RESEARCH: CANCER
FOLDING PROJECT #18124 PROFILE
PROJECT TEAM
Manager(s): Rafal WiewioraInstitution: Roivant Sciences (Silicon Therapeutics)
Project URL: View Project Website
WORK UNIT INFO
Atoms: 25,000Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Scientists are studying KRAS, a protein that can cause cancer when it's malfunctioning. This project uses computer simulations to understand how drugs work against mutated KRAS. Researchers hope this will lead to better cancer treatments and all data is available publicly.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
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.
RELATED TERMS GLOSSARY AI BETA
KRas
A protein that plays a role in cell growth and division.
KRas is a protein that acts like a switch, controlling whether cells grow and divide. When it's 'on', cells multiply rapidly. In many cancers, KRas becomes stuck in the 'on' position, leading to uncontrolled cell growth.
GDP
Guanosine Diphosphate
GDP is a molecule that binds to KRas protein, turning it 'off' and stopping cell growth. When GDP is bound to KRas, the protein can't signal for cell division.
GTP
Guanosine Triphosphate
GTP is a molecule that binds to KRas protein, turning it 'on' and allowing cell growth. When GTP is bound to KRas, the protein signals for cell division.
Inhibitor
A substance that blocks or reduces the activity of a particular molecule.
Inhibitors are molecules designed to stop KRas from functioning properly. They are being developed as potential cancer drugs because they can prevent uncontrolled cell growth.
Protein
A large biological molecule made up of amino acids.
Proteins are the workhorses of cells. They carry out a vast array of functions, including building and repairing tissues, catalyzing chemical reactions, and transporting molecules.
Cancer
A disease characterized by uncontrolled cell growth.
Cancer is a group of diseases where cells divide and grow uncontrollably. This can lead to the formation of tumors that invade surrounding tissues.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:31:52|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,347,964 | 125,384 | 18.73 | 1 hrs 17 mins |
| 2 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,130,135 | 121,830 | 17.48 | 1 hrs 22 mins |
| 3 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,101,828 | 120,660 | 17.42 | 1 hrs 23 mins |
| 4 | GeForce RTX 2070 SUPER Mobile / Max-Q TU104M [GeForce RTX 2070 SUPER Mobile / Max-Q] |
Nvidia | TU104M | 2,013,844 | 118,700 | 16.97 | 1 hrs 25 mins |
| 5 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,856,823 | 115,975 | 16.01 | 1 hrs 30 mins |
| 6 | Tesla P40 GP102GL [Tesla P40] 11760 |
Nvidia | GP102GL | 1,671,755 | 112,562 | 14.85 | 1 hrs 37 mins |
| 7 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,636,448 | 111,079 | 14.73 | 1 hrs 38 mins |
| 8 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,516,140 | 108,730 | 13.94 | 1 hrs 43 mins |
| 9 | GeForce RTX 2080 Mobile TU104M [GeForce RTX 2080 Mobile] |
Nvidia | TU104M | 1,502,206 | 105,902 | 14.18 | 1 hrs 42 mins |
| 10 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,430,415 | 106,364 | 13.45 | 1 hrs 47 mins |
| 11 | GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q] |
Nvidia | TU106M | 1,224,837 | 101,199 | 12.10 | 1 hrs 59 mins |
| 12 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,202,132 | 100,177 | 12.00 | 1 hrs 60 mins |
| 13 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,148,265 | 98,342 | 11.68 | 2 hrs 3 mins |
| 14 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,122,963 | 97,469 | 11.52 | 2 hrs 5 mins |
| 15 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,080,275 | 87,581 | 12.33 | 1 hrs 57 mins |
| 16 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,075,323 | 92,385 | 11.64 | 2 hrs 4 mins |
| 17 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,052,164 | 94,479 | 11.14 | 2 hrs 9 mins |
| 18 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,035,838 | 93,439 | 11.09 | 2 hrs 10 mins |
| 19 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,008,130 | 93,779 | 10.75 | 2 hrs 14 mins |
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|
|||||||
