PROJECT #16495 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE
PROJECT SUMMARY
Kinases are a major target for a variety of cancer therapies, but their mechanism of action is relatively unknown at a detailed atomic level, preventing us from understanding and optimizing known inhibitors.
One example is the Serine/Threonine Kinase RIPK2.
RIPK2 inhibition is useful for cancer targeting as it prevents RIPK2 from binding a protein partner named XIAP.
In fact, there are already 3 known inhibitors that bind to RIPK2 and prevent RIPK2-XIAP binding! However, it remains difficult to optimize these ligands for clinical purposes because we do not understand how any of these three inhibitors actually act on RIPK2 to prevent XIAP binding behavior.
These four projects are simulating RIPK2 by itself and bound to each of the three inhibitors, with the hope that this will reveal a more detailed mechanism of how each inhibitor works to prevent XIAP binding.
As a bonus, this will help reveal how RIPK2 *binds* XIAP (also unknown)! In this set of projects we are studying the following systems: 16466 – RIPK2 16467 – RIPK2:CSLP43 inhibitor-bound complex 16468 – RIPK2:CSLP48 inhibitor-bound complex 16469 – RIPK2:GSK583 inhibitor-bound complex 16470 – RIPK2:WEHI-345 inhibitor-bound complex 16471 – RIPK2:BI inhibitor-bound complex 16488 – RIPK2:BI inhibitor-bound complex (alt configuration) 16489 – RIPK2:BI inhibitor-bound complex (alt configuration 2) 16490 – RIPK2:NVS inhibitor-bound complex 16491 – RIPK2 apo from the GSK bound structure 16492 – RIPK2 apo fro the BI bound structure 16493 – RIPK2 apo from a Gefitinib bound structure 16494 – RIPK2 apo from a Novartis-produced inhibitor 16495 – RIPK2:Gefitinib complex 16496 – RIPK2:Novartis inhibitor structure.
PROJECT INFO
Manager(s): Sukrit Singh
Institution: Memorial Sloan-Kettering Cancer-Center
Project URL: http://sukritsingh.github.io/
PROJECT WORK UNIT SUMMARY
Atoms: 65,418
Core: OPENMM_22
Status: Public
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Tuesday, 07 February 2023 06:14:55
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
---|---|---|---|---|---|---|---|
1 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 4,721,091 | 127,170 | 37.12 | 0 hrs 39 mins |
2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 4,490,213 | 125,549 | 35.76 | 0 hrs 40 mins |
3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 4,413,765 | 124,300 | 35.51 | 0 hrs 41 mins |
4 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 3,865,632 | 120,696 | 32.03 | 0 hrs 45 mins |
5 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,281,614 | 113,977 | 28.79 | 0 hrs 50 mins |
6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,267,826 | 113,685 | 28.74 | 0 hrs 50 mins |
7 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 2,971,398 | 110,793 | 26.82 | 0 hrs 54 mins |
8 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 2,968,107 | 105,318 | 28.18 | 0 hrs 51 mins |
9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,721,623 | 106,065 | 25.66 | 0 hrs 56 mins |
10 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,563,025 | 105,291 | 24.34 | 0 hrs 59 mins |
11 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 2,402,382 | 103,047 | 23.31 | 1 hrs 2 mins |
12 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,081,942 | 95,130 | 21.89 | 1 hrs 6 mins |
13 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,064,530 | 98,076 | 21.05 | 1 hrs 8 mins |
14 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,019,251 | 97,358 | 20.74 | 1 hrs 9 mins |
15 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 1,851,277 | 94,274 | 19.64 | 1 hrs 13 mins |
16 | GeForce RTX 2070 SUPER Mobile / Max-Q TU104M [GeForce RTX 2070 SUPER Mobile / Max-Q] |
Nvidia | TU104M | 1,829,708 | 93,179 | 19.64 | 1 hrs 13 mins |
17 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,656,129 | 90,560 | 18.29 | 1 hrs 19 mins |
18 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,625,904 | 90,328 | 18.00 | 1 hrs 20 mins |
19 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,613,577 | 90,116 | 17.91 | 1 hrs 20 mins |
20 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 1,560,709 | 90,319 | 17.28 | 1 hrs 23 mins |
21 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,517,347 | 88,371 | 17.17 | 1 hrs 24 mins |
22 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,468,186 | 87,503 | 16.78 | 1 hrs 26 mins |
23 | GeForce RTX 2080 Mobile TU104M [GeForce RTX 2080 Mobile] |
Nvidia | TU104M | 1,449,561 | 87,685 | 16.53 | 1 hrs 27 mins |
24 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 1,385,363 | 85,264 | 16.25 | 1 hrs 29 mins |
25 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,223,205 | 81,720 | 14.97 | 2 hrs 36 mins |
26 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,155,654 | 80,624 | 14.33 | 2 hrs 40 mins |
27 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,027,048 | 77,395 | 13.27 | 2 hrs 49 mins |
28 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 881,206 | 73,616 | 11.97 | 2 hrs 0 mins |
29 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 853,787 | 73,330 | 11.64 | 2 hrs 4 mins |
30 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 699,286 | 67,920 | 10.30 | 2 hrs 20 mins |
31 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 662,306 | 66,640 | 9.94 | 2 hrs 25 mins |
32 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 637,174 | 66,420 | 9.59 | 3 hrs 30 mins |
33 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 575,709 | 63,861 | 9.02 | 3 hrs 40 mins |
34 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 469,814 | 59,744 | 7.86 | 3 hrs 3 mins |
35 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 384,189 | 52,970 | 7.25 | 3 hrs 19 mins |
36 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 348,831 | 50,231 | 6.94 | 3 hrs 27 mins |
37 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 287,505 | 50,459 | 5.70 | 4 hrs 13 mins |
38 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 195,357 | 44,686 | 4.37 | 5 hrs 29 mins |
39 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 185,608 | 43,954 | 4.22 | 6 hrs 41 mins |
40 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 109,520 | 36,855 | 2.97 | 8 hrs 5 mins |
41 | GeForce GTX 660 GK106 [GeForce GTX 660] |
Nvidia | GK106 | 109,221 | 36,870 | 2.96 | 8 hrs 6 mins |
42 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 103,505 | 35,789 | 2.89 | 8 hrs 18 mins |
43 | GeForce GT 730 GK208B [GeForce GT 730] 692.7 |
Nvidia | GK208B | 17,929 | 16,518 | 1.09 | 22 hrs 7 mins |
44 | GeForce GT 720 GK208 [GeForce GT 720] |
Nvidia | GK208 | 15,602 | 16,557 | 0.94 | 25 hrs 28 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Tuesday, 07 February 2023 06:14:55
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|