PROJECT #18103 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: 19,724
Core: OPENMM_22
Status: Public
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Wednesday, 29 March 2023 06:15:36
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 | 3,734,565 | 240,593 | 15.52 | 2 hrs 33 mins |
2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 2,827,651 | 124,005 | 22.80 | 1 hrs 3 mins |
3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 2,804,721 | 122,139 | 22.96 | 1 hrs 3 mins |
4 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 2,307,827 | 116,368 | 19.83 | 1 hrs 13 mins |
5 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 2,298,864 | 116,653 | 19.71 | 1 hrs 13 mins |
6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 2,178,958 | 113,555 | 19.19 | 1 hrs 15 mins |
7 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 2,142,283 | 113,686 | 18.84 | 1 hrs 16 mins |
8 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 2,034,409 | 110,973 | 18.33 | 1 hrs 19 mins |
9 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 1,901,808 | 108,934 | 17.46 | 1 hrs 22 mins |
10 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 1,898,120 | 109,334 | 17.36 | 1 hrs 23 mins |
11 | RTX A4000 GA104GL [RTX A4000] |
Nvidia | GA104GL | 1,821,669 | 108,038 | 16.86 | 1 hrs 25 mins |
12 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,771,013 | 106,361 | 16.65 | 1 hrs 26 mins |
13 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 1,683,634 | 105,341 | 15.98 | 2 hrs 30 mins |
14 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 1,547,524 | 102,085 | 15.16 | 2 hrs 35 mins |
15 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 1,515,781 | 101,163 | 14.98 | 2 hrs 36 mins |
16 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 1,503,186 | 101,249 | 14.85 | 2 hrs 37 mins |
17 | Tesla P40 GP102GL [Tesla P40] 11760 |
Nvidia | GP102GL | 1,471,374 | 99,948 | 14.72 | 2 hrs 38 mins |
18 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 1,456,411 | 100,139 | 14.54 | 2 hrs 39 mins |
19 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,424,264 | 99,448 | 14.32 | 2 hrs 41 mins |
20 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,397,408 | 98,812 | 14.14 | 2 hrs 42 mins |
21 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,357,379 | 96,746 | 14.03 | 2 hrs 43 mins |
22 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 1,300,974 | 96,358 | 13.50 | 2 hrs 47 mins |
23 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,272,058 | 95,699 | 13.29 | 2 hrs 48 mins |
24 | GeForce RTX 3070 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,094,284 | 88,767 | 12.33 | 2 hrs 57 mins |
25 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 1,052,537 | 90,148 | 11.68 | 2 hrs 3 mins |
26 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,051,448 | 89,816 | 11.71 | 2 hrs 3 mins |
27 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,014,937 | 89,072 | 11.39 | 2 hrs 6 mins |
28 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 871,864 | 68,742 | 12.68 | 2 hrs 54 mins |
29 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 778,234 | 78,503 | 9.91 | 2 hrs 25 mins |
30 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 587,018 | 74,055 | 7.93 | 3 hrs 2 mins |
31 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 527,370 | 70,584 | 7.47 | 3 hrs 13 mins |
32 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 518,777 | 71,509 | 7.25 | 3 hrs 18 mins |
33 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 472,877 | 68,595 | 6.89 | 3 hrs 29 mins |
34 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 442,191 | 67,153 | 6.58 | 4 hrs 39 mins |
35 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 363,460 | 63,435 | 5.73 | 4 hrs 11 mins |
36 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 272,010 | 56,698 | 4.80 | 5 hrs 0 mins |
37 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 254,454 | 56,106 | 4.54 | 5 hrs 18 mins |
38 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 231,179 | 54,510 | 4.24 | 6 hrs 40 mins |
39 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 199,348 | 51,700 | 3.86 | 6 hrs 13 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Wednesday, 29 March 2023 06:15:36
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|