00:10:13,130 --> 00:10:15,140 We have the molecular weight marker. 218 00:10:15,140 --> 00:10:18,080 All of these are with the immunoprecipitation. 219 00:10:18,080 --> 00:10:22,130 And we're looking at times from below one minute 220 00:10:22,130 --> 00:10:23,700 up to 10 minutes. 221 00:10:23,700 --> 00:10:27,980 So the question is what do we see in these data here. 222 00:10:32,273 --> 00:10:34,670 AUDIENCE: As time goes on, you see 223 00:10:34,670 --> 00:10:37,325 more and more concentrations of the smaller proteins. 224 00:10:37,325 --> 00:10:38,200 ELIZABETH NOLAN: Yes. 225 00:10:38,200 --> 00:10:41,310 So we're seeing fewer proteins as time passes. 226 00:10:41,310 --> 00:10:41,810 Right. 227 00:10:41,810 --> 00:10:44,555 Let's start with the first time point here. 228 00:10:44,555 --> 00:10:46,430 Does that look to be in pretty good agreement 229 00:10:46,430 --> 00:10:49,500 to what we saw on the prior slide? 230 00:10:49,500 --> 00:10:50,000 Right. 231 00:10:50,000 --> 00:10:52,610 We see that there's a number of polypeptides 232 00:10:52,610 --> 00:10:54,540 that DnaK is interacting with. 233 00:10:54,540 --> 00:10:55,040 Right. 234 00:10:55,040 --> 00:10:57,450 And they're over a range of molecular weights. 235 00:10:57,450 --> 00:10:57,950 Right. 236 00:10:57,950 --> 00:11:01,580 And then exactly as we just heard, as time progresses, 237 00:11:01,580 --> 00:11:04,250 what we see is, overall, there's fewer polypeptides. 238 00:11:04,250 --> 00:11:06,230 But it looks like there's fewer polypeptides 239 00:11:06,230 --> 00:11:10,840 of lower molecular weight here. 240 00:11:10,840 --> 00:11:15,710 So what does this suggest if you're 241 00:11:15,710 --> 00:11:18,035 going to interpret the data? 242 00:11:18,035 --> 00:11:20,243 AUDIENCE: Probably that lower molecular rate peptides 243 00:11:20,243 --> 00:11:22,053 are folded more quickly. 244 00:11:22,053 --> 00:11:22,970 ELIZABETH NOLAN: Yeah. 245 00:11:22,970 --> 00:11:26,410 So maybe the folding there is complete over this time 246 00:11:26,410 --> 00:11:31,220 or it's complete to a point that DnaK isn't needed anymore. 247 00:11:31,220 --> 00:11:33,370 Right here. 248 00:11:33,370 --> 00:11:35,230 What do you think about the DnaK band? 249 00:11:40,942 --> 00:11:42,380 AUDIENCE: Quite constant. 250 00:11:42,380 --> 00:11:43,027 AUDIENCE: Yeah. 251 00:11:43,027 --> 00:11:44,360 ELIZABETH NOLAN: Quite constant. 252 00:11:44,360 --> 00:11:46,590 So does that make sense? 253 00:11:46,590 --> 00:11:48,130 Yeah, why does that make sense? 254 00:11:51,930 --> 00:11:54,720 AUDIENCE: Because it's just the whole quantity is not changing. 255 00:11:54,720 --> 00:11:56,220 And it's not involving [INAUDIBLE].. 256 00:11:56,220 --> 00:11:59,860 Just like in the case of the less [INAUDIBLE] so when 257 00:11:59,860 --> 00:12:00,892 [INAUDIBLE]. 258 00:12:00,892 --> 00:12:02,100 ELIZABETH NOLAN: Yeah, right? 259 00:12:02,100 --> 00:12:04,980 So there was some newly-- what this indicates, right? 260 00:12:04,980 --> 00:12:07,560 There was some newly synthesized DnaK 261 00:12:07,560 --> 00:12:10,090 in those 15 seconds of the pulse. 262 00:12:10,090 --> 00:12:10,590 Right? 263 00:12:10,590 --> 00:12:12,030 And that has stuck around. 264 00:12:12,030 --> 00:12:16,590 And that's all precipitated to the same degree in each sample 265 00:12:16,590 --> 00:12:18,150 here. 266 00:12:18,150 --> 00:12:21,390 So what about this data here? 267 00:12:21,390 --> 00:12:23,710 And then, how helpful is this data? 268 00:12:23,710 --> 00:12:24,210 Right? 269 00:12:24,210 --> 00:12:27,090 So effectively, what was done is, 270 00:12:27,090 --> 00:12:30,820 radioactivity was measured by liquid scintillation counting. 271 00:12:30,820 --> 00:12:35,160 OK, so they measured the total radioactivity in each sample 272 00:12:35,160 --> 00:12:38,040 prior to separation. 273 00:12:38,040 --> 00:12:41,910 And then, they've converted that to some arbitrary scale 274 00:12:41,910 --> 00:12:43,560 of proteins bound to DnaK. 275 00:12:51,040 --> 00:12:51,540 Right? 276 00:12:51,540 --> 00:12:54,720 So we see that, over time, the total radioactivity 277 00:12:54,720 --> 00:12:58,590 decreases and effectively comes to some sort of plateau. 278 00:12:58,590 --> 00:13:01,290 So that's just some nice quantitation 279 00:13:01,290 --> 00:13:03,750 in terms of what we see here in the gel, right? 280 00:13:03,750 --> 00:13:06,540 It's quite easy to measure the total radioactivity 281 00:13:06,540 --> 00:13:07,650 in a sample. 282 00:13:07,650 --> 00:13:10,120 And you get a measure of that from liquid scintillation 283 00:13:10,120 --> 00:13:10,620 counting. 284 00:13:10,620 --> 00:13:12,690 And then, you can look at the gel, right? 285 00:13:12,690 --> 00:13:15,030 And they're in good agreement there. 286 00:13:15,030 --> 00:13:16,920 And as I said, this is completely arbitrary, 287 00:13:16,920 --> 00:13:17,795 what's on the y-axis. 288 00:13:20,200 --> 00:13:24,840 So do these experiments tell us much about the specifics 289 00:13:24,840 --> 00:13:27,780 of DnaK function? 290 00:13:27,780 --> 00:13:30,300 So we see polypeptides being bound. 291 00:13:30,300 --> 00:13:32,690 We see over time that fewer are bound. 292 00:13:32,690 --> 00:13:34,410 What's actually happening in the cell? 293 00:13:43,427 --> 00:13:45,760 AUDIENCE: I don't think we can conclude much from these. 294 00:13:45,760 --> 00:13:49,500 Only that we know that it interacts with the polypeptides 295 00:13:49,500 --> 00:13:51,213 for some amount of time. 296 00:13:51,213 --> 00:13:52,130 ELIZABETH NOLAN: Yeah. 297 00:13:52,130 --> 00:13:52,630 Right. 298 00:13:52,630 --> 00:13:53,150 I agree. 299 00:13:53,150 --> 00:13:56,360 So is it acting as a foldase? 300 00:13:56,360 --> 00:13:58,450 Is it acting as an holdase-- 301 00:13:58,450 --> 00:14:00,230 an un-foldase? 302 00:14:00,230 --> 00:14:06,440 That's not clear from the data presented in these experiments. 303 00:14:06,440 --> 00:14:09,170 And I'd say overall, there are studies 304 00:14:09,170 --> 00:14:12,890 that show different things, depending on the system there, 305 00:14:12,890 --> 00:14:14,510 for this. 306 00:14:14,510 --> 00:14:18,620 So that's where we're going to close 307 00:14:18,620 --> 00:14:21,320 with the chaperone systems. 