RESEARCH: CANCER
FOLDING PROJECT #13009 PROFILE

PROJECT TEAM

Manager(s): Lin Zhu
Institution: the University of Illinois Urbana-Champaign

WORK UNIT INFO

Atoms: 60,000
Core: 0x24
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project aims to create supercharged fluorescent proteins that can better detect rare earth elements in our bodies. These proteins could help diagnose diseases like cancer and neurodegenerative disorders earlier. It also might lead to new drugs and therapies by targeting specific cells or tissues.

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

OFFICAL PROJECT DESCRIPTION

Super Charged Fluorescent protein design Rare earth elements play vital roles in various biological processes, and their detection using fluorescent proteins could advance biomedical research and diagnostics.

By developing more sensitive and specific sensors for rare earth elements, this project could contribute to early detection of diseases, such as cancer and neurodegenerative disorders, where abnormal levels of certain elements are often observed.

Moreover, the enhanced understanding of binding mechanisms between fluorescent proteins and rare earth elements could lead to the development of novel therapeutic agents or drug delivery systems tailored to target specific cellular pathways or tissues, thereby potentially improving treatment outcomes and patient well-being.This project aims to investigate the binding mechanism of supercharged fluorescent proteins for capturing rare earth elements and then design a new variant of fluorescent protein that exhibits stronger binding affinity for specific rare earth elements than existing fluorescent proteins.
In this project, there are 557 double mutants systems of yellow fluorescent protein with a negative charge of 31.

RELATED TERMS GLOSSARY AI BETA

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

Fluorescent protein

A protein that emits light when exposed to a specific wavelength of light.

Scientific: Healthcare
Biotechnology / Molecular Biology

Fluorescent proteins are naturally occurring or genetically engineered proteins that glow when excited by light. They are widely used in biological research for visualizing cells and molecules, tracking processes within living organisms, and developing diagnostic tools.


Rare earth elements

A group of 17 metallic elements with unique magnetic, optical, and electronic properties.

Scientific: Technology
Materials Science / Chemistry

Rare earth elements are a group of 17 metals found in the periodic table. They have special properties that make them valuable for various applications, including magnets, lasers, batteries, and electronics.


Biomedical research

Scientific investigation into biological processes and their application to medicine.

Academic: Research & Development
Healthcare / Biology

Biomedical research is the study of living organisms and their functions to understand diseases and develop new treatments. It involves various disciplines like biology, chemistry, and engineering to improve human health.


Cancer

A disease characterized by uncontrolled cell growth.

Medical: Pharmaceuticals
Healthcare / Oncology

Cancer is a group of diseases where abnormal cells grow uncontrollably and can spread to other parts of the body. It is caused by various factors like genetics, lifestyle, and environmental exposure.


Neurodegenerative disorders

A group of diseases characterized by the progressive loss of brain cells and function.

Medical: Pharmaceuticals
Healthcare / Neuroscience

Neurodegenerative disorders are a category of diseases that involve the gradual deterioration of nerve cells in the brain. Examples include Alzheimer's disease, Parkinson's disease, and Huntington's disease.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:33:45
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 5,224,510 84,870 61.56 0 hrs 23 mins
2 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 3,703,314 389,908 9.50 2 hrs 32 mins
3 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,879,284 362,225 7.95 3 hrs 1 mins
4 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,313,419 320,326 7.22 3 hrs 19 mins
5 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 2,247,348 323,827 6.94 3 hrs 27 mins
6 GeForce RTX 2070 Mobile / Max-Q Refresh
TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh]
Nvidia TU106M 2,048,704 319,737 6.41 3 hrs 45 mins
7 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,035,757 160,654 12.67 1 hrs 54 mins
8 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,018,267 174,087 11.59 2 hrs 4 mins
9 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,739,676 156,793 11.10 2 hrs 10 mins
10 GeForce RTX 3050 8GB
GA107 [GeForce RTX 3050 8GB]
Nvidia GA107 1,667,846 307,253 5.43 4 hrs 25 mins
11 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,412,536 289,523 4.88 4 hrs 55 mins
12 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,314,705 276,221 4.76 5 hrs 3 mins
13 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,192,041 264,944 4.50 5 hrs 20 mins
14 Intel Arc B580 Graphics
Battlemage G21 [Intel Arc B580 Graphics]
Intel Battlemage G21 1,112,661 262,792 4.23 5 hrs 40 mins
15 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,086,929 258,773 4.20 5 hrs 43 mins
16 GeForce GTX 1070 Mobile
GP104M [GeForce GTX 1070 Mobile]
Nvidia GP104M 987,384 84,870 11.63 2 hrs 4 mins
17 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 787,717 90,329 8.72 2 hrs 45 mins
18 GeForce RTX 3050 Ti Mobile
GA107M [GeForce RTX 3050 Ti Mobile]
Nvidia GA107M 751,703 84,870 8.86 2 hrs 43 mins
19 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 739,452 226,811 3.26 7 hrs 22 mins
20 P106-100
GP106 [P106-100]
Nvidia GP106 704,421 223,484 3.15 7 hrs 37 mins
21 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 677,816 84,870 7.99 3 hrs 0 mins
22 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 591,564 84,870 6.97 3 hrs 27 mins
23 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 503,721 150,597 3.34 7 hrs 11 mins
24 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 502,957 212,027 2.37 10 hrs 7 mins
25 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 478,446 84,870 5.64 4 hrs 15 mins
26 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 471,733 213,613 2.21 10 hrs 52 mins
27 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 281,779 84,870 3.32 7 hrs 14 mins
28 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 226,272 84,870 2.67 9 hrs 0 mins
29 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 191,437 106,794 1.79 13 hrs 23 mins
30 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 179,990 88,737 2.03 11 hrs 50 mins
31 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 127,995 127,602 1.00 23 hrs 56 mins
32 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 122,137 96,669 1.26 18 hrs 60 mins
33 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 90,365 84,870 1.06 22 hrs 32 mins
34 GeForce GTX 750
GM107 [GeForce GTX 750] 1111
Nvidia GM107 86,673 84,870 1.02 23 hrs 30 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:33:45
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 5 3600X 6-CORE 12 AMD
2 CORE I7-4770S CPU @ 3.10GHZ 8 Intel
3 RYZEN 9 9950X 16-CORE 32 AMD