PROJECT #16493 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: 54,231

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 22 May 2022 15:22:36

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 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,033,559 119,141 42.25 1 hrs 34 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 5,022,099 117,958 42.58 1 hrs 34 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,895,352 118,725 41.23 1 hrs 35 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,276,496 114,809 37.25 1 hrs 39 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,707,475 109,371 33.90 1 hrs 42 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,591,894 108,165 33.21 1 hrs 43 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,485,772 105,360 33.08 1 hrs 44 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,971,544 100,907 29.45 1 hrs 49 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,754,007 99,441 27.69 1 hrs 52 mins
10 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 2,627,122 97,465 26.95 1 hrs 53 mins
11 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,403,741 92,494 25.99 1 hrs 55 mins
12 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,261,536 92,875 24.35 1 hrs 59 mins
13 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,260,994 92,898 24.34 1 hrs 59 mins
14 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,128,910 84,859 25.09 1 hrs 57 mins
15 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,119,514 91,278 23.22 1 hrs 2 mins
16 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,097,131 89,807 23.35 1 hrs 2 mins
17 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,955,835 88,284 22.15 1 hrs 5 mins
18 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 1,883,579 87,203 21.60 1 hrs 7 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,793,693 85,871 20.89 1 hrs 9 mins
20 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 1,688,992 84,058 20.09 1 hrs 12 mins
21 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,601,640 83,418 19.20 1 hrs 15 mins
22 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 1,520,821 79,357 19.16 1 hrs 15 mins
23 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,370,494 77,349 17.72 1 hrs 21 mins
24 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,362,524 78,176 17.43 1 hrs 23 mins
25 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,273,225 76,512 16.64 1 hrs 27 mins
26 GeForce RTX 2080 Mobile
TU104M [GeForce RTX 2080 Mobile]
Nvidia TU104M 1,189,787 56,766 20.96 1 hrs 9 mins
27 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,162,798 74,534 15.60 2 hrs 32 mins
28 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,136,095 73,729 15.41 2 hrs 33 mins
29 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,027,243 69,784 14.72 2 hrs 38 mins
30 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 990,416 71,055 13.94 2 hrs 43 mins
31 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 743,848 49,827 14.93 2 hrs 36 mins
32 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 685,644 62,107 11.04 2 hrs 10 mins
33 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 619,577 60,229 10.29 2 hrs 20 mins
34 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 607,712 59,161 10.27 2 hrs 20 mins
35 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 591,314 58,647 10.08 2 hrs 23 mins
36 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 529,467 57,219 9.25 3 hrs 36 mins
37 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 450,122 53,696 8.38 3 hrs 52 mins
38 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 448,331 53,357 8.40 3 hrs 51 mins
39 P106-100
GP106 [P106-100]
Nvidia GP106 354,266 49,204 7.20 3 hrs 20 mins
40 GeForce GTX 980M
GM204 [GeForce GTX 980M] 3189
Nvidia GM204 327,016 48,932 6.68 4 hrs 35 mins
41 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 318,078 48,387 6.57 4 hrs 39 mins
42 P106-090
GP106 [P106-090]
Nvidia GP106 301,463 47,148 6.39 4 hrs 45 mins
43 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 229,181 42,903 5.34 4 hrs 30 mins
44 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 218,943 41,748 5.24 5 hrs 35 mins
45 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 207,421 42,127 4.92 5 hrs 52 mins
46 GeForce GTX 680
GK104 [GeForce GTX 680] 3250
Nvidia GK104 126,984 33,175 3.83 6 hrs 16 mins
47 GeForce GTX 660
GK106 [GeForce GTX 660]
Nvidia GK106 123,401 35,199 3.51 7 hrs 51 mins
48 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 115,434 34,264 3.37 7 hrs 7 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 22 May 2022 15:22:36

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