308 00:14:21,320 --> 00:14:24,950 And where we're going to move into-- 309 00:14:24,950 --> 00:14:27,890 actually, one more comment, right, 310 00:14:27,890 --> 00:14:29,780 before closing on the chaperones. 311 00:14:33,430 --> 00:14:35,470 What happens if certain ones are deleted? 312 00:14:35,470 --> 00:14:38,500 So just to reiterate, not all of these systems 313 00:14:38,500 --> 00:14:41,710 are required for cell viability of E. coli. 314 00:14:41,710 --> 00:14:43,880 It's only GroEL/GroES. 315 00:14:43,880 --> 00:14:44,380 Right? 316 00:14:44,380 --> 00:14:50,650 So you might ask if trigger factor or DnaK or DnaJ 317 00:14:50,650 --> 00:14:53,650 is deleted, what happens in the cell 318 00:14:53,650 --> 00:14:56,350 to keep things functioning properly? 319 00:14:56,350 --> 00:14:58,810 And just one observation. 320 00:14:58,810 --> 00:15:01,420 If trigger factor is deleted, OK, there's 321 00:15:01,420 --> 00:15:03,310 no growth phenotype. 322 00:15:03,310 --> 00:15:05,050 Is that surprising? 323 00:15:05,050 --> 00:15:06,760 Right? 324 00:15:06,760 --> 00:15:09,370 That observation may depend on growth conditions. 325 00:15:09,370 --> 00:15:11,873 But say you're in some standard growth conditions. 326 00:15:11,873 --> 00:15:14,290 What's observed is that, in the absence of trigger factor, 327 00:15:14,290 --> 00:15:18,460 DnaK and J can basically compensate 328 00:15:18,460 --> 00:15:20,790 for that loss of function. 329 00:15:20,790 --> 00:15:21,520 OK? 330 00:15:21,520 --> 00:15:24,970 But then, if trigger factor and DnaK 331 00:15:24,970 --> 00:15:26,950 are deleted, at higher temperatures, 332 00:15:26,950 --> 00:15:28,640 that becomes lethal here. 333 00:15:28,640 --> 00:15:29,140 OK? 334 00:15:29,140 --> 00:15:32,290 The cells can't cope for that. 335 00:15:32,290 --> 00:15:34,660 But at lower temperature, GroEL/GroES 336 00:15:34,660 --> 00:15:37,135 can compensate for that loss of function. 337 00:15:39,870 --> 00:15:40,490 OK. 338 00:15:40,490 --> 00:15:43,010 So we're on to protein degradation. 339 00:15:43,010 --> 00:15:46,910 There's some incredible macromolecular machines 340 00:15:46,910 --> 00:15:49,790 involved in this unit here. 341 00:15:49,790 --> 00:15:53,593 And we'll move on to that one come Wednesday. 342 00:15:53,593 --> 00:15:55,010 Just if we think about where we're 343 00:15:55,010 --> 00:15:59,120 going with lifecycle of a protein, 344 00:15:59,120 --> 00:16:06,520 right, we've gone from synthesis to folding. 345 00:16:10,060 --> 00:16:11,935 We've learned that misfolding can occur. 346 00:16:16,110 --> 00:16:16,870 OK? 347 00:16:16,870 --> 00:16:19,660 And at some point these polypeptides, 348 00:16:19,660 --> 00:16:22,330 whether they're folded or unfolded, need to be degraded. 349 00:16:22,330 --> 00:16:25,270 So they have some lifetime in the cell. 350 00:16:31,549 --> 00:16:32,520 OK? 351 00:16:32,520 --> 00:16:38,640 And so we can think about proteases, 352 00:16:38,640 --> 00:16:40,740 so classical enzymes, like trypsin. 353 00:16:47,260 --> 00:16:53,980 And we can think about proteasomes, 354 00:16:53,980 --> 00:16:55,300 which are degradation chambers. 355 00:17:04,980 --> 00:17:10,050 And these players are really important because they 356 00:17:10,050 --> 00:17:14,270 have a role, big picture, in controlling 357 00:17:14,270 --> 00:17:22,345 the dynamics and lifetimes of all proteins and cells. 358 00:17:39,270 --> 00:17:44,540 So what are some of our questions for this module? 359 00:17:44,540 --> 00:17:46,370 Why are proteins degraded? 360 00:17:46,370 --> 00:17:48,560 We just said a little bit about that. 361 00:17:48,560 --> 00:17:51,650 How are proteins degraded? 362 00:17:51,650 --> 00:17:54,620 And what types of proteases exist? 363 00:17:54,620 --> 00:17:59,720 We'll briefly today touch upon the general catalytic mechanism 364 00:17:59,720 --> 00:18:02,930 because that's important to have this background for thinking 365 00:18:02,930 --> 00:18:04,660 about the degradation chambers. 366 00:18:04,660 --> 00:18:07,310 So what are the general mechanisms and 367 00:18:07,310 --> 00:18:09,980 what are the active site machineries? 368 00:18:09,980 --> 00:18:13,460 Protease inhibitors are really important at the lab bench, 369 00:18:13,460 --> 00:18:16,010 and they also have a big role in therapeutics. 370 00:18:16,010 --> 00:18:19,580 And so we'll talk about those a bit here. 371 00:18:19,580 --> 00:18:22,910 And then moving into protein degradation machines, 372 00:18:22,910 --> 00:18:28,430 we're going to look at ClpXP from E. coli as a case study. 373 00:18:28,430 --> 00:18:29,960 So we need to think about, what are 374 00:18:29,960 --> 00:18:33,320 the structures of these degradation machines, what 375 00:18:33,320 --> 00:18:35,450 are the mechanisms? 376 00:18:35,450 --> 00:18:38,410 How do they differ in prokaryotes and eukaryotes? 377 00:18:38,410 --> 00:18:40,280 So after spring break, Joanne will 378 00:18:40,280 --> 00:18:43,440 spend some time talking about the eukaryotic proteasome 379 00:18:43,440 --> 00:18:43,940 there. 380 00:18:43,940 --> 00:18:46,100 We won't talk about it as much immediately here, 381 00:18:46,100 --> 00:18:49,200 but we'll come back to that later. 382 00:18:49,200 --> 00:18:53,090 And how are proteins that are destined for degradation 383 00:18:53,090 --> 00:18:57,800 by a proteasome tagged to get to that destination? 384 00:18:57,800 --> 00:19:00,020 So here are our topics. 385 00:19:00,020 --> 00:19:02,660 An overview, which is where we'll focus today. 386 00:19:02,660 --> 00:19:05,960 And then, looking at ClpXP, and down the road, 387 00:19:05,960 --> 00:19:09,530 the 26S proteasome. 388 00:19:09,530 --> 00:19:13,940 So first, thinking about proteases. 389 00:19:13,940 --> 00:19:17,420 Some general points to get everyone up to speed. 390 00:19:17,420 --> 00:19:22,300 So because we all know proteases catalyze the hydrolysis 391 00:19:22,300 --> 00:19:24,270 of peptide bonds. 392 00:19:24,270 --> 00:19:26,600 So we can just think of some peptide 393 00:19:26,600 --> 00:19:30,140 and that peptide bond gets hydrolyzed to give us 394 00:19:30,140 --> 00:19:32,450 these products here. 395 00:19:32,450 --> 00:19:36,470 Why do we need a protease? 