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, 31 January 2023 00:14:59
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, 31 January 2023 00:14:59
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|