PROJECT #16492 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.

PROJECT INFO

Manager(s): Sukrit Singh

Institution: Memorial Sloan-Kettering Cancer-Center

Project URL: http://sukritsingh.github.io/

PROJECT WORK UNIT SUMMARY

Atoms: 56,311

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 04 December 2022 18:13:27

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 5,599,759 126,737 44.18 0 hrs 33 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,812,043 118,526 40.60 0 hrs 35 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,130,404 114,951 35.93 0 hrs 40 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,105,159 112,019 36.65 0 hrs 39 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,460,956 107,061 32.33 0 hrs 45 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,326,125 106,664 31.18 0 hrs 46 mins
7 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 3,198,921 105,481 30.33 0 hrs 47 mins
8 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 3,193,692 105,860 30.17 0 hrs 48 mins
9 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,175,173 104,951 30.25 0 hrs 48 mins
10 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,001,025 102,995 29.14 0 hrs 49 mins
11 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 2,537,644 97,803 25.95 0 hrs 55 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,458,914 97,326 25.26 0 hrs 57 mins
13 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 2,359,042 95,563 24.69 0 hrs 58 mins
14 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,342,156 94,075 24.90 0 hrs 58 mins
15 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,262,871 101,615 22.27 1 hrs 5 mins
16 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,234,203 93,976 23.77 1 hrs 1 mins
17 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,064,354 91,570 22.54 1 hrs 4 mins
18 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,039,500 90,982 22.42 1 hrs 4 mins
19 GeForce RTX 2070 SUPER Mobile / Max-Q
TU104M [GeForce RTX 2070 SUPER Mobile / Max-Q]
Nvidia TU104M 2,002,651 89,218 22.45 1 hrs 4 mins
20 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 1,849,025 87,743 21.07 1 hrs 8 mins
21 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,772,641 86,758 20.43 1 hrs 10 mins
22 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,765,356 86,719 20.36 1 hrs 11 mins
23 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,734,540 86,325 20.09 1 hrs 12 mins
24 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,720,855 85,644 20.09 1 hrs 12 mins
25 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 1,712,511 85,229 20.09 1 hrs 12 mins
26 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,595,748 83,935 19.01 1 hrs 16 mins
27 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,491,427 80,797 18.46 1 hrs 18 mins
28 GeForce RTX 2080 Mobile
TU104M [GeForce RTX 2080 Mobile]
Nvidia TU104M 1,444,625 79,345 18.21 1 hrs 19 mins
29 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,251,243 76,085 16.45 1 hrs 28 mins
30 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,250,141 76,686 16.30 1 hrs 28 mins
31 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,240,767 76,722 16.17 1 hrs 29 mins
32 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,074,635 73,379 14.64 2 hrs 38 mins
33 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,060,326 72,838 14.56 2 hrs 39 mins
34 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 984,962 70,134 14.04 2 hrs 43 mins
35 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 980,639 69,645 14.08 2 hrs 42 mins
36 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 869,342 68,568 12.68 2 hrs 54 mins
37 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 726,706 64,333 11.30 2 hrs 7 mins
38 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 708,267 63,716 11.12 2 hrs 10 mins
39 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 672,480 62,700 10.73 2 hrs 14 mins
40 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 648,045 61,856 10.48 2 hrs 17 mins
41 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 521,109 50,632 10.29 2 hrs 20 mins
42 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 488,263 56,278 8.68 3 hrs 46 mins
43 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 480,847 55,944 8.60 3 hrs 48 mins
44 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 479,812 56,262 8.53 3 hrs 49 mins
45 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 326,255 49,452 6.60 4 hrs 38 mins
46 GeForce GTX 780
GK110 [GeForce GTX 780] 3977
Nvidia GK110 317,806 48,307 6.58 4 hrs 39 mins
47 P106-090
GP106 [P106-090]
Nvidia GP106 287,505 47,003 6.12 4 hrs 55 mins
48 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 244,259 44,569 5.48 4 hrs 23 mins
49 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 215,167 42,446 5.07 5 hrs 44 mins
50 GeForce GTX 690
GK104 [GeForce GTX 690] 3130
Nvidia GK104 195,628 41,850 4.67 5 hrs 8 mins
51 GeForce GTX 760
GK104 [GeForce GTX 760] 2258
Nvidia GK104 173,233 39,938 4.34 6 hrs 32 mins
52 GeForce GTX 660 Ti
GK104 [GeForce GTX 660 Ti] 2634
Nvidia GK104 134,182 30,076 4.46 5 hrs 23 mins
53 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 123,832 35,797 3.46 7 hrs 56 mins
54 GeForce GTX 660
GK106 [GeForce GTX 660]
Nvidia GK106 122,731 35,648 3.44 7 hrs 58 mins
55 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 120,218 20,871 5.76 4 hrs 10 mins
56 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 78,534 29,990 2.62 9 hrs 10 mins
57 GeForce GTX 680
GK104 [GeForce GTX 680] 3250
Nvidia GK104 57,919 26,124 2.22 11 hrs 50 mins
58 GeForce GT 730
GK208B [GeForce GT 730] 692.7
Nvidia GK208B 24,295 20,873 1.16 21 hrs 37 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 04 December 2022 18:13:27

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make