PROJECT #18124 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 at https://console.cloud.google.com/storage/browser/stxfah-bucket, 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/ All data is being made publicly available as soon as it is received at https://console.cloud.google.com/storage/browser/stxfah-bucket.

PROJECT INFO

Manager(s): Rafal Wiewiora

Institution: Roivant Sciences (Silicon Therapeutics)

Project URL: roivant.com

PROJECT WORK UNIT SUMMARY

Atoms: 25,000

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 04 December 2022 18:13:20

Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,347,964 125,384 18.73 1 hrs 17 mins
2 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,130,135 121,830 17.48 1 hrs 22 mins
3 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,101,828 120,660 17.42 1 hrs 23 mins
4 GeForce RTX 2070 SUPER Mobile / Max-Q
TU104M [GeForce RTX 2070 SUPER Mobile / Max-Q]
Nvidia TU104M 2,013,844 118,700 16.97 1 hrs 25 mins
5 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,856,823 115,975 16.01 1 hrs 30 mins
6 Tesla P40
GP102GL [Tesla P40] 11760
Nvidia GP102GL 1,671,755 112,562 14.85 2 hrs 37 mins
7 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,636,448 111,079 14.73 2 hrs 38 mins
8 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,516,140 108,730 13.94 2 hrs 43 mins
9 GeForce RTX 2080 Mobile
TU104M [GeForce RTX 2080 Mobile]
Nvidia TU104M 1,502,206 105,902 14.18 2 hrs 42 mins
10 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,430,415 106,364 13.45 2 hrs 47 mins
11 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,224,837 101,199 12.10 2 hrs 59 mins
12 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,202,132 100,177 12.00 2 hrs 60 mins
13 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,148,265 98,342 11.68 2 hrs 3 mins
14 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,122,963 97,469 11.52 2 hrs 5 mins
15 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,080,275 87,581 12.33 2 hrs 57 mins
16 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 1,075,323 92,385 11.64 2 hrs 4 mins
17 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,052,164 94,479 11.14 2 hrs 9 mins
18 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,035,838 93,439 11.09 2 hrs 10 mins
19 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,008,130 93,779 10.75 2 hrs 14 mins
20 Quadro P4000
GP104GL [Quadro P4000]
Nvidia GP104GL 827,456 89,271 9.27 3 hrs 35 mins
21 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 813,974 88,093 9.24 3 hrs 36 mins
22 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 806,636 87,794 9.19 3 hrs 37 mins
23 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 679,665 82,224 8.27 3 hrs 54 mins
24 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 674,075 71,124 9.48 3 hrs 32 mins
25 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 671,915 83,212 8.07 3 hrs 58 mins
26 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 606,190 81,168 7.47 3 hrs 13 mins
27 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 563,884 78,419 7.19 3 hrs 20 mins
28 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 525,296 76,098 6.90 3 hrs 29 mins
29 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 499,463 73,958 6.75 4 hrs 33 mins
30 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 486,882 74,606 6.53 4 hrs 41 mins
31 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 482,616 74,057 6.52 4 hrs 41 mins
32 GeForce GTX 980M
GM204 [GeForce GTX 980M] 3189
Nvidia GM204 393,295 69,438 5.66 4 hrs 14 mins
33 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 345,010 66,664 5.18 5 hrs 38 mins
34 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 333,863 63,622 5.25 5 hrs 34 mins
35 P106-090
GP106 [P106-090]
Nvidia GP106 325,036 64,986 5.00 5 hrs 48 mins
36 T600
TU117GL [T600]
Intel TU117GL 322,798 64,417 5.01 5 hrs 47 mins
37 P104-100
GP104 [P104-100]
Nvidia GP104 294,386 63,257 4.65 5 hrs 9 mins
38 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 247,084 58,672 4.21 6 hrs 42 mins
39 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 221,209 57,251 3.86 6 hrs 13 mins
40 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 142,472 49,251 2.89 8 hrs 18 mins
41 GeForce GTX 690
GK104 [GeForce GTX 690] 3130
Nvidia GK104 141,921 49,647 2.86 8 hrs 24 mins
42 Quadro K2200
GM107GL [Quadro K2200]
Nvidia GM107GL 140,312 48,993 2.86 8 hrs 23 mins
43 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 138,129 48,864 2.83 8 hrs 29 mins
44 GeForce GTX 680
GK104 [GeForce GTX 680] 3250
Nvidia GK104 137,402 48,651 2.82 8 hrs 30 mins
45 GeForce GTX 1060 Mobile
GP106M [GeForce GTX 1060 Mobile]
Nvidia GP106M 137,106 48,925 2.80 9 hrs 34 mins
46 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 129,905 47,199 2.75 9 hrs 43 mins
47 GeForce GTX 1050 Mobile
GP107M [GeForce GTX 1050 Mobile]
Nvidia GP107M 126,363 48,142 2.62 9 hrs 9 mins
48 GeForce GTX 750
GM107 [GeForce GTX 750] 1111
Nvidia GM107 116,560 46,120 2.53 9 hrs 30 mins
49 GeForce GTX 660 Ti
GK104 [GeForce GTX 660 Ti] 2634
Nvidia GK104 108,441 45,072 2.41 10 hrs 59 mins
50 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 102,423 43,988 2.33 10 hrs 18 mins
51 GeForce GTX 760
GK104 [GeForce GTX 760] 2258
Nvidia GK104 99,615 43,772 2.28 11 hrs 33 mins
52 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 80,554 40,990 1.97 12 hrs 13 mins
53 GeForce GTX 660
GK106 [GeForce GTX 660]
Nvidia GK106 66,473 37,787 1.76 14 hrs 39 mins
54 GeForce 940MX
GM108M [GeForce 940MX]
Nvidia GM108M 46,190 33,413 1.38 17 hrs 22 mins
55 GeForce GTX 765M
GK106 [GeForce GTX 765M]
Nvidia GK106 33,925 30,831 1.10 22 hrs 49 mins
56 GeForce MX130
GM108M [GeForce MX130]
Nvidia GM108M 32,231 24,000 1.34 18 hrs 52 mins
57 GeForce GT 730
GK208B [GeForce GT 730] 692.7
Nvidia GK208B 21,315 25,366 0.84 29 hrs 34 mins
58 GeForce GT 710
GK208B [GeForce GT 710] 366
Nvidia GK208B 16,059 24,000 0.67 36 hrs 52 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 04 December 2022 18:13:20

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