396 00:19:36,470 --> 00:19:40,270 The bottom line is just that spontaneous hydrolysis 397 00:19:40,270 --> 00:19:43,070 of peptide bonds is very slow, right? 398 00:19:43,070 --> 00:19:46,400 So we can leave a protein or a polypeptide on the bench top. 399 00:19:46,400 --> 00:19:48,170 And maybe it will unfold. 400 00:19:48,170 --> 00:19:49,490 Maybe it will precipitate. 401 00:19:49,490 --> 00:19:52,430 But it's not going to have the peptide bonds being 402 00:19:52,430 --> 00:19:56,030 broken unless something else has been done to it, right? 403 00:19:56,030 --> 00:19:57,500 So we can think about a half life 404 00:19:57,500 --> 00:20:00,180 on the order of seven years. 405 00:20:00,180 --> 00:20:03,770 And so proteases give tremendous rate accelerations 406 00:20:03,770 --> 00:20:06,740 on the order of 10 to the ninth. 407 00:20:06,740 --> 00:20:09,480 And we can just think about chemistry for a minute 408 00:20:09,480 --> 00:20:11,150 and what we might do as a chemist 409 00:20:11,150 --> 00:20:13,590 to hydrolyze a peptide bond. 410 00:20:13,590 --> 00:20:17,580 So hydrolysis is pH dependent. 411 00:20:17,580 --> 00:20:20,570 And so in chemistry we'll use acid or base 412 00:20:20,570 --> 00:20:22,610 to hydrolyze a peptide bond. 413 00:20:22,610 --> 00:20:25,820 And we can think about base catalyzed reactions, 414 00:20:25,820 --> 00:20:29,720 such as this one, where we have our OH-minus group 415 00:20:29,720 --> 00:20:34,710 attacking, or acid-catalyzed reactions, as this one here. 416 00:20:34,710 --> 00:20:35,600 OK? 417 00:20:35,600 --> 00:20:40,220 So effectively we can just think about pH dependence 418 00:20:40,220 --> 00:20:41,045 of hydrolysis. 419 00:20:55,330 --> 00:21:00,340 Just if we have rate and we have pH. 420 00:21:05,000 --> 00:21:07,400 Something on the order of this, right? 421 00:21:07,400 --> 00:21:10,370 Where we have enhancements at low and high pH 422 00:21:10,370 --> 00:21:14,669 and a relative minimum at neutral pH here for that. 423 00:21:17,840 --> 00:21:20,390 And so these types of chemistry is 424 00:21:20,390 --> 00:21:23,420 going to come up in the context of the protease enzymes, 425 00:21:23,420 --> 00:21:25,790 depending on the type, as we'll see in a few slides. 426 00:21:29,100 --> 00:21:36,690 So we can think about proteases as being 427 00:21:36,690 --> 00:21:39,430 irreversible biological switches, 428 00:21:39,430 --> 00:21:43,590 that these reactions are irreversible. 429 00:21:43,590 --> 00:21:47,670 And what does this mean from the standpoint of the cell? 430 00:21:47,670 --> 00:21:50,880 It means that the cell needs some way 431 00:21:50,880 --> 00:21:53,620 to handle and deal with these proteases, 432 00:21:53,620 --> 00:21:57,330 right, such that they don't cause unnecessary hydrolysis 433 00:21:57,330 --> 00:21:58,350 of polypeptides. 434 00:21:58,350 --> 00:22:00,480 That would be very deleterious to the cell, 435 00:22:00,480 --> 00:22:05,190 right, if a protease was running rampant and hydrolyzing 436 00:22:05,190 --> 00:22:08,590 proteins that it shouldn't here. 437 00:22:08,590 --> 00:22:14,100 So what are some strategies that the cell can use? 438 00:22:14,100 --> 00:22:19,290 One, cells are quite good at controlling protease activity, 439 00:22:19,290 --> 00:22:21,780 both in terms of space and time. 440 00:22:21,780 --> 00:22:23,940 And there's a variety of different strategies, 441 00:22:23,940 --> 00:22:27,240 depending on the locale and the protease. 442 00:22:27,240 --> 00:22:29,790 So regulation is really key here. 443 00:22:29,790 --> 00:22:33,340 And some examples are provided here. 444 00:22:33,340 --> 00:22:36,990 So one is that proteases will be stored as zymogens 445 00:22:36,990 --> 00:22:39,210 or inactivated precursors. 446 00:22:39,210 --> 00:22:40,890 And there'll have to be some event that 447 00:22:40,890 --> 00:22:45,870 activates this zymogen to give the active protease. 448 00:22:45,870 --> 00:22:50,250 Proteases can be stored in separate organelles here. 449 00:22:50,250 --> 00:22:54,690 So these might be zymogen granules or lysosomes. 450 00:22:54,690 --> 00:22:57,360 And sometimes they're stored with a protease inhibitor, 451 00:22:57,360 --> 00:22:59,190 as well. 452 00:22:59,190 --> 00:23:00,990 And another strategy, which is really 453 00:23:00,990 --> 00:23:04,410 the strategy we're going to focus on as we move forward 454 00:23:04,410 --> 00:23:07,830 in this module, is that degradation chambers 455 00:23:07,830 --> 00:23:10,500 are used, such that you have this huge macromolecular 456 00:23:10,500 --> 00:23:13,170 machine where all of the protease activity 457 00:23:13,170 --> 00:23:14,670 is in the inside. 458 00:23:14,670 --> 00:23:19,080 And what this means is that somehow a condemned protein 459 00:23:19,080 --> 00:23:21,510 that needs to be degraded by this machine 460 00:23:21,510 --> 00:23:22,770 needs to be tagged. 461 00:23:22,770 --> 00:23:24,720 And there needs to be some mechanism to get it 462 00:23:24,720 --> 00:23:26,550 in the inside of the chamber. 463 00:23:26,550 --> 00:23:29,700 So effectively, degradation will limit 464 00:23:29,700 --> 00:23:32,610 access of the active sites to the rest 465 00:23:32,610 --> 00:23:34,540 of the cellular environment. 466 00:23:34,540 --> 00:23:41,640 So that's what we see in ClpXP and this 26S proteasome. 467 00:23:41,640 --> 00:23:45,660 Just to note-- so just the other week in C&E News, 468 00:23:45,660 --> 00:23:48,570 there is a highlight of a pretty exciting paper. 469 00:23:48,570 --> 00:23:51,960 So I noted that proteases are of interest 470 00:23:51,960 --> 00:23:54,960 and important from therapeutic development. 471 00:23:54,960 --> 00:23:59,730 And here's a little excerpt about a molecule shown here 472 00:23:59,730 --> 00:24:05,210 that's found to hit the proteasome of malaria parasite. 473 00:24:05,210 --> 00:24:07,200 And so hopefully, by the end of this unit, 474 00:24:07,200 --> 00:24:09,330 if you go back and read this, you'll 475 00:24:09,330 --> 00:24:11,940 have some sense as to why is this a good inhibitor 476 00:24:11,940 --> 00:24:14,640 of the proteasome or a protease. 