Research section Research projects and references

Research: CANCER Folding Project #13010

Project #13010 overview

Project Summary AI Beta

This project designs super-powered fluorescent proteins that grab rare earth elements. These elements are important for our bodies, and finding them can help diagnose diseases like cancer early. The goal is to create a protein that's better at capturing specific rare earth elements than existing ones. The project involves testing 100 different versions of these proteins.
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
0x24
Status
Public
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 the 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 double mutant systems of yellow fluorescent protein with a negative charge of 31.

Performance data

Hardware Performance for Project 13010

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

Data as of Sunday, 02 August 2026 22:07:54

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 GeForce RTX 5090
GB202 [GeForce RTX 5090]
Nvidia GB202 25,890,541 88,691 291.92 0 hrs 5 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 9,862,343 556,077 17.74 1 hrs 21 mins
3 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 9,072,486 539,600 16.81 1 hrs 26 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,863,415 493,024 13.92 1 hrs 43 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 6,472,740 88,691 72.98 0 hrs 20 mins
6 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 5,189,813 88,691 58.52 0 hrs 25 mins
7 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 4,721,313 440,497 10.72 2 hrs 14 mins
8 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 3,708,068 213,467 17.37 1 hrs 23 mins
9 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 3,548,648 88,691 40.01 0 hrs 36 mins
10 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,417,867 337,677 10.12 2 hrs 22 mins
11 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,410,020 88,691 38.45 0 hrs 37 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,218,226 384,244 8.38 2 hrs 52 mins
13 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,188,728 88,691 35.95 0 hrs 40 mins
14 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,964,045 371,316 7.98 3 hrs 0 mins
15 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 2,377,395 88,691 26.81 0 hrs 54 mins
16 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,584,549 302,031 5.25 4 hrs 34 mins
17 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,372,916 88,691 15.48 1 hrs 33 mins
18 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,234,468 286,083 4.32 5 hrs 34 mins
19 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 1,102,855 88,691 12.43 1 hrs 56 mins
20 RTX A1000
GA107GL [RTX A1000]
Nvidia GA107GL 1,078,999 88,691 12.17 1 hrs 58 mins
21 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 181,173 144,712 1.25 19 hrs 10 mins
22 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 114,806 88,691 1.29 18 hrs 32 mins
23 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 88,473 88,691 1.00 24 hrs 4 mins