RESEARCH: CANCER
FOLDING PROJECT #17805 PROFILE

PROJECT TEAM

Manager(s): Rafal Wiewiora
Institution: Memorial Sloan Kettering Cancer Center
Project URL: View Project Website

WORK UNIT INFO

Atoms: 80,000
Core: OPENMM_22
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project studies BAX, a protein important for cell death in lymphoma. It's similar to another protein studied before, but this one changes shape dramatically when activated. This makes understanding it harder, but could lead to new cancer treatments.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

BAX apoptotic protein --- a drug target in lymphoma. This is a homologous (i.e shares some structures) protein to BCL in projects 17800-03 --- as in there, I am testing adaptive sampling strategies --- this project is 'vanilla' (i.e.

no adaptive algorithm) and the problem here is probably much harder than in the previous project, this particular protein experiences 'activation' which is a massive structural change, a long tail unbinds and extends away from the protein.

RELATED TERMS GLOSSARY AI BETA

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

BAX apoptotic protein

A pro-apoptotic protein involved in programmed cell death.

Scientific: Biotechnology
Oncology / Lymphoma Research

BAX is a protein that plays a crucial role in triggering apoptosis, the process of programmed cell death. It is found to be dysregulated in various cancers, including lymphoma. Research focuses on BAX as a potential drug target for cancer therapies.


BCL

Bcl-2 family of proteins regulating apoptosis.

Scientific: Biotechnology
Oncology / Protein Structure Research

The Bcl-2 protein family consists of various proteins that play a critical role in controlling cell death (apoptosis). Some members promote cell survival, while others, like BAX, induce apoptosis. Understanding the interactions within this family is crucial for developing targeted cancer therapies.


Adaptive Sampling

A technique for selecting protein structures in simulations.

Technical: Biotechnology
Computational Biology / Protein Modeling

Adaptive sampling is a computational method used to improve the efficiency of protein modeling simulations. It involves dynamically adjusting the selection criteria for protein structures during simulations, focusing on regions that are more relevant for understanding protein function or folding.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:34:50
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 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 5,234,965 230,117 22.75 1 hrs 3 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,940,000 222,986 22.15 1 hrs 5 mins
3 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,934,145 208,619 18.86 1 hrs 16 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 3,813,710 207,263 18.40 1 hrs 18 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 2,827,602 187,529 15.08 1 hrs 36 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,455,842 179,040 13.72 1 hrs 45 mins
7 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,258,080 173,951 12.98 1 hrs 51 mins
8 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,142,147 171,067 12.52 1 hrs 55 mins
9 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,081,956 169,531 12.28 1 hrs 57 mins
10 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,081,202 169,564 12.27 1 hrs 57 mins
11 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,986,379 166,506 11.93 2 hrs 1 mins
12 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,879,007 163,865 11.47 2 hrs 6 mins
13 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,850,532 162,938 11.36 2 hrs 7 mins
14 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,833,398 162,536 11.28 2 hrs 8 mins
15 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,585,674 152,650 10.39 2 hrs 19 mins
16 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,476,840 151,552 9.74 2 hrs 28 mins
17 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,397,173 148,543 9.41 2 hrs 33 mins
18 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,150,599 139,125 8.27 2 hrs 54 mins
19 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,090,591 137,061 7.96 3 hrs 1 mins
20 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,034,177 134,456 7.69 3 hrs 7 mins
21 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 994,714 132,202 7.52 3 hrs 11 mins
22 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 985,078 131,379 7.50 3 hrs 12 mins
23 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 286,966 87,581 3.28 7 hrs 19 mins
24 GeForce GTX 1050 Mobile
GP107M [GeForce GTX 1050 Mobile]
Nvidia GP107M 252,604 83,794 3.01 7 hrs 58 mins
25 P106-100
GP106 [P106-100]
Nvidia GP106 247,328 83,370 2.97 8 hrs 5 mins
26 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 121,153 65,088 1.86 12 hrs 54 mins
27 GeForce GT 840M
GM108 [GeForce GT 840M]
Nvidia GM108 39,980 43,053 0.93 25 hrs 51 mins
28 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 30,580 40,542 0.75 31 hrs 49 mins
29 GeForce 920M
GK208 [GeForce 920M]
Nvidia GK208 26,734 39,832 0.67 35 hrs 46 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:34:50
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make