477 00:24:14,640 --> 00:24:19,620 And what's going on in terms of the proteasome machinery here. 478 00:24:19,620 --> 00:24:22,350 And how can we differentiate proteasomes 479 00:24:22,350 --> 00:24:23,790 from different organisms. 480 00:24:27,980 --> 00:24:31,280 Back to some of the strategies. 481 00:24:31,280 --> 00:24:34,330 Just an example is zymogen activation, 482 00:24:34,330 --> 00:24:37,430 and thinking a little bit from the perspective 483 00:24:37,430 --> 00:24:39,360 of the organism. 484 00:24:39,360 --> 00:24:42,320 So here, we can think about the gut. 485 00:24:42,320 --> 00:24:44,210 We're in the small intestine. 486 00:24:44,210 --> 00:24:48,200 So there's the epithelium, the cells, these are crypts. 487 00:24:48,200 --> 00:24:51,410 And here's the lumen, so the space where the food goes 488 00:24:51,410 --> 00:24:53,180 through, et cetera. 489 00:24:53,180 --> 00:24:54,920 What do we see? 490 00:24:54,920 --> 00:24:59,900 So inside the intestine, there's a protease named entarokinase. 491 00:24:59,900 --> 00:25:03,260 And it has a role of activating trypsinogen. 492 00:25:03,260 --> 00:25:08,390 So trypsinogen is a zymogen. It's produced by the pancreas. 493 00:25:08,390 --> 00:25:12,200 And the pancreas delivers trypsinogen and other things 494 00:25:12,200 --> 00:25:14,490 into the small intestine. 495 00:25:14,490 --> 00:25:17,570 And so once it reaches the small intestine where its activity is 496 00:25:17,570 --> 00:25:21,230 needed, it will be activated by the action of entarokinase 497 00:25:21,230 --> 00:25:22,800 to give trypsin. 498 00:25:22,800 --> 00:25:23,300 OK? 499 00:25:23,300 --> 00:25:25,130 And then what can happen? 500 00:25:25,130 --> 00:25:28,220 Trypsin can also activate trypsinogen, 501 00:25:28,220 --> 00:25:31,160 and it will also activate chymotrypsinogen 502 00:25:31,160 --> 00:25:32,810 to give chymotrypsin. 503 00:25:32,810 --> 00:25:33,310 Right? 504 00:25:33,310 --> 00:25:36,590 So the net result here is protease activity 505 00:25:36,590 --> 00:25:39,290 in the intestinal lumen, which is the extracellular 506 00:25:39,290 --> 00:25:42,120 space here. 507 00:25:42,120 --> 00:25:45,020 And so they travel from the pancreas 508 00:25:45,020 --> 00:25:46,940 in a form that's inactive and then 509 00:25:46,940 --> 00:25:50,030 become active in the intestinal lumen there. 510 00:25:53,160 --> 00:25:57,840 So as I said before, proteases are important. 511 00:25:57,840 --> 00:26:01,380 And if we think about this role in controlling dynamics 512 00:26:01,380 --> 00:26:06,870 and lifetimes of proteins and cells, what 513 00:26:06,870 --> 00:26:09,163 are some of those roles? 514 00:26:09,163 --> 00:26:10,830 And I guess I also point out this also-- 515 00:26:10,830 --> 00:26:14,080 they also can exist in the extracellular space. 516 00:26:14,080 --> 00:26:17,520 So if we think about homeostasis and how 517 00:26:17,520 --> 00:26:20,880 proteases can regulate homeostasis, just 518 00:26:20,880 --> 00:26:21,840 some examples. 519 00:26:21,840 --> 00:26:24,420 They can remove misfolded proteins 520 00:26:24,420 --> 00:26:27,150 or aggregated proteins. 521 00:26:27,150 --> 00:26:30,000 They can provide amino acids when needed, right? 522 00:26:30,000 --> 00:26:33,150 So after destruction of a polypeptide, 523 00:26:33,150 --> 00:26:37,770 you have small fragments or amino acid monomers. 524 00:26:37,770 --> 00:26:40,900 And they can modulate many cellular functions. 525 00:26:40,900 --> 00:26:42,460 So just some examples. 526 00:26:42,460 --> 00:26:44,670 And this is to show the broad range. 527 00:26:44,670 --> 00:26:47,310 We can think about blood clotting, the generation 528 00:26:47,310 --> 00:26:52,690 of hormones, just digestion and recycling of amino acids. 529 00:26:52,690 --> 00:26:56,130 So energy harvesting, the cell cycle, 530 00:26:56,130 --> 00:26:59,290 control of the cell cycle, and even cell deaths. 531 00:26:59,290 --> 00:27:02,240 So thinking about apoptosis here. 532 00:27:02,240 --> 00:27:05,040 And if we just select two of these cellular functions 533 00:27:05,040 --> 00:27:09,690 and how proteases play a role, what I have here 534 00:27:09,690 --> 00:27:14,250 is the maturation of insulin, a peptide hormone in the blood 535 00:27:14,250 --> 00:27:16,690 coagulation cascade. 536 00:27:16,690 --> 00:27:18,290 OK, so if we take a look, insulin 537 00:27:18,290 --> 00:27:20,250 is a really terrific molecule. 538 00:27:20,250 --> 00:27:24,000 And if you're looking from some trivia not shown here, 539 00:27:24,000 --> 00:27:27,270 it also binds zinc and forms an interesting oligomer. 540 00:27:27,270 --> 00:27:30,960 So if you're interested in metals, that's a good one. 541 00:27:30,960 --> 00:27:32,590 But what do we see? 542 00:27:32,590 --> 00:27:38,000 We see that insulin is synthesized as a prepropeptide. 543 00:27:38,000 --> 00:27:40,800 And so in blue, we have a signal sequence. 544 00:27:40,800 --> 00:27:42,660 And then we have these chains here. 545 00:27:42,660 --> 00:27:46,080 And look, there's a bunch of cysteines, right? 546 00:27:46,080 --> 00:27:48,270 So there's action of a protease. 547 00:27:48,270 --> 00:27:49,110 And what do we see? 548 00:27:49,110 --> 00:27:52,380 The signal sequence is cleaved and at some point 549 00:27:52,380 --> 00:27:54,120 in this process, there's formation 550 00:27:54,120 --> 00:27:58,320 of disulfide bonds, right, in some regiospecific manner. 551 00:27:58,320 --> 00:28:00,570 So this is pro insulin. 552 00:28:00,570 --> 00:28:01,530 And then what happens? 553 00:28:01,530 --> 00:28:04,380 There's another protease cleavage event that gives us 554 00:28:04,380 --> 00:28:05,830 the mature form of insulin. 555 00:28:05,830 --> 00:28:09,090 This grape chain here is removed. 556 00:28:09,090 --> 00:28:09,780 OK? 557 00:28:09,780 --> 00:28:12,600 So this is an example of a hormone being stored 558 00:28:12,600 --> 00:28:14,550 as an inactive precursor. 559 00:28:14,550 --> 00:28:16,320 And actually, there's many peptides 560 00:28:16,320 --> 00:28:18,840 that are stored as inactive precursors. 561 00:28:18,840 --> 00:28:22,650 And then some protease has to come and cleave a pro region. 