PROJECT #18042 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: 190,000

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
GA102 [GeForce RTX 3090]
Nvidia GA102 6,718,801 1,198,369 5.61 4 hrs 17 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 6,222,355 1,185,479 5.25 5 hrs 34 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 5,058,150 1,086,883 4.65 5 hrs 9 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,850,325 1,106,520 4.38 5 hrs 29 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,466,929 1,063,113 4.20 6 hrs 43 mins
6 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 3,939,746 1,041,623 3.78 6 hrs 21 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,786,763 1,003,063 3.78 6 hrs 21 mins
8 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 3,726,860 1,000,478 3.73 6 hrs 27 mins
9 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,193,385 924,348 3.45 7 hrs 57 mins
10 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,751,742 899,313 3.06 8 hrs 51 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,674,229 888,560 3.01 8 hrs 58 mins
12 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 2,532,254 875,546 2.89 8 hrs 18 mins
13 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,496,498 858,118 2.91 8 hrs 15 mins
14 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 2,034,220 817,869 2.49 10 hrs 39 mins
15 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,948,716 844,389 2.31 10 hrs 24 mins
16 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 1,854,928 812,739 2.28 11 hrs 31 mins
17 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,705,321 825,273 2.07 12 hrs 37 mins
18 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,512,714 736,195 2.05 12 hrs 41 mins
19 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,477,932 734,963 2.01 12 hrs 56 mins
20 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,297,507 699,461 1.86 13 hrs 56 mins
21 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,236,287 688,254 1.80 13 hrs 22 mins
22 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,045,088 681,397 1.53 16 hrs 39 mins
23 Radeon RX 5600 OEM/5600 XT/5700/5700 XT
Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]
AMD Navi 10 1,037,394 644,683 1.61 15 hrs 55 mins
24 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 909,760 619,163 1.47 16 hrs 20 mins
25 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 874,148 649,825 1.35 18 hrs 50 mins
26 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 758,163 629,389 1.20 20 hrs 55 mins
27 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 671,254 542,121 1.24 19 hrs 23 mins
28 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 425,725 481,658 0.88 27 hrs 9 mins
29 Radeon RX 5500/5500M / Pro 5500M
Navi 14 [Radeon RX 5500/5500M / Pro 5500M]
AMD Navi 14 420,518 479,265 0.88 27 hrs 21 mins
30 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 347,669 461,224 0.75 32 hrs 50 mins
31 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 244,062 420,000 0.58 41 hrs 18 mins
32 Radeon Vega Series / Radeon Vega Mobile Series
Raven Ridge [Radeon Vega Series / Radeon Vega Mobile Series]
AMD Raven Ridge 95,549 420,000 0.23 105 hrs 30 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