PROJECT #18105 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

We are simulating publicly available protein and small molecule structures of the currently very hot cancer target KRas, see https://www.fiercepharma.com/pharma/amgen-s-lumakras-becomes-first-fda-approved-kras-inhibitor-for-lung-cancer-patients for recent developments. Folding@home has previously looked at this protein (in project 10490), and the following part of the description is copied from there:

This project is "studying a small protein called KRAS, which forms a key link in growth signaling and cancer. This gene is something like a molecular switch with a timer. When it is bound to a molecule called GDP, it is off, and does not signal that the cell should grow. However, other proteins can cause it to swap its GDP for a GTP, turning KRAS on. In the on state, it signals that the cell should grow and divide. Normally, after some time, KRAS, with the aid of some partners, will chemically convert its GTP to GDP and return to its inactive state.

In many cancers, this protein becomes mutated, and cannot return to its off state. The result? The cells continue to divide without limit. What’s worse, cancers with this protein mutated tend to have much poorer prognoses. As a result, scientists have been trying to target this protein for decades."

We are investigating the dynamic behavior of KRas with these publicly disclosed inhibitors so that we can apply this knowledge to our own drug design. At the same time, we are further testing the adaptive sampling methodology. All data is being made publicly available, and insights from methodology developments will be shared. 

This is a project run by Roivant Sciences (formerly Silicon Therapeutics) as was officially announced in this press release: https://foldingathome.org/2021/04/20/maximizing-the-impact-of-foldinghome-by-engaging-industry-collaborators/

PROJECT INFO

Manager(s): Rafal Wiewiora

Institution: Roivant Sciences (Silicon Therapeutics)

Project URL: roivant.com

PROJECT WORK UNIT SUMMARY

Atoms: 19,729

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Friday, 23 July 2021 12:13:38

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 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 3,787,164 241,081 15.71 2 hrs 32 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 2,866,168 122,133 23.47 1 hrs 1 mins
3 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 2,824,994 123,923 22.80 1 hrs 3 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 2,517,319 118,974 21.16 1 hrs 8 mins
5 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 2,398,368 118,300 20.27 1 hrs 11 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,341,211 116,445 20.11 1 hrs 12 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 2,331,068 116,781 19.96 1 hrs 12 mins
8 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,220,624 115,371 19.25 1 hrs 15 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 1,898,821 108,741 17.46 1 hrs 22 mins
10 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 1,875,401 108,298 17.32 1 hrs 23 mins
11 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,737,355 107,332 16.19 1 hrs 29 mins
12 RTX A4000
GA104GL [RTX A4000]
GA104GL 1,702,311 105,491 16.14 1 hrs 29 mins
13 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,691,545 105,113 16.09 1 hrs 29 mins
14 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,558,104 102,481 15.20 2 hrs 35 mins
15 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,541,179 101,890 15.13 2 hrs 35 mins
16 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,510,037 101,368 14.90 2 hrs 37 mins
17 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,455,997 100,136 14.54 2 hrs 39 mins
18 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 1,443,794 96,002 15.04 2 hrs 36 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,361,672 97,240 14.00 2 hrs 43 mins
20 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,341,052 97,785 13.71 2 hrs 45 mins
21 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,156,392 92,653 12.48 2 hrs 55 mins
22 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,103,186 91,932 12.00 2 hrs 60 mins
23 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 977,302 87,601 11.16 2 hrs 9 mins
24 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 894,983 84,808 10.55 2 hrs 16 mins
25 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 886,176 84,485 10.49 2 hrs 17 mins
26 GeForce GTX 1660 Mobile
TU116M [GeForce GTX 1660 Mobile]
Nvidia TU116M 656,346 64,571 10.16 2 hrs 22 mins
27 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 622,960 75,338 8.27 3 hrs 54 mins
28 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 512,784 69,631 7.36 3 hrs 16 mins
29 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 401,795 59,583 6.74 4 hrs 34 mins
30 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 353,796 60,593 5.84 4 hrs 7 mins
31 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 335,116 61,426 5.46 4 hrs 24 mins
32 P104-100
GP104 [P104-100]
Nvidia GP104 266,068 56,846 4.68 5 hrs 8 mins
33 P106-100
GP106 [P106-100]
Nvidia GP106 200,012 51,750 3.86 6 hrs 13 mins
34 GeForce GTX 1650
TU116 [GeForce GTX 1650] 2984
Nvidia TU116 194,880 36,606 5.32 5 hrs 30 mins
35 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 84,947 31,875 2.67 9 hrs 0 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 23 July 2021 12:13:38

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