PROJECT #18036 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: 70,000

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 22 May 2022 15:22:31

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 Ti
GA102 [GeForce RTX 3090 Ti]
Nvidia GA102 5,623,552 433,521 12.97 2 hrs 51 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 5,172,727 416,662 12.41 2 hrs 56 mins
3 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,913,697 410,296 11.98 2 hrs 0 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,857,206 411,241 11.81 2 hrs 2 mins
5 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,297,649 387,943 11.08 2 hrs 10 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,757,094 376,829 9.97 2 hrs 24 mins
7 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,592,781 371,064 9.68 2 hrs 29 mins
8 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 3,267,554 357,029 9.15 3 hrs 37 mins
9 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 3,155,090 353,389 8.93 3 hrs 41 mins
10 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,125,391 350,075 8.93 3 hrs 41 mins
11 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 3,055,715 352,116 8.68 3 hrs 46 mins
12 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,935,361 345,310 8.50 3 hrs 49 mins
13 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,303,362 320,426 7.19 3 hrs 20 mins
14 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,211,835 316,486 6.99 3 hrs 26 mins
15 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,164,249 314,208 6.89 3 hrs 29 mins
16 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,128,167 301,436 7.06 3 hrs 24 mins
17 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,995,662 307,317 6.49 4 hrs 42 mins
18 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 1,974,067 303,878 6.50 4 hrs 42 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,747,060 294,243 5.94 4 hrs 3 mins
20 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,665,258 284,148 5.86 4 hrs 6 mins
21 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,533,237 280,383 5.47 4 hrs 23 mins
22 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 1,505,529 277,887 5.42 4 hrs 26 mins
23 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 1,439,261 273,193 5.27 5 hrs 33 mins
24 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,310,557 263,008 4.98 5 hrs 49 mins
25 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,248,819 261,255 4.78 5 hrs 1 mins
26 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,082,538 250,679 4.32 6 hrs 33 mins
27 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,033,075 243,263 4.25 6 hrs 39 mins
28 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 957,839 244,254 3.92 6 hrs 7 mins
29 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 870,085 235,182 3.70 6 hrs 29 mins
30 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 812,403 220,318 3.69 7 hrs 31 mins
31 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 744,859 208,744 3.57 7 hrs 44 mins
32 Geforce RTX 3050
GA106 [Geforce RTX 3050]
Nvidia GA106 715,896 212,595 3.37 7 hrs 8 mins
33 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 689,102 213,163 3.23 7 hrs 25 mins
34 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 580,139 206,919 2.80 9 hrs 34 mins
35 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 505,293 200,151 2.52 10 hrs 30 mins
36 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 476,126 184,836 2.58 9 hrs 19 mins
37 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 355,446 172,158 2.06 12 hrs 37 mins
38 P106-090
GP106 [P106-090]
Nvidia GP106 345,185 170,137 2.03 12 hrs 50 mins
39 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 311,464 163,811 1.90 13 hrs 37 mins
40 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 254,690 156,103 1.63 15 hrs 43 mins
41 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 221,420 146,335 1.51 16 hrs 52 mins
42 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 180,401 136,814 1.32 18 hrs 12 mins
43 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 84,406 101,841 0.83 29 hrs 57 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 22 May 2022 15:22:31

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