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 Sunday, 02 October 2022 12:16:39

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 1 hrs 39 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,490,213 125,549 35.76 1 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 1 hrs 41 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 3,865,632 120,696 32.03 1 hrs 45 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,281,614 113,977 28.79 1 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 1 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 1 hrs 54 mins
8 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,968,107 105,318 28.18 1 hrs 51 mins
9 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,721,623 106,065 25.66 1 hrs 56 mins
10 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,563,025 105,291 24.34 1 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 Sunday, 02 October 2022 12:16:39

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