562 00:28:22,650 --> 00:28:24,690 So in my group, we're interested in a family 563 00:28:24,690 --> 00:28:28,200 of antibacterial peptides called defensins 564 00:28:28,200 --> 00:28:29,790 that are in the intestine. 565 00:28:29,790 --> 00:28:31,470 And they have a pro region. 566 00:28:31,470 --> 00:28:33,510 And it's trypsin or another protease 567 00:28:33,510 --> 00:28:36,720 that comes along and has a cleavage event 568 00:28:36,720 --> 00:28:38,700 to release the active peptide. 569 00:28:38,700 --> 00:28:42,540 So not only limited to insulin here. 570 00:28:42,540 --> 00:28:46,710 If we look at the blood coagulation cascade, 571 00:28:46,710 --> 00:28:48,480 we can imagine that we don't want blood 572 00:28:48,480 --> 00:28:50,700 to coagulate on whim, right? 573 00:28:50,700 --> 00:28:52,320 That'd be a huge problem. 574 00:28:52,320 --> 00:28:58,320 So proteases are required to allow coagulation to occur. 575 00:28:58,320 --> 00:29:02,430 And what we can see here is that prothrombin is converted 576 00:29:02,430 --> 00:29:04,650 to thrombin by a protease. 577 00:29:04,650 --> 00:29:06,780 And thrombin is a serine protease. 578 00:29:06,780 --> 00:29:09,720 And we'll hear more about serine proteases in a little bit. 579 00:29:09,720 --> 00:29:13,260 That converts fibrinogen to fibrin. 580 00:29:13,260 --> 00:29:16,000 And as a result, coagulation occurs. 581 00:29:16,000 --> 00:29:19,580 And that's important for wounds. 582 00:29:19,580 --> 00:29:23,110 And there's many, many other examples. 583 00:29:23,110 --> 00:29:27,480 So if we think about types of proteases and mechanisms 584 00:29:27,480 --> 00:29:31,140 of catalysis, what I just would like you all to be aware of 585 00:29:31,140 --> 00:29:35,250 is that there's two general mechanisms. 586 00:29:35,250 --> 00:29:38,790 And we can think about four different mechanistic varieties 587 00:29:38,790 --> 00:29:40,200 within that. 588 00:29:40,200 --> 00:29:45,690 And so we can divide these up by proteases that are 589 00:29:45,690 --> 00:29:48,250 involved in covalent catalysis. 590 00:29:48,250 --> 00:29:50,400 So there's formation of a covalent 591 00:29:50,400 --> 00:29:52,980 acylenzyme intermediate. 592 00:29:52,980 --> 00:29:56,420 And this is what we'll see for serine proteases, 593 00:29:56,420 --> 00:30:00,510 cysteine proteases, and threonine proteases. 594 00:30:00,510 --> 00:30:04,590 So examples here are quite relevant to this module 595 00:30:04,590 --> 00:30:08,370 as ClpXP is a serine protease. 596 00:30:08,370 --> 00:30:11,820 And as you'll see later on, the eukaryotic proteasome 597 00:30:11,820 --> 00:30:16,140 is an end terminal threonine protease. 598 00:30:16,140 --> 00:30:20,640 The second general type are proteases 599 00:30:20,640 --> 00:30:24,030 that accelerate the direct attack of water 600 00:30:24,030 --> 00:30:26,160 on the substrate. 601 00:30:26,160 --> 00:30:29,220 OK, so this is non-covalent catalysis. 602 00:30:29,220 --> 00:30:33,270 And the types here are aspartyl proteases and zinc proteases. 603 00:30:33,270 --> 00:30:35,460 So there was a question a few lectures ago 604 00:30:35,460 --> 00:30:37,930 if there's metal-dependent proteases. 605 00:30:37,930 --> 00:30:41,650 And the answer is yes, zinc proteases. 606 00:30:41,650 --> 00:30:43,170 And we can also think about these 607 00:30:43,170 --> 00:30:46,290 from the standpoint of the acid and base catalyzed chemistry 608 00:30:46,290 --> 00:30:48,700 we saw before. 609 00:30:48,700 --> 00:30:50,790 So just for some trivia. 610 00:30:50,790 --> 00:30:53,220 If we think about the human proteome-- 611 00:30:53,220 --> 00:30:57,070 533 proteases. 612 00:30:57,070 --> 00:31:00,720 And this is a count here. 613 00:31:00,720 --> 00:31:05,970 So on the order of 200 serine proteases, 140 cysteine, 614 00:31:05,970 --> 00:31:10,720 around 190 metalloproteases, and 21 aspartyl proteases. 615 00:31:10,720 --> 00:31:15,030 So we have many of these enzymes to act 616 00:31:15,030 --> 00:31:17,100 at different places and points. 617 00:31:20,230 --> 00:31:26,080 If we take a look at the active site machinery, what do we see? 618 00:31:26,080 --> 00:31:30,610 So here we have the serine proteases. 619 00:31:30,610 --> 00:31:34,370 They have a catalytic triad comprised of aspartate, 620 00:31:34,370 --> 00:31:37,590 a histidine and a serine here. 621 00:31:37,590 --> 00:31:42,310 Cysteine proteases-- we see a cysteine and a histidine. 622 00:31:42,310 --> 00:31:46,480 And so these are the ones involved in covalent catalysis. 623 00:31:46,480 --> 00:31:49,360 Here we have the non-covalent catalysis. 624 00:31:49,360 --> 00:31:51,790 So the aspartic acid or aspartyl protease. 625 00:31:51,790 --> 00:31:53,650 We have two asp residues. 626 00:31:53,650 --> 00:31:56,620 And here we have an example of a zinc protease, 627 00:31:56,620 --> 00:32:01,240 where we see a single zinc ion coordinated by two histidines, 628 00:32:01,240 --> 00:32:04,320 and in this case, a glutamate and a bound water. 629 00:32:04,320 --> 00:32:05,740 OK? 630 00:32:05,740 --> 00:32:16,790 So if we think about just the covalent 631 00:32:16,790 --> 00:32:29,870 versus non-covalent catalysis here. 632 00:32:34,073 --> 00:32:35,555 So when I get further along. 633 00:32:40,910 --> 00:32:42,995 So imagine we just have some dipeptide. 634 00:32:53,910 --> 00:33:08,350 What we find in these enzymes is that they have what's 635 00:33:08,350 --> 00:33:16,540 called an oxyanion hole here. 636 00:33:16,540 --> 00:33:25,100 And we can think about the enzyme allowing attack as such. 637 00:33:25,100 --> 00:33:30,240 So that or some nucleophile here. 638 00:33:30,240 --> 00:33:31,160 So what do we get? 639 00:33:31,160 --> 00:33:39,510 We get a covalent acylenzyme intermediate. 640 00:33:39,510 --> 00:33:43,010 OK, we have the oxyanion hole. 641 00:33:43,010 --> 00:33:50,960 And these are the serine and the cysteine proteases here. 642 00:33:50,960 --> 00:33:52,050 OK? 643 00:33:52,050 --> 00:33:54,060 And we'll go through in more detail 644 00:33:54,060 --> 00:33:55,850 the mechanism in a minute. 645 00:33:55,850 --> 00:34:08,560 If we think about non-covalent catalysis, 646 00:34:08,560 --> 00:34:10,389 and again, we have our dipeptide. 