| 20 | Quadro P4000 GP104GL [Quadro P4000] |
Nvidia | GP104GL | 827,456 | 89,271 | 9.27 | 2 hrs 35 mins |
| 21 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 813,974 | 88,093 | 9.24 | 2 hrs 36 mins |
| 22 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 806,636 | 87,794 | 9.19 | 2 hrs 37 mins |
| 23 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 679,665 | 82,224 | 8.27 | 2 hrs 54 mins |
| 24 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 674,075 | 71,124 | 9.48 | 2 hrs 32 mins |
| 25 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 671,915 | 83,212 | 8.07 | 2 hrs 58 mins |
| 26 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 606,190 | 81,168 | 7.47 | 3 hrs 13 mins |
| 27 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 563,884 | 78,419 | 7.19 | 3 hrs 20 mins |
| 28 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 525,296 | 76,098 | 6.90 | 3 hrs 29 mins |
| 29 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 499,463 | 73,958 | 6.75 | 3 hrs 33 mins |
| 30 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 486,882 | 74,606 | 6.53 | 3 hrs 41 mins |
| 31 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 482,616 | 74,057 | 6.52 | 3 hrs 41 mins |
| 32 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 393,295 | 69,438 | 5.66 | 4 hrs 14 mins |
| 33 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 345,010 | 66,664 | 5.18 | 4 hrs 38 mins |
| 34 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 333,863 | 63,622 | 5.25 | 4 hrs 34 mins |
| 35 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 325,036 | 64,986 | 5.00 | 4 hrs 48 mins |
| 36 | T600 TU117GL [T600] |
Nvidia | TU117GL | 322,798 | 64,417 | 5.01 | 4 hrs 47 mins |
| 37 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 294,386 | 63,257 | 4.65 | 5 hrs 9 mins |
| 38 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 247,084 | 58,672 | 4.21 | 5 hrs 42 mins |
| 39 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 221,209 | 57,251 | 3.86 | 6 hrs 13 mins |
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|
|||||||
| 40 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 142,472 | 49,251 | 2.89 | 8 hrs 18 mins |
| 41 | GeForce GTX 690 GK104 [GeForce GTX 690] 3130 |
Nvidia | GK104 | 141,921 | 49,647 | 2.86 | 8 hrs 24 mins |
| 42 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 140,312 | 48,993 | 2.86 | 8 hrs 23 mins |
| 43 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 138,129 | 48,864 | 2.83 | 8 hrs 29 mins |
| 44 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 137,402 | 48,651 | 2.82 | 8 hrs 30 mins |
| 45 | GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile] |
Nvidia | GP106M | 137,106 | 48,925 | 2.80 | 8 hrs 34 mins |
| 46 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 129,905 | 47,199 | 2.75 | 8 hrs 43 mins |
| 47 | GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile] |
Nvidia | GP107M | 126,363 | 48,142 | 2.62 | 9 hrs 9 mins |
| 48 | GeForce GTX 750 GM107 [GeForce GTX 750] 1111 |
Nvidia | GM107 | 116,560 | 46,120 | 2.53 | 9 hrs 30 mins |
| 49 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 108,441 | 45,072 | 2.41 | 9 hrs 59 mins |
| 50 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 102,423 | 43,988 | 2.33 | 10 hrs 18 mins |
| 51 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 99,615 | 43,772 | 2.28 | 10 hrs 33 mins |
| 52 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 80,554 | 40,990 | 1.97 | 12 hrs 13 mins |
| 53 | GeForce GTX 660 GK106 [GeForce GTX 660] |
Nvidia | GK106 | 66,473 | 37,787 | 1.76 | 13 hrs 39 mins |
| 54 | GeForce 940MX GM108M [GeForce 940MX] |
Nvidia | GM108M | 46,190 | 33,413 | 1.38 | 17 hrs 22 mins |
| 55 | GeForce GTX 765M GK106 [GeForce GTX 765M] |
Nvidia | GK106 | 33,925 | 30,831 | 1.10 | 21 hrs 49 mins |
| 56 | GeForce MX130 GM108M [GeForce MX130] |
Nvidia | GM108M | 32,231 | 24,000 | 1.34 | 17 hrs 52 mins |
| 57 | GeForce GT 730 GK208B [GeForce GT 730] 692.7 |
Nvidia | GK208B | 21,315 | 25,366 | 0.84 | 28 hrs 34 mins |
| 58 | GeForce GT 710 GK208B [GeForce GT 710] 366 |
Nvidia | GK208B | 16,059 | 24,000 | 0.67 | 35 hrs 52 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:31:52|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|