PROJECT #18118 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: 25,000
Core: OPENMM_22
Status: Public
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Saturday, 01 April 2023 12:14:47
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 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 2,458,544 | 131,452 | 18.70 | 1 hrs 17 mins |
2 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,257,270 | 126,944 | 17.78 | 1 hrs 21 mins |
3 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,100,130 | 124,789 | 16.83 | 1 hrs 26 mins |
4 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,926,328 | 118,530 | 16.25 | 1 hrs 29 mins |
5 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,791,179 | 118,544 | 15.11 | 2 hrs 35 mins |
6 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,776,607 | 116,639 | 15.23 | 2 hrs 35 mins |
7 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,746,875 | 112,077 | 15.59 | 2 hrs 32 mins |
8 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,525,998 | 116,499 | 13.10 | 2 hrs 50 mins |
9 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,385,604 | 108,778 | 12.74 | 2 hrs 53 mins |
10 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,338,199 | 107,273 | 12.47 | 2 hrs 55 mins |
11 | GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q] 4550 |
Nvidia | TU106M | 1,312,071 | 106,432 | 12.33 | 2 hrs 57 mins |
12 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,240,454 | 104,160 | 11.91 | 2 hrs 1 mins |
13 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,150,524 | 102,003 | 11.28 | 2 hrs 8 mins |
14 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,116,046 | 100,517 | 11.10 | 2 hrs 10 mins |
15 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 1,004,548 | 95,874 | 10.48 | 2 hrs 17 mins |
16 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 832,498 | 91,665 | 9.08 | 3 hrs 39 mins |
17 | Quadro P2200 GP106GL [Quadro P2200] |
Nvidia | GP106GL | 793,124 | 89,957 | 8.82 | 3 hrs 43 mins |
18 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 776,712 | 88,323 | 8.79 | 3 hrs 44 mins |
19 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 765,366 | 89,122 | 8.59 | 3 hrs 48 mins |
20 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 712,968 | 87,223 | 8.17 | 3 hrs 56 mins |
21 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 545,853 | 79,587 | 6.86 | 3 hrs 30 mins |
22 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 504,335 | 75,626 | 6.67 | 4 hrs 36 mins |
23 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 485,300 | 72,031 | 6.74 | 4 hrs 34 mins |
24 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 263,630 | 62,532 | 4.22 | 6 hrs 42 mins |
25 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 262,249 | 61,552 | 4.26 | 6 hrs 38 mins |
26 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 194,761 | 56,516 | 3.45 | 7 hrs 58 mins |
27 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 177,170 | 52,868 | 3.35 | 7 hrs 10 mins |
28 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 141,418 | 50,698 | 2.79 | 9 hrs 36 mins |
29 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 141,220 | 50,637 | 2.79 | 9 hrs 36 mins |
30 | GeForce GTX 690 GK104 [GeForce GTX 690] 3130 |
Nvidia | GK104 | 132,774 | 47,403 | 2.80 | 9 hrs 34 mins |
31 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 123,267 | 47,297 | 2.61 | 9 hrs 13 mins |
32 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 100,828 | 44,930 | 2.24 | 11 hrs 42 mins |
33 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 100,622 | 45,274 | 2.22 | 11 hrs 48 mins |
34 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 90,282 | 43,681 | 2.07 | 12 hrs 37 mins |
35 | GeForce 940MX GM108M [GeForce 940MX] |
Nvidia | GM108M | 55,125 | 37,004 | 1.49 | 16 hrs 7 mins |
36 | GeForce GT 730 GK208B [GeForce GT 730] 692.7 |
Nvidia | GK208B | 52,839 | 36,729 | 1.44 | 17 hrs 41 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Saturday, 01 April 2023 12:14:47
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|