647 00:34:27,710 --> 00:34:29,719 We can just think about for a minute one 648 00:34:29,719 --> 00:34:31,610 of the metalloproteases, right? 649 00:34:31,610 --> 00:34:34,159 So in these cases, the protease is accelerating 650 00:34:34,159 --> 00:34:35,719 the direct attack by water. 651 00:34:39,290 --> 00:34:44,750 So I imagine we have some metal here 652 00:34:44,750 --> 00:34:47,750 that has water bound, right? 653 00:34:47,750 --> 00:34:50,510 What happens? 654 00:34:50,510 --> 00:34:53,381 Imagine we can de-proteinate the water molecule. 655 00:34:53,381 --> 00:34:54,589 And then there can be attack. 656 00:35:11,920 --> 00:35:26,810 OK, so why does the metalloprotease 657 00:35:26,810 --> 00:35:27,785 allow this to occur? 658 00:35:48,830 --> 00:35:52,550 So what's happening when the water binds to the metal that 659 00:35:52,550 --> 00:35:53,770 will facilitate this? 660 00:36:17,950 --> 00:36:23,440 So we can think about the pKa of a water molecule, right? 661 00:36:23,440 --> 00:36:29,670 And what happens when a water molecule is bound to a metal, 662 00:36:29,670 --> 00:36:30,170 right? 663 00:36:30,170 --> 00:36:32,530 Say zinc. 664 00:36:32,530 --> 00:36:34,000 So how do we think about a metal? 665 00:36:36,958 --> 00:36:37,950 AUDIENCE: A Lewis acid. 666 00:36:37,950 --> 00:36:38,400 ELIZABETH NOLAN: Yeah. 667 00:36:38,400 --> 00:36:38,900 Right? 668 00:36:38,900 --> 00:36:40,410 We have a general Lewis acid here. 669 00:36:47,060 --> 00:36:48,300 Here. 670 00:36:48,300 --> 00:36:52,490 So what's going to be effect of the pKa of the bound water 671 00:36:52,490 --> 00:36:53,900 relative to unbound water? 672 00:36:59,804 --> 00:37:01,502 AUDIENCE: It'll be more acidic. 673 00:37:01,502 --> 00:37:02,460 ELIZABETH NOLAN: Right. 674 00:37:02,460 --> 00:37:04,710 We're going to lower the pKa of the bound water, which 675 00:37:04,710 --> 00:37:07,150 is going to help generate the nucleophile. 676 00:37:07,150 --> 00:37:07,650 Right? 677 00:37:20,390 --> 00:37:26,630 So that's how it's facilitating the direct attack here. 678 00:37:29,450 --> 00:37:33,460 OK, so what we're going to do is look at the serine protease 679 00:37:33,460 --> 00:37:36,150 example in a bit more detail. 680 00:37:36,150 --> 00:37:40,570 AUDIENCE: Are the end termini de-pertinated? 681 00:37:40,570 --> 00:37:41,980 Or is it-- 682 00:37:41,980 --> 00:37:44,500 ELIZABETH NOLAN: I am just-- 683 00:37:44,500 --> 00:37:48,624 what would it be at physiological pH? 684 00:37:48,624 --> 00:37:49,755 AUDIENCE: NH3? 685 00:37:49,755 --> 00:37:51,380 ELIZABETH NOLAN: The embryote NH3 plus. 686 00:37:51,380 --> 00:37:51,880 Right. 687 00:37:51,880 --> 00:37:54,800 So these are just showing a simple dipeptide 688 00:37:54,800 --> 00:37:58,670 that we have NH3 plus and O minus in terms of the acid ends 689 00:37:58,670 --> 00:38:00,790 there. 690 00:38:00,790 --> 00:38:02,330 OK. 691 00:38:02,330 --> 00:38:07,980 So just thinking about here, this covalent catalysis. 692 00:38:07,980 --> 00:38:10,850 So here's each protease type, the active site, 693 00:38:10,850 --> 00:38:12,380 and the nucleophile. 694 00:38:12,380 --> 00:38:14,630 So in the case of the serine proteases, 695 00:38:14,630 --> 00:38:19,580 the nucleophile is the serine side chain. 696 00:38:19,580 --> 00:38:24,410 And I'm showing this because ClpXP-- 697 00:38:24,410 --> 00:38:30,950 ClpP protease-- uses serine protease chemistry here. 698 00:38:30,950 --> 00:38:34,850 So what we observe in this overview 699 00:38:34,850 --> 00:38:37,520 is a generally accepted mechanism. 700 00:38:37,520 --> 00:38:39,830 And we see formation and collapse 701 00:38:39,830 --> 00:38:43,160 of this covalent acylenzyme intermediate. 702 00:38:43,160 --> 00:38:47,300 So if we take a look here, we have a bound polypeptide. 703 00:38:47,300 --> 00:38:52,250 This is the oxyanion hole provided by these two NH. 704 00:38:52,250 --> 00:38:56,100 Here we see the aspartate, the histidine, and the serine. 705 00:38:56,100 --> 00:38:56,600 Right? 706 00:38:56,600 --> 00:38:59,320 So what do we see happening here? 707 00:38:59,320 --> 00:39:02,900 First, there's formation of a tetrahedral intermediate. 708 00:39:02,900 --> 00:39:04,940 So there's an attack. 709 00:39:04,940 --> 00:39:05,510 OK? 710 00:39:05,510 --> 00:39:10,010 And here we have loss of the RNH2. 711 00:39:10,010 --> 00:39:12,480 And here what do we see? 712 00:39:12,480 --> 00:39:19,280 We see, basically, the histidine working on this water molecule. 713 00:39:19,280 --> 00:39:22,110 We have collapse of this acylenzyme intermediate, 714 00:39:22,110 --> 00:39:24,440 another tetrahedral intermediate, and release 715 00:39:24,440 --> 00:39:26,970 of the acid product here. 716 00:39:26,970 --> 00:39:28,160 OK? 717 00:39:28,160 --> 00:39:33,230 So in thinking about this, we think 718 00:39:33,230 --> 00:39:35,570 about the histidine as being a general acid 719 00:39:35,570 --> 00:39:38,960 general base involved in general acid-base catalysis, a proton 720 00:39:38,960 --> 00:39:40,610 carrier. 721 00:39:40,610 --> 00:39:45,340 We see this oxyanion hole providing stabilization 722 00:39:45,340 --> 00:39:46,800 here and here. 723 00:39:46,800 --> 00:39:47,300 Right? 724 00:39:47,300 --> 00:39:49,000 We have this negative charge. 725 00:39:49,000 --> 00:39:52,550 And something that you need to think about are the pKas. 726 00:39:52,550 --> 00:39:55,610 If we think about just pKas of amino acids 727 00:39:55,610 --> 00:39:58,610 and how this chemistry is happening. 728 00:39:58,610 --> 00:39:59,600 Right? 729 00:39:59,600 --> 00:40:02,120 So what is a little bit mysterious here, 730 00:40:02,120 --> 00:40:06,940 based on our knowledge of pKas of the catalytic triad? 731 00:40:06,940 --> 00:40:09,710 And they give some approximate values just for serine, 732 00:40:09,710 --> 00:40:11,690 histidine, and aspartate here. 733 00:40:17,210 --> 00:40:19,580 AUDIENCE: Well, each proton abstraction 734 00:40:19,580 --> 00:40:23,330 is being done by something that should, theoretically, 735 00:40:23,330 --> 00:40:24,220 have a lower pKa. 736 00:40:24,220 --> 00:40:26,690 So you have an aspartate abstracting a proton 737 00:40:26,690 --> 00:40:28,360 from a histidine, which is abstracting 738 00:40:28,360 --> 00:40:29,583 a proton from serine. 