RESEARCH: CANCER
FOLDING PROJECT #18019 PROFILE

PROJECT TEAM

Manager(s): Rafal Wiewiora
Institution: Roivant Sciences (Silicon Therapeutics)
Project URL: View Project Website

WORK UNIT INFO

Atoms: 498,112
Core: 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

Note: Glossary items are a high level summary and may not be 100% accurate.

E3 ligase

Enzyme that attaches ubiquitin to proteins for degradation.

Scientific: Medicine
Biotechnology / Protein 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.

Scientific: Medicine
Biotechnology / Protein Degradation

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.

Scientific: Medicine
Biotechnology / Protein Modification

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.

Scientific: Medicine
Biotechnology / Protein 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.

Scientific: Medicine
Biotechnology / Protein Degradation

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.

Company: Pharmaceuticals
Biotechnology / Drug Development

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