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 Tuesday, 26 October 2021 06:56:06

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 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 2,874,634 125,071 22.98 1 hrs 3 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 2,814,362 123,465 22.79 1 hrs 3 mins
3 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 2,726,340 120,517 22.62 1 hrs 4 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 2,501,428 118,709 21.07 1 hrs 8 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 2,380,576 117,623 20.24 1 hrs 11 mins
6 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 2,343,537 117,417 19.96 1 hrs 12 mins
7 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,266,501 148,319 15.28 2 hrs 34 mins
8 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,229,904 114,779 19.43 1 hrs 14 mins
9 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,124,437 113,339 18.74 1 hrs 17 mins
10 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 1,938,548 109,566 17.69 1 hrs 21 mins
11 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 1,906,373 109,137 17.47 1 hrs 22 mins
12 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,719,676 105,385 16.32 1 hrs 28 mins
13 RTX A4000
GA104GL [RTX A4000]
Nvidia GA104GL 1,702,311 105,491 16.14 1 hrs 29 mins
14 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,659,832 104,671 15.86 2 hrs 31 mins
15 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,600,545 103,444 15.47 2 hrs 33 mins
16 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,572,123 102,486 15.34 2 hrs 34 mins
17 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,467,799 100,231 14.64 2 hrs 38 mins
18 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,446,690 99,916 14.48 2 hrs 39 mins
19 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 1,400,450 98,844 14.17 2 hrs 42 mins
20 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 1,397,687 98,641 14.17 2 hrs 42 mins
21 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,393,256 98,659 14.12 2 hrs 42 mins
22 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 1,378,005 96,485 14.28 2 hrs 41 mins
23 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
24 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,339,400 96,674 13.85 2 hrs 44 mins
25 TITAN X
GP102 [TITAN X] 6144
Nvidia GP102 1,337,393 96,923 13.80 2 hrs 44 mins
26 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,288,970 95,875 13.44 2 hrs 47 mins
27 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,103,186 91,932 12.00 2 hrs 60 mins
28 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,005,661 88,167 11.41 2 hrs 6 mins
29 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 985,790 87,943 11.21 2 hrs 8 mins
30 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 924,008 86,626 10.67 2 hrs 15 mins
31 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 912,519 85,192 10.71 2 hrs 14 mins
32 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 892,455 84,853 10.52 2 hrs 17 mins
33 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 674,441 79,630 8.47 3 hrs 50 mins
34 GeForce GTX 1660 Mobile
TU116M [GeForce GTX 1660 Mobile]
Nvidia TU116M 656,346 64,571 10.16 2 hrs 22 mins
35 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 649,621 76,587 8.48 3 hrs 50 mins
36 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 631,797 75,483 8.37 3 hrs 52 mins
37 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 624,335 75,060 8.32 3 hrs 53 mins
38 GeForce GTX 1650
TU117 [GeForce GTX 1650] 3091
Nvidia TU117 489,652 67,054 7.30 3 hrs 17 mins
39 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 430,479 66,493 6.47 4 hrs 42 mins
40 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 407,430 62,247 6.55 4 hrs 40 mins
41 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 386,077 63,389 6.09 4 hrs 56 mins
42 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 341,755 61,789 5.53 4 hrs 20 mins
43 P104-100
GP104 [P104-100]
Nvidia GP104 266,068 56,846 4.68 5 hrs 8 mins
44 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 203,862 52,236 3.90 6 hrs 9 mins
45 P106-100
GP106 [P106-100]
Nvidia GP106 199,456 51,746 3.85 6 hrs 14 mins
46 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 196,459 50,497 3.89 6 hrs 10 mins
47 GeForce GTX 1650
TU116 [GeForce GTX 1650] 2984
Nvidia TU116 194,880 36,606 5.32 5 hrs 30 mins
48 GeForce GTX 1050 Ti Mobile
GP107M [GeForce GTX 1050 Ti Mobile]
Nvidia GP107M 180,367 49,924 3.61 7 hrs 39 mins
49 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 Tuesday, 26 October 2021 06:56:06

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