RESEARCH: CANCER
FOLDING PROJECT #18721 PROFILE
PROJECT TEAM
Manager(s): Rafal WiewioraInstitution: Roivant Sciences (Silicon Therapeutics)
Project URL: View Project Website
WORK UNIT INFO
Atoms: 77,809Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project studies tumor necrosis factor (TNF), a protein that can both help and harm cancer. Researchers want to understand how TNF works by looking at its structure and how it interacts with other molecules. They're using computer simulations to explore different shapes of TNF and see how they affect its ability to fight or promote cancer.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Tumor necrosis factor α (TNFα) is a cytokine that belongs to a superfamily of trimeric proteins.
This protein has been shown to be important in regulating autoimmune diseases such as arthritis and Crohn’s disease through interactions with the TNF receptor.
In regard to cancer, TNF is a double-dealer.
On one hand, TNF could be an endogenous tumor promoter, because TNF stimulates cancer cells’ growth, proliferation, invasion and metastasis, and tumor angiogenesis.
On the other hand, TNF could be a cancer killer.
In it’s apo state TNFα has shown to be symmetrical, but small ligand inhibitors bind the TNFα disrupt this symmetry by forcing one of the monomers to be below the other two, which disrupts the binding interface to form the TNFα-receptor complex.
In this project, we want to determine the stability of the trimer and get a sense of the free energy landscape.
We also want to determine if the asymmetry found in the inhibited conformation requires the presence of an inhibitor or if the apo trimer can visit inhibited states in the absence of the ligand.
In particular we are interested in learning about the effect the volume of the binding pocket has on forming the asymmetrical TNFα complex.
The initial starting structures are 50 diverse seeds from HREMD simulations started from a crystal structure.
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
Tumor necrosis factor
A cytokine that regulates inflammation and immune responses.
Tumor necrosis factor (TNF) is a protein that plays a crucial role in the body's inflammatory response. It helps fight infections and diseases but can also contribute to chronic inflammation if overproduced. TNF is involved in autoimmune disorders like arthritis and Crohn's disease, as well as certain types of cancer.
Cytokine
A signaling molecule produced by cells of the immune system.
Cytokines are small proteins that act as messengers between cells in the immune system. They play a vital role in coordinating immune responses, such as inflammation, fighting infections, and regulating cell growth. Cytokines can be beneficial or harmful depending on their type and concentration.
TNF receptor
Receptor for tumor necrosis factor (TNF).
The TNF receptor is a protein found on the surface of cells that binds to TNF. This binding triggers a cascade of events within the cell, ultimately influencing its behavior. There are several types of TNF receptors, each playing a specific role in immune responses.
Autoimmune diseases
Diseases caused by the immune system attacking healthy tissues.
Autoimmune diseases occur when the body's immune system mistakenly attacks its own cells and tissues. This can lead to a wide range of symptoms depending on the affected organs. Examples include rheumatoid arthritis, lupus, and type 1 diabetes.
Cancer
Uncontrolled growth and spread of abnormal cells.
Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells. These cells can invade surrounding tissues and organs, leading to various health problems. Cancer is caused by a complex interplay of genetic and environmental factors.
Tumor angiogenesis
The formation of new blood vessels within a tumor.
Tumor angiogenesis is the process by which tumors develop their own blood supply. New blood vessels provide nutrients and oxygen to the growing tumor, enabling its further growth and spread.
HREMD
High-resolution Enhanced Molecular Dynamics simulations.
HREMD is a computational method used to simulate the movement and interactions of molecules in biological systems. It allows researchers to study the behavior of proteins, DNA, and other biomolecules at high resolution.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:27:25|
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 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 10,104,978 | 537,872 | 18.79 | 1 hrs 17 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 10,034,892 | 594,482 | 16.88 | 1 hrs 25 mins |
| 3 | GeForce RTX 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 9,682,632 | 574,461 | 16.86 | 1 hrs 25 mins |
| 4 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 5,588,532 | 489,113 | 11.43 | 2 hrs 6 mins |
| 5 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 5,260,164 | 481,740 | 10.92 | 2 hrs 12 mins |
| 6 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,240,047 | 478,111 | 10.96 | 2 hrs 11 mins |
| 7 | GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB] |
Nvidia | GA102 | 4,857,507 | 466,754 | 10.41 | 2 hrs 18 mins |
| 8 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 4,727,744 | 464,563 | 10.18 | 2 hrs 21 mins |
| 9 | Radeon RX 7900XT/XTX Navi 31 [Radeon RX 7900XT/XTX] |
AMD | Navi 31 | 4,615,260 | 459,154 | 10.05 | 2 hrs 23 mins |
| 10 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,224,220 | 450,624 | 9.37 | 2 hrs 34 mins |
| 11 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 4,165,151 | 447,743 | 9.30 | 2 hrs 35 mins |
