PROJECT #18104 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: 19,723

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 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 3,759,505 240,751 15.62 2 hrs 32 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 2,775,186 123,847 22.41 1 hrs 4 mins
3 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 2,655,653 118,961 22.32 1 hrs 5 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 2,515,825 117,906 21.34 1 hrs 7 mins
5 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 2,363,820 115,234 20.51 1 hrs 10 mins
6 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,183,518 114,591 19.05 1 hrs 16 mins
7 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,943,262 110,169 17.64 1 hrs 22 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 1,758,302 106,585 16.50 1 hrs 27 mins
9 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,492,259 101,092 14.76 2 hrs 38 mins
10 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 1,471,906 100,665 14.62 2 hrs 38 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 1,470,808 100,633 14.62 2 hrs 39 mins
12 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,468,023 101,584 14.45 2 hrs 40 mins
13 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,457,636 101,379 14.38 2 hrs 40 mins
14 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,452,126 100,111 14.51 2 hrs 39 mins
15 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,423,207 96,846 14.70 2 hrs 38 mins
16 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,400,746 98,895 14.16 2 hrs 42 mins
17 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,323,952 97,095 13.64 2 hrs 46 mins
18 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,189,766 93,639 12.71 2 hrs 53 mins
19 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,122,667 92,256 12.17 2 hrs 58 mins
20 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,041,562 89,198 11.68 2 hrs 3 mins
21 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 955,579 85,418 11.19 2 hrs 9 mins
22 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 890,821 84,545 10.54 2 hrs 17 mins
23 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 734,219 63,944 11.48 2 hrs 5 mins
24 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 663,043 77,629 8.54 3 hrs 49 mins
25 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 436,329 56,091 7.78 3 hrs 5 mins
26 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 434,503 67,242 6.46 4 hrs 43 mins
27 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 52,150 21,637 2.41 10 hrs 57 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