RESEARCH: CANCER
FOLDING PROJECT #18019 PROFILE
PROJECT TEAM
Manager(s): Rafal WiewioraInstitution: Roivant Sciences (Silicon Therapeutics)
Project URL: View Project Website
WORK UNIT INFO
Atoms: 498,112Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Scientists are using computer simulations to study how a protein called NEDD8 activates another protein called VHL. VHL is part of a system that tags other proteins for destruction in cells. This research could help us understand how diseases develop and create new drugs.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
In this system we are simulating an E3 ligase (specifically, culling-ring-VHL) in presence of another protein called NEDD8.
Culling ring is normally in inactive form, but NEDD8 can activate it.
Using these simulations we are trying to understand how protein-protein interactions help induce conformational changes that enable activation of cullin ring.
Understanding this process help us better understand how cullin-ring based E3 ligases transfer ubiquitin to proteins which results in their subsequent degradation by the proteasome system. 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
E3 ligase
Enzyme that attaches ubiquitin to proteins for degradation.
E3 ligases are crucial enzymes involved in marking proteins for destruction within cells. They work by attaching a small protein called ubiquitin to target proteins, essentially acting like a signal flag that tells the cell's recycling machinery (the proteasome) to break down the tagged protein. This process is essential for regulating various cellular functions, including cell cycle control, DNA repair, and immune responses.
cullin ring
A protein complex that forms the core of an E3 ligase.
Cullin rings are multi-subunit complexes that act as scaffolds for assembling E3 ligases. They provide a platform for interacting with various proteins involved in ubiquitination, including substrate recognition factors and the RING domain protein. The structure of the cullin ring is flexible and can undergo conformational changes upon activation by NEDD8, allowing it to bind to specific substrates and facilitate their ubiquitination.
NEDD8
A small protein that activates cullin rings.
NEDD8 (Neural precursor cell expressed, developmentally down-regulated 8) is a ubiquitin-like protein that plays a key role in regulating protein function. It works by attaching itself to specific target proteins, known as NEDDylation, which can alter their activity, localization, or interactions with other molecules. In the context of E3 ligases, NEDD8 modification of cullin rings is essential for activating these complexes and promoting ubiquitination.
ubiquitin
A small protein that tags proteins for degradation.
Ubiquitin is a highly conserved 76-amino acid protein that plays a central role in cellular processes such as protein degradation, signal transduction, and DNA repair. It functions by attaching to target proteins through an enzymatic cascade involving ubiquitin-activating (E1), conjugating (E2), and ligase (E3) enzymes. The attachment of ubiquitin chains to proteins serves as a signal for their recognition and degradation by the proteasome, a cellular machine responsible for breaking down unwanted or damaged proteins.
proteasome
A cellular complex that degrades proteins.
The proteasome is a large, barrel-shaped protein complex found in eukaryotic cells. It plays a crucial role in degrading unwanted or damaged proteins by breaking them down into smaller peptides. The process of protein degradation by the proteasome is tightly regulated and involves multiple steps, including ubiquitination (the attachment of ubiquitin tags) and translocation of the target protein into the proteolytic chamber of the proteasome. This ensures that only specific proteins are degraded at appropriate times.
Roivant Sciences
A pharmaceutical company focused on developing new drugs.
