RESEARCH: CANCER
FOLDING PROJECT #13008 PROFILE
PROJECT TEAM
Manager(s): Lin ZhuInstitution: the University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 60,000Core: 0x24
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project is designing super-charged fluorescent proteins that can detect rare earth elements. These elements are important for our bodies and detecting them could help diagnose diseases like cancer earlier. The goal is to create a protein that binds better to specific rare earth elements than existing ones, potentially leading to new treatments.
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 206 double mutants systems of yellow fluorescent protein with a negative charge of 31.
RELATED TERMS GLOSSARY AI BETA
Fluorescent protein
Proteins that emit light when exposed to certain wavelengths.
Fluorescent proteins are naturally occurring or engineered proteins that absorb light at one wavelength and re-emit it at a longer wavelength. This property makes them valuable tools in biological research for tracking molecules, visualizing cells, and studying protein interactions.
Rare earth elements
A group of 17 metallic elements with similar chemical properties.
Rare earth elements are a set of metallic elements found in the periodic table. They are called 'rare' because they are not as abundant as other metals, but their unique magnetic, luminescent, and catalytic properties make them crucial for various technologies, including electronics, magnets, and medical imaging.
Supercharged fluorescent protein
A variant of fluorescent protein with enhanced fluorescence intensity.
Supercharged fluorescent proteins are engineered versions of naturally occurring fluorescent proteins that have been modified to produce brighter and more stable fluorescence. These improvements make them valuable tools for a wide range of applications, such as live-cell imaging and high-throughput screening.
Binding mechanism
The process by which molecules interact and attach to each other.
Binding mechanisms describe how molecules connect and form temporary or permanent associations. These interactions are fundamental to biological processes, such as enzyme activity, protein folding, and drug-target binding. Understanding binding mechanisms is essential for developing new drugs and therapies.
Double mutants
Proteins with two specific amino acid substitutions.
Double mutants are proteins that have undergone genetic modifications resulting in the replacement of two specific amino acids. These changes can alter protein structure and function, providing insights into the role of individual amino acids and enabling researchers to study protein evolution and design.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:33:46|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 3,332,995 | 272,687 | 12.22 | 1 hrs 58 mins |
| 2 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 3,027,536 | 85,574 | 35.38 | 0 hrs 41 mins |
| 3 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 2,517,800 | 277,770 | 9.06 | 2 hrs 39 mins |
| 4 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,312,499 | 85,810 | 26.95 | 0 hrs 53 mins |
| 5 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,212,056 | 328,211 | 6.74 | 3 hrs 34 mins |
| 6 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,202,672 | 330,587 | 6.66 | 3 hrs 36 mins |
| 7 | GeForce RTX 2070 Mobile / Max-Q Refresh TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh] |
Nvidia | TU106M | 2,119,377 | 326,263 | 6.50 | 3 hrs 42 mins |
| 8 | GeForce RTX 3050 8GB GA107 [GeForce RTX 3050 8GB] |
Nvidia | GA107 | 1,680,335 | 312,388 | 5.38 | 4 hrs 28 mins |
| 9 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 1,332,254 | 280,465 | 4.75 | 5 hrs 3 mins |
| 10 | GeForce GTX Titan X GM200 [GeForce GTX Titan X] 6144 |
Nvidia | GM200 | 1,189,085 | 276,394 | 4.30 | 5 hrs 35 mins |
| 11 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,092,784 | 241,705 | 4.52 | 5 hrs 19 mins |
| 12 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 1,048,268 | 84,870 | 12.35 | 1 hrs 57 mins |
| 13 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 962,579 | 252,529 | 3.81 | 6 hrs 18 mins |
| 14 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 828,550 | 165,323 | 5.01 | 4 hrs 47 mins |
| 15 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 782,843 | 237,026 | 3.30 | 7 hrs 16 mins |
| 16 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 759,086 | 85,272 | 8.90 | 2 hrs 42 mins |
| 17 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 737,938 | 230,148 | 3.21 | 7 hrs 29 mins |
| 18 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 727,989 | 85,342 | 8.53 | 2 hrs 49 mins |
| 19 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 719,943 | 86,150 | 8.36 | 2 hrs 52 mins |
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| 20 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 575,498 | 173,116 | 3.32 | 7 hrs 13 mins |
| 21 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 568,621 | 85,907 | 6.62 | 3 hrs 38 mins |
| 22 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 534,882 | 167,850 | 3.19 | 7 hrs 32 mins |
| 23 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 199,339 | 84,870 | 2.35 | 10 hrs 13 mins |
| 24 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 192,968 | 107,341 | 1.80 | 13 hrs 21 mins |
| 25 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 191,275 | 147,845 | 1.29 | 18 hrs 33 mins |
| 26 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 130,056 | 130,069 | 1.00 | 24 hrs 0 mins |
| 27 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 88,203 | 86,355 | 1.02 | 23 hrs 30 mins |
| 28 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 84,407 | 112,001 | 0.75 | 31 hrs 51 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:33:46|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|---|---|---|---|---|
| 1 | PHENOM II X4 970 | 4 | AMD |