| 12 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,003,967 | 440,771 | 9.08 | 2 hrs 39 mins |
| 13 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,813,707 | 431,683 | 8.83 | 2 hrs 43 mins |
| 14 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,395,310 | 417,116 | 8.14 | 2 hrs 57 mins |
| 15 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 3,050,868 | 399,416 | 7.64 | 3 hrs 9 mins |
| 16 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,909,261 | 438,676 | 6.63 | 3 hrs 37 mins |
| 17 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,762,628 | 385,885 | 7.16 | 3 hrs 21 mins |
| 18 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,696,668 | 387,340 | 6.96 | 3 hrs 27 mins |
| 19 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 2,299,635 | 371,394 | 6.19 | 3 hrs 53 mins |
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|
|||||||
| 20 | RTX A4000 GA104GL [RTX A4000] |
Nvidia | GA104GL | 2,224,164 | 362,944 | 6.13 | 3 hrs 55 mins |
| 21 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,216,017 | 361,849 | 6.12 | 3 hrs 55 mins |
| 22 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 2,027,114 | 349,511 | 5.80 | 4 hrs 8 mins |
| 23 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 1,947,801 | 346,358 | 5.62 | 4 hrs 16 mins |
| 24 | Radeon RX 6650XT Navi 23 [Radeon RX 6650XT] |
AMD | Navi 23 | 1,919,536 | 346,494 | 5.54 | 4 hrs 20 mins |
| 25 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,910,780 | 345,458 | 5.53 | 4 hrs 20 mins |
| 26 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 1,793,732 | 336,398 | 5.33 | 4 hrs 30 mins |
| 27 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,675,379 | 328,774 | 5.10 | 4 hrs 43 mins |
| 28 | Radeon VII Vega 20 [Radeon VII] |
AMD | Vega 20 | 1,672,863 | 333,180 | 5.02 | 4 hrs 47 mins |
| 29 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 1,470,361 | 257,814 | 5.70 | 4 hrs 12 mins |
| 30 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,453,217 | 303,012 | 4.80 | 5 hrs 0 mins |
| 31 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,452,871 | 317,365 | 4.58 | 5 hrs 15 mins |
| 32 | GeForce RTX 3060 GA104 [GeForce RTX 3060] |
Nvidia | GA104 | 1,367,046 | 322,784 | 4.24 | 5 hrs 40 mins |
| 33 | Radeon RX 6600/6600 XT/6600M Navi 23 XT-XL [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 XT-XL | 1,214,622 | 293,866 | 4.13 | 5 hrs 48 mins |
| 34 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 1,196,625 | 295,611 | 4.05 | 5 hrs 56 mins |
| 35 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,184,628 | 306,138 | 3.87 | 6 hrs 12 mins |
| 36 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,038,373 | 281,707 | 3.69 | 6 hrs 31 mins |
| 37 | Radeon Pro W5700 Navi 10 [Radeon Pro W5700] |
AMD | Navi 10 | 1,007,212 | 289,534 | 3.48 | 6 hrs 54 mins |
| 38 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,006,675 | 279,522 | 3.60 | 6 hrs 40 mins |
| 39 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 936,592 | 260,206 | 3.60 | 6 hrs 40 mins |
|
|
|||||||
| 40 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 925,651 | 284,080 | 3.26 | 7 hrs 22 mins |
| 41 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 917,884 | 274,353 | 3.35 | 7 hrs 10 mins |
| 42 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 877,616 | 277,545 | 3.16 | 7 hrs 35 mins |
| 43 | GeForce RTX 3050 Ti Mobile GA107M [GeForce RTX 3050 Ti Mobile] |
Nvidia | GA107M | 835,786 | 261,668 | 3.19 | 7 hrs 31 mins |
| 44 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 807,034 | 259,245 | 3.11 | 7 hrs 43 mins |
| 45 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 759,038 | 252,962 | 3.00 | 7 hrs 60 mins |
| 46 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 709,408 | 250,450 | 2.83 | 8 hrs 28 mins |
| 47 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 622,610 | 232,894 | 2.67 | 8 hrs 59 mins |
| 48 | R9 Fury X/NANO Fiji XT [R9 Fury X/NANO] |
AMD | Fiji XT | 521,045 | 230,708 | 2.26 | 10 hrs 38 mins |
| 49 | RX 5500/5500M/Pro 5500M Navi 14 [RX 5500/5500M/Pro 5500M] |
AMD | Navi 14 | 517,032 | 220,901 | 2.34 | 10 hrs 15 mins |
| 50 | GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile] |
Nvidia | GP106M | 455,503 | 214,444 | 2.12 | 11 hrs 18 mins |
| 51 | Quadro P2200 GP106GL [Quadro P2200] |
Nvidia | GP106GL | 369,404 | 220,445 | 1.68 | 14 hrs 19 mins |
| 52 | RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590] |
AMD | Ellesmere XT | 342,183 | 202,155 | 1.69 | 14 hrs 11 mins |
| 53 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 325,349 | 191,653 | 1.70 | 14 hrs 8 mins |
| 54 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 227,152 | 166,647 | 1.36 | 17 hrs 36 mins |
| 55 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 199,187 | 162,552 | 1.23 | 19 hrs 35 mins |
| 56 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 189,394 | 159,629 | 1.19 | 20 hrs 14 mins |
| 57 | Tesla K40m GK110 [Tesla K40m] 5046 |
Nvidia | GK110 | 186,841 | 180,939 | 1.03 | 23 hrs 15 mins |
| 58 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 147,425 | 161,215 | 0.91 | 26 hrs 15 mins |
| 59 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 104,465 | 131,730 | 0.79 | 30 hrs 16 mins |
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|||||||
| 60 | Radeon RX 460/560D Baffin [Radeon RX 460/560D] |
AMD | Baffin | 95,128 | 132,017 | 0.72 | 33 hrs 18 mins |
| 61 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 84,228 | 141,749 | 0.59 | 40 hrs 23 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:27:25|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|