Roivant Sciences is a biopharmaceutical company that leverages technology and data science to accelerate drug development. The company focuses on acquiring intellectual property rights for promising therapeutic candidates and bringing them through clinical trials to market. Roivant has established several subsidiaries, each specializing in different therapeutic areas, such as oncology, neurology, and infectious diseases.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:32:54|
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 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 8,675,385 | 794,999 | 10.91 | 2 hrs 12 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 7,840,698 | 757,766 | 10.35 | 2 hrs 19 mins |
| 3 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 6,818,385 | 735,160 | 9.27 | 2 hrs 35 mins |
| 4 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 6,649,956 | 729,414 | 9.12 | 2 hrs 38 mins |
| 5 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 5,266,434 | 677,588 | 7.77 | 3 hrs 5 mins |
| 6 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,062,167 | 668,876 | 7.57 | 3 hrs 10 mins |
| 7 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,805,870 | 655,215 | 7.33 | 3 hrs 16 mins |
| 8 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,990,832 | 619,051 | 6.45 | 3 hrs 43 mins |
| 9 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 3,288,757 | 578,961 | 5.68 | 4 hrs 14 mins |
| 10 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,206,923 | 574,557 | 5.58 | 4 hrs 18 mins |
| 11 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 3,061,266 | 566,276 | 5.41 | 4 hrs 26 mins |
| 12 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,044,617 | 564,538 | 5.39 | 4 hrs 27 mins |
| 13 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,723,151 | 539,713 | 5.05 | 4 hrs 45 mins |
| 14 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,713,814 | 544,298 | 4.99 | 4 hrs 49 mins |
| 15 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,458,188 | 523,657 | 4.69 | 5 hrs 7 mins |
| 16 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,428,905 | 522,728 | 4.65 | 5 hrs 10 mins |
| 17 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 2,381,193 | 455,384 | 5.23 | 4 hrs 35 mins |
| 18 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,345,630 | 517,417 | 4.53 | 5 hrs 18 mins |
| 19 | TITAN X GP102 [TITAN X] 6144 |
Nvidia | GP102 | 2,320,107 | 515,615 | 4.50 | 5 hrs 20 mins |
|
|
|||||||
| 20 | GeForce RTX 3070 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,196,861 | 507,377 | 4.33 | 5 hrs 33 mins |
| 21 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,835,008 | 478,627 | 3.83 | 6 hrs 16 mins |
| 22 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,830,669 | 469,395 | 3.90 | 6 hrs 9 mins |
| 23 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,815,081 | 475,111 | 3.82 | 6 hrs 17 mins |
| 24 | Tesla P40 GP102GL [Tesla P40] 11760 |
Nvidia | GP102GL | 1,789,184 | 473,593 | 3.78 | 6 hrs 21 mins |
| 25 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,643,538 | 460,263 | 3.57 | 6 hrs 43 mins |
| 26 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,578,554 | 454,920 | 3.47 | 6 hrs 55 mins |
| 27 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,493,255 | 446,371 | 3.35 | 7 hrs 10 mins |
| 28 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 1,459,626 | 442,304 | 3.30 | 7 hrs 16 mins |
| 29 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,440,759 | 441,026 | 3.27 | 7 hrs 21 mins |
| 30 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,371,560 | 430,373 | 3.19 | 7 hrs 32 mins |
| 31 | GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q] 4550 |
Nvidia | TU106M | 1,293,753 | 425,420 | 3.04 | 7 hrs 54 mins |
| 32 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,259,969 | 421,500 | 2.99 | 8 hrs 2 mins |
| 33 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,235,649 | 402,192 | 3.07 | 7 hrs 49 mins |
| 34 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,233,446 | 413,095 | 2.99 | 8 hrs 2 mins |
| 35 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 955,402 | 383,450 | 2.49 | 9 hrs 38 mins |
| 36 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 793,949 | 358,975 | 2.21 | 10 hrs 51 mins |
| 37 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 750,901 | 354,044 | 2.12 | 11 hrs 19 mins |
| 38 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 674,530 | 342,474 | 1.97 | 12 hrs 11 mins |
| 39 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 646,427 | 338,177 | 1.91 | 12 hrs 33 mins |
|
|
|||||||
| 40 | Quadro T2000 Mobile / Max-Q TU117GLM [Quadro T2000 Mobile / Max-Q] |
Nvidia | TU117GLM | 519,572 | 314,367 | 1.65 | 14 hrs 31 mins |
| 41 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 499,769 | 303,672 | 1.65 | 14 hrs 35 mins |
| 42 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 355,615 | 276,904 | 1.28 | 18 hrs 41 mins |
| 43 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 352,895 | 276,036 | 1.28 | 18 hrs 46 mins |
| 44 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 352,813 | 276,313 | 1.28 | 18 hrs 48 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:32:54|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|