Research section Research projects and references

Research: CANCER Folding Project #13002

Project #13002 overview

Project Summary AI Beta

This project looks at how special proteins called fluorescent proteins can be used to find rare earth elements in our bodies. These elements are important for health, and finding them early could help diagnose diseases like cancer. The project will try to make even stronger fluorescent proteins that grab onto specific rare earth elements better than before. They'll do this by testing 100 different versions of a yellow protein, changing one part at a time to see what works best.
Automated summary; simplified and may not be fully accurate.

Project team

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

Work unit

Atoms
60,000
Core
0x23
Status
Public

No related projects listed.

Source material

Official 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 100 single-point mutant systems of yellow fluorescent protein with a negative charge of 31.

Performance data

Hardware Performance for Project 13002

Compare community-sampled Folding@Home output for the GPUs and CPUs processing this project.

Data as of Sunday, 02 August 2026 22:08:03

GPU PPD Averages

Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 3,501,369 354,905 9.87 2 hrs 26 mins
2 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,441,918 316,135 7.72 3 hrs 6 mins
3 GeForce RTX 2060 12GB
TU106 [GeForce RTX 2060 12GB]
Nvidia TU106 2,433,378 314,999 7.73 3 hrs 6 mins
4 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,106,846 300,609 7.01 3 hrs 25 mins
5 Radeon RX 7700XT/7800XT
Navi 32 [Radeon RX 7700XT/7800XT]
AMD Navi 32 1,937,875 293,039 6.61 3 hrs 38 mins
6 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,920,375 276,379 6.95 3 hrs 27 mins
7 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,912,347 281,219 6.80 3 hrs 32 mins
8 Radeon RX 6800/6800XT/6900XT
Navi 21 [Radeon RX 6800/6800XT/6900XT]
AMD Navi 21 1,893,025 281,022 6.74 3 hrs 34 mins
9 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,773,224 286,273 6.19 3 hrs 52 mins
10 GeForce RTX 2070 Mobile / Max-Q Refresh
TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh]
Nvidia TU106M 1,736,080 282,020 6.16 3 hrs 54 mins
11 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,561,221 76,132 20.51 1 hrs 10 mins
12 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,284,175 266,656 4.82 4 hrs 59 mins
13 Radeon RX 6700/6700XT/6800M
Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M]
AMD Navi 22 XT-XL 1,263,239 107,183 11.79 2 hrs 2 mins
14 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,167,058 248,290 4.70 5 hrs 6 mins
15 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 948,439 239,050 3.97 6 hrs 3 mins
16 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 807,921 216,216 3.74 6 hrs 25 mins
17 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 774,733 215,388 3.60 6 hrs 40 mins
18 Quadro P3200 Mobile
GP104GLM [Quadro P3200 Mobile]
Nvidia GP104GLM 656,321 204,402 3.21 7 hrs 28 mins
19 Radeon RX 6600/6600 XT/6600M
Navi 23 XT-XL [Radeon RX 6600/6600 XT/6600M]
AMD Navi 23 XT-XL 633,557 221,748 2.86 8 hrs 24 mins
20 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 201,308 155,341 1.30 18 hrs 31 mins
21 RX 5600 OEM/5600XT/5700/5700XT
Navi 10 [RX 5600 OEM/5600XT/5700/5700XT]
AMD Navi 10 162,694 128,323 1.27 18 hrs 56 mins