739 00:40:29,583 --> 00:40:31,250 So there has to be a lot of perturbation 740 00:40:31,250 --> 00:40:32,550 of the system for that to happen. 741 00:40:32,550 --> 00:40:33,020 ELIZABETH NOLAN: Yeah. 742 00:40:33,020 --> 00:40:33,520 Right. 743 00:40:33,520 --> 00:40:35,780 There needs to be a lot of perturbation to pKas 744 00:40:35,780 --> 00:40:37,310 for this to work, right? 745 00:40:37,310 --> 00:40:40,520 How easy is it to de-proteinate the serine 746 00:40:40,520 --> 00:40:42,290 by a typical histidine? 747 00:40:42,290 --> 00:40:45,278 Is that going to happen based on pKa? 748 00:40:45,278 --> 00:40:45,820 AUDIENCE: No. 749 00:40:45,820 --> 00:40:46,778 ELIZABETH NOLAN: Right? 750 00:40:46,778 --> 00:40:50,660 So there's something about this active site and the environment 751 00:40:50,660 --> 00:40:55,340 that's going to give perturbation of these values. 752 00:40:55,340 --> 00:40:59,810 If we just move beyond this cartoon form for a minute, 753 00:40:59,810 --> 00:41:04,610 and just look at the catalytic triad from chymotrypsin 754 00:41:04,610 --> 00:41:06,530 from a crystal structure. 755 00:41:06,530 --> 00:41:12,890 This is the orientation of the serine histidine and aspartate. 756 00:41:12,890 --> 00:41:17,060 And something to keep in mind is that different serine 757 00:41:17,060 --> 00:41:19,520 proteases, or different proteases in general, 758 00:41:19,520 --> 00:41:22,160 have different substrate specificity's, 759 00:41:22,160 --> 00:41:24,410 which means they prefer to cut before 760 00:41:24,410 --> 00:41:27,380 or after a given type of amino acid, 761 00:41:27,380 --> 00:41:29,450 depending on the side chain. 762 00:41:29,450 --> 00:41:32,450 And this is just a cartoon depiction indicating 763 00:41:32,450 --> 00:41:36,110 that, here's the peptide, here's some side chain, 764 00:41:36,110 --> 00:41:38,600 and there's some recognition site here. 765 00:41:38,600 --> 00:41:41,690 So there's a degree of substrate discrimination. 766 00:41:41,690 --> 00:41:45,740 For instance, trypsin likes to cut after arginine and lysine. 767 00:41:45,740 --> 00:41:49,200 But it will cut at other places, as well. 768 00:41:49,200 --> 00:41:49,700 Right? 769 00:41:49,700 --> 00:41:53,720 Chymotrypsin likes aromatic hydrophobic residues. 770 00:41:53,720 --> 00:41:57,770 Elastase likes small and uncharged residues here 771 00:41:57,770 --> 00:41:58,530 for that. 772 00:41:58,530 --> 00:42:03,350 So you may have seen diagrams or cartoons of specificity pockets 773 00:42:03,350 --> 00:42:06,920 for thinking about substrate discrimination 774 00:42:06,920 --> 00:42:08,870 amongst these proteases. 775 00:42:08,870 --> 00:42:10,580 And I guess what I would just say 776 00:42:10,580 --> 00:42:15,155 is, it's not so simple as those types of cartoons. 777 00:42:17,930 --> 00:42:21,320 If we look at the structures of serine proteases, 778 00:42:21,320 --> 00:42:27,920 just to compare, what we see is that, for trypsin, elastase, 779 00:42:27,920 --> 00:42:32,900 and chymotrypsin, they have similar overall structure. 780 00:42:32,900 --> 00:42:37,100 So this is an overlay of the three enzymes. 781 00:42:37,100 --> 00:42:40,410 And the catalytic triad is shown in red. 782 00:42:40,410 --> 00:42:40,910 OK? 783 00:42:40,910 --> 00:42:44,240 So despite this similar overall structure, 784 00:42:44,240 --> 00:42:47,780 they have distinct substrate preferences. 785 00:42:47,780 --> 00:42:50,280 And it's just something to be aware of. 786 00:42:50,280 --> 00:42:52,670 So you're not responsible for the origins 787 00:42:52,670 --> 00:42:55,040 of this substrate discrimination. 788 00:42:55,040 --> 00:42:56,780 And here's just a view showing more 789 00:42:56,780 --> 00:43:01,040 about the secondary structure of trypsin shown here. 790 00:43:01,040 --> 00:43:03,020 And in this case, there's an inhibitor bound. 791 00:43:07,260 --> 00:43:22,540 And I'll just note, in terms of the substrate preference, 792 00:43:22,540 --> 00:43:24,730 and these are the three types of activity 793 00:43:24,730 --> 00:43:38,000 we'll end up seeing within the eukaryotic proteasome. 794 00:43:38,000 --> 00:43:42,290 So if we just have some polypeptide. 795 00:43:57,260 --> 00:43:57,760 OK? 796 00:44:00,840 --> 00:44:06,600 OK, and so imagine we're thinking about hydrolysis here. 797 00:44:06,600 --> 00:44:10,470 OK, so the C terminal end of this amino acid 798 00:44:10,470 --> 00:44:13,700 with our one side chain. 799 00:44:13,700 --> 00:44:21,450 We think about the enzyme and the identity of R1. 800 00:44:21,450 --> 00:44:30,120 For trypsin, it prefers to cut after arginine or lysine. 801 00:44:30,120 --> 00:44:31,380 OK, so a positive charge. 802 00:44:34,520 --> 00:44:49,010 For chymotrypsin, phenylalanine, tyrosine, and also other ones 803 00:44:49,010 --> 00:44:54,005 like valine, leucine, and isoleucine. 804 00:44:54,005 --> 00:44:59,817 OK, so aromatic plus hydrophobic. 805 00:45:04,690 --> 00:45:10,400 And then elastase here. 806 00:45:10,400 --> 00:45:13,930 And we find that elastase prefers to cut after small. 807 00:45:16,720 --> 00:45:18,730 And if I'm boxing it, these are the ones 808 00:45:18,730 --> 00:45:22,825 we think is most preferred, small and uncharged residues. 809 00:45:34,039 --> 00:45:34,539 OK? 810 00:45:37,510 --> 00:45:41,040 So some discrimination based on side chain identity. 811 00:45:45,560 --> 00:45:49,370 So where we'll close the general background 812 00:45:49,370 --> 00:45:53,970 is just with a note on proteases and disease and protease 813 00:45:53,970 --> 00:45:54,710 inhibition. 814 00:45:57,650 --> 00:46:04,220 So if we consider various human diseases and proteases, 815 00:46:04,220 --> 00:46:06,110 there's many, many links. 816 00:46:06,110 --> 00:46:10,760 And many proteases are implicated in a variety 817 00:46:10,760 --> 00:46:14,270 of diseases and pathologies. 818 00:46:14,270 --> 00:46:17,120 And so this is a table just to give you 819 00:46:17,120 --> 00:46:19,190 a sense of the breadth. 