PROJECT #18127 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: 49,000

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Wednesday, 30 November 2022 06:13:32

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 4,769,212 263,532 18.10 1 hrs 20 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,766,486 257,353 18.52 1 hrs 18 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,321,834 251,238 17.20 1 hrs 24 mins
4 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 4,026,350 244,597 16.46 1 hrs 27 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,844,435 243,946 15.76 2 hrs 31 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,471,256 236,953 14.65 2 hrs 38 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,346,583 233,948 14.30 2 hrs 41 mins
8 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 3,061,483 227,983 13.43 2 hrs 47 mins
9 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,013,943 226,499 13.31 2 hrs 48 mins
10 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,873,072 223,359 12.86 2 hrs 52 mins
11 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,710,411 216,913 12.50 2 hrs 55 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,448,867 212,132 11.54 2 hrs 5 mins
13 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 2,209,575 204,982 10.78 2 hrs 14 mins
14 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,105,368 200,688 10.49 2 hrs 17 mins
15 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,074,048 199,541 10.39 2 hrs 19 mins
16 Tesla P100 16GB
GP100GL [Tesla P100 16GB] 9340
Nvidia GP100GL 1,973,661 197,288 10.00 2 hrs 24 mins
17 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,692,469 186,770 9.06 3 hrs 39 mins
18 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 1,684,496 186,008 9.06 3 hrs 39 mins
19 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 1,295,781 170,895 7.58 3 hrs 10 mins
20 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,200,522 165,097 7.27 3 hrs 18 mins
21 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,167,146 165,901 7.04 3 hrs 25 mins
22 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,125,169 155,407 7.24 3 hrs 19 mins
23 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,057,014 160,172 6.60 4 hrs 38 mins
24 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 985,100 153,866 6.40 4 hrs 45 mins
25 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 739,522 142,505 5.19 5 hrs 37 mins
26 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 696,307 139,159 5.00 5 hrs 48 mins
27 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 633,959 134,875 4.70 5 hrs 6 mins
28 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 631,881 135,076 4.68 5 hrs 8 mins
29 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 593,078 133,816 4.43 5 hrs 25 mins
30 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 568,078 129,590 4.38 5 hrs 28 mins
31 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 487,337 80,889 6.02 4 hrs 59 mins
32 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 334,130 108,962 3.07 8 hrs 50 mins
33 P106-090
GP106 [P106-090]
Nvidia GP106 333,690 108,899 3.06 8 hrs 50 mins
34 Quadro M4000
GM204GL [Quadro M4000]
Nvidia GM204GL 288,329 106,032 2.72 9 hrs 50 mins
35 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 230,386 105,670 2.18 11 hrs 0 mins
36 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 226,999 95,164 2.39 10 hrs 4 mins
37 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 120,911 78,796 1.53 16 hrs 38 mins
38 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 79,512 67,604 1.18 20 hrs 24 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Wednesday, 30 November 2022 06:13:32

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