PROJECT #18105 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: 19,729
Core: OPENMM_22
Status: Public
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Friday, 27 May 2022 17:25:50
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 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 2,874,634 | 125,071 | 22.98 | 1 hrs 3 mins |
2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 2,814,362 | 123,465 | 22.79 | 1 hrs 3 mins |
3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 2,726,340 | 120,517 | 22.62 | 1 hrs 4 mins |
4 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 2,501,428 | 118,709 | 21.07 | 1 hrs 8 mins |
5 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 2,380,576 | 117,623 | 20.24 | 1 hrs 11 mins |
6 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 2,343,537 | 117,417 | 19.96 | 1 hrs 12 mins |
7 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,266,501 | 148,319 | 15.28 | 2 hrs 34 mins |
8 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 2,229,904 | 114,779 | 19.43 | 1 hrs 14 mins |
9 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 2,124,437 | 113,339 | 18.74 | 1 hrs 17 mins |
10 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 1,938,548 | 109,566 | 17.69 | 1 hrs 21 mins |
11 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 1,906,373 | 109,137 | 17.47 | 1 hrs 22 mins |
12 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,719,676 | 105,385 | 16.32 | 1 hrs 28 mins |
13 | RTX A4000 GA104GL [RTX A4000] |
Nvidia | GA104GL | 1,702,311 | 105,491 | 16.14 | 1 hrs 29 mins |
14 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 1,659,832 | 104,671 | 15.86 | 2 hrs 31 mins |
15 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 1,600,545 | 103,444 | 15.47 | 2 hrs 33 mins |
16 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 1,572,123 | 102,486 | 15.34 | 2 hrs 34 mins |
17 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,467,799 | 100,231 | 14.64 | 2 hrs 38 mins |
18 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 1,446,690 | 99,916 | 14.48 | 2 hrs 39 mins |
19 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 1,400,450 | 98,844 | 14.17 | 2 hrs 42 mins |
20 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 1,397,687 | 98,641 | 14.17 | 2 hrs 42 mins |
21 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,393,256 | 98,659 | 14.12 | 2 hrs 42 mins |
22 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,378,005 | 96,485 | 14.28 | 2 hrs 41 mins |
23 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,341,052 | 97,785 | 13.71 | 2 hrs 45 mins |
24 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,339,400 | 96,674 | 13.85 | 2 hrs 44 mins |
25 | TITAN X GP102 [TITAN X] 6144 |
Nvidia | GP102 | 1,337,393 | 96,923 | 13.80 | 2 hrs 44 mins |
26 | GeForce RTX 3070 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,288,970 | 95,875 | 13.44 | 2 hrs 47 mins |
27 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,103,186 | 91,932 | 12.00 | 2 hrs 60 mins |
28 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,005,661 | 88,167 | 11.41 | 2 hrs 6 mins |
29 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 985,790 | 87,943 | 11.21 | 2 hrs 8 mins |
30 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 924,008 | 86,626 | 10.67 | 2 hrs 15 mins |
31 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 912,519 | 85,192 | 10.71 | 2 hrs 14 mins |
32 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 892,455 | 84,853 | 10.52 | 2 hrs 17 mins |
33 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 674,441 | 79,630 | 8.47 | 3 hrs 50 mins |
34 | GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile] |
Nvidia | TU116M | 656,346 | 64,571 | 10.16 | 2 hrs 22 mins |
35 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 649,621 | 76,587 | 8.48 | 3 hrs 50 mins |
36 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 631,797 | 75,483 | 8.37 | 3 hrs 52 mins |
37 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 624,335 | 75,060 | 8.32 | 3 hrs 53 mins |
38 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 489,652 | 67,054 | 7.30 | 3 hrs 17 mins |
39 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 430,479 | 66,493 | 6.47 | 4 hrs 42 mins |
40 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 407,430 | 62,247 | 6.55 | 4 hrs 40 mins |
41 | Quadro T2000 Mobile / Max-Q TU117GLM [Quadro T2000 Mobile / Max-Q] |
Nvidia | TU117GLM | 386,077 | 63,389 | 6.09 | 4 hrs 56 mins |
42 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 341,755 | 61,789 | 5.53 | 4 hrs 20 mins |
43 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 266,068 | 56,846 | 4.68 | 5 hrs 8 mins |
44 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 203,862 | 52,236 | 3.90 | 6 hrs 9 mins |
45 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 199,456 | 51,746 | 3.85 | 6 hrs 14 mins |
46 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 196,459 | 50,497 | 3.89 | 6 hrs 10 mins |
47 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 194,880 | 36,606 | 5.32 | 5 hrs 30 mins |
48 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 180,367 | 49,924 | 3.61 | 7 hrs 39 mins |
49 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 84,947 | 31,875 | 2.67 | 9 hrs 0 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Friday, 27 May 2022 17:25:50
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|
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