820 00:46:19,190 --> 00:46:21,590 What we see in terms of the class 821 00:46:21,590 --> 00:46:25,400 is that all of the classes are represented here. 822 00:46:25,400 --> 00:46:31,190 And that we see diseases ranging from cardiovascular problems, 823 00:46:31,190 --> 00:46:37,110 to cancer, et cetera, cystic fibrosis, inflammation here. 824 00:46:37,110 --> 00:46:37,610 OK? 825 00:46:37,610 --> 00:46:40,790 So as a result, there is quite a bit of interest 826 00:46:40,790 --> 00:46:44,210 in terms of the possibility of protease inhibitors 827 00:46:44,210 --> 00:46:46,910 as therapeutics. 828 00:46:46,910 --> 00:46:51,440 And beyond that, they're also widely used in the lab. 829 00:46:51,440 --> 00:46:56,750 So how do these inhibitors work? 830 00:46:56,750 --> 00:47:00,920 Just as a general rule of thumb to think about, 831 00:47:00,920 --> 00:47:05,750 generally they react to form a covalent bond 832 00:47:05,750 --> 00:47:07,430 with the catalytic nucleophile. 833 00:47:07,430 --> 00:47:09,590 So for instance, for the serine proteases, 834 00:47:09,590 --> 00:47:12,710 they'll form some covalent bond with the active site serine 835 00:47:12,710 --> 00:47:14,090 residue. 836 00:47:14,090 --> 00:47:16,850 And we can classify these inhibitors 837 00:47:16,850 --> 00:47:20,600 as being either reversible inhibitors or irreversible 838 00:47:20,600 --> 00:47:21,890 inhibitors. 839 00:47:21,890 --> 00:47:26,900 So as those names indicate, if it's a reversible inhibitor, 840 00:47:26,900 --> 00:47:31,850 that covalent linkage between the protease or the proteasome 841 00:47:31,850 --> 00:47:35,360 and the inhibitor can be broken down. 842 00:47:35,360 --> 00:47:38,720 And types of reversible inhibitors, for instance, 843 00:47:38,720 --> 00:47:43,940 use aldehydes as the reactive group. 844 00:47:43,940 --> 00:47:46,520 So in contrast, the irreversible inhibitors 845 00:47:46,520 --> 00:47:51,830 form a covalent linkage that is not readily broken down 846 00:47:51,830 --> 00:47:54,830 with the catalytic nucleophile. 847 00:47:54,830 --> 00:47:58,430 And so irreversible inhibitors include vinylsulfones. 848 00:47:58,430 --> 00:48:00,560 And if you go back and look at that little excerpt 849 00:48:00,560 --> 00:48:03,140 from C&E News about this molecule that's 850 00:48:03,140 --> 00:48:05,570 inhibiting the proteasome of malaria, 851 00:48:05,570 --> 00:48:08,390 you'll see that it has a vinylsulfone on its terminus 852 00:48:08,390 --> 00:48:09,890 here. 853 00:48:09,890 --> 00:48:13,040 Epoxides are also employed. 854 00:48:13,040 --> 00:48:17,630 OK, and generally, if we have inhibitors 855 00:48:17,630 --> 00:48:21,440 that block the function of a protease or a proteasome, 856 00:48:21,440 --> 00:48:23,720 they're going to interfere with many critical cellular 857 00:48:23,720 --> 00:48:25,970 functions right here. 858 00:48:25,970 --> 00:48:30,960 And just in terms of cancer, just some observations. 859 00:48:30,960 --> 00:48:34,670 So it's been found that proliferating cells are 860 00:48:34,670 --> 00:48:37,700 sensitive to proteasome inhibitors. 861 00:48:37,700 --> 00:48:39,860 And there's some proteasome inhibitors 862 00:48:39,860 --> 00:48:42,860 that can selectively induce apoptosis 863 00:48:42,860 --> 00:48:45,320 in proliferating cells. 864 00:48:45,320 --> 00:48:48,080 And so cancer cells are proliferating, 865 00:48:48,080 --> 00:48:53,150 and there's interest in the use of these as anti-cancer drugs. 866 00:48:53,150 --> 00:48:55,460 So what I've included in these slides 867 00:48:55,460 --> 00:48:59,720 are some examples of inhibitors of each class, and then 868 00:48:59,720 --> 00:49:02,390 the mechanisms. 869 00:49:02,390 --> 00:49:06,090 Here are just three molecules. 870 00:49:06,090 --> 00:49:10,520 So we have either reversible or irreversible inhibitors, right? 871 00:49:10,520 --> 00:49:14,000 And what is there to note looking at these molecules? 872 00:49:14,000 --> 00:49:16,460 They're all polypeptide-like. 873 00:49:16,460 --> 00:49:17,120 Right? 874 00:49:17,120 --> 00:49:20,600 So there's amino acids or moieties 875 00:49:20,600 --> 00:49:23,330 that, with a little imagination, we can think about 876 00:49:23,330 --> 00:49:25,260 as being somewhat similar. 877 00:49:25,260 --> 00:49:27,890 And then we see these reactive groups on the terminus. 878 00:49:27,890 --> 00:49:31,202 So the aldehyde, for instance, the vinylsulfone. 879 00:49:31,202 --> 00:49:32,660 And so if you look at the structure 880 00:49:32,660 --> 00:49:36,740 of this molecule being used to inhibit the malaria proteasome, 881 00:49:36,740 --> 00:49:40,310 there's some clear similarities to these here. 882 00:49:40,310 --> 00:49:43,880 In terms of mechanisms, we can think 883 00:49:43,880 --> 00:49:46,460 about these reversible inhibitors. 884 00:49:46,460 --> 00:49:50,840 So for instance, the chemistry with the peptide aldehyde. 885 00:49:50,840 --> 00:49:53,690 Here we're seeing the nucleophile 886 00:49:53,690 --> 00:49:56,000 of the eukaryotic proteasome, which 887 00:49:56,000 --> 00:49:59,270 is really interesting because it's an end terminal threonine. 888 00:49:59,270 --> 00:50:03,080 That's why we're seeing it drawn as such here. 889 00:50:03,080 --> 00:50:07,400 So we can have formation and collapse of this species here. 890 00:50:07,400 --> 00:50:10,580 Or in the case of the irreversible inhibitors, 891 00:50:10,580 --> 00:50:13,730 we have the vinylsulfone and the chemistry 892 00:50:13,730 --> 00:50:17,360 that happens here for that. 893 00:50:17,360 --> 00:50:19,460 And so if you're interested in these, 894 00:50:19,460 --> 00:50:23,810 I encourage you to look at the mechanisms a bit more. 895 00:50:23,810 --> 00:50:26,300 And we'll see a little bit more on inhibitors 896 00:50:26,300 --> 00:50:28,100 being used experimentally as we go 897 00:50:28,100 --> 00:50:30,960 through the rest of this module. 898 00:50:30,960 --> 00:50:33,470 So where we'll start on Wednesday 899 00:50:33,470 --> 00:50:38,690 is looking at the structure of E. coli ClpXP, which 900 00:50:38,690 --> 00:50:43,100 is a degradation machine used to degrade certain condemned 901 00:50:43,100 --> 00:50:44,660 proteins there. 902 00:50:44,660 --> 00:50:46,210 OK?