Research section Research projects and references

Research: CANCER Folding Project #13004

Project #13004 overview

Project Summary AI Beta

This project is about making fluorescent proteins that can grab rare earth elements. These elements are important for our bodies, and finding them could help diagnose diseases early. The new proteins could also be used to deliver medicine more effectively. Scientists will test lots of different versions of these proteins to see which ones work 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
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 13004

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

Data as of Sunday, 02 August 2026 22:08:00

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 4,671,074 427,282 10.93 2 hrs 12 mins
2 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 3,511,711 386,770 9.08 2 hrs 39 mins
3 Radeon RX 6800/6800XT/6900XT
Navi 21 [Radeon RX 6800/6800XT/6900XT]
AMD Navi 21 2,212,244 332,508 6.65 3 hrs 36 mins
4 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,200,422 209,342 10.51 2 hrs 17 mins
5 GeForce RTX 3050 8GB
GA107 [GeForce RTX 3050 8GB]
Nvidia GA107 1,755,193 315,770 5.56 4 hrs 19 mins
6 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 1,558,230 245,473 6.35 3 hrs 47 mins
7 Radeon RX 6700/6700XT/6800M
Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M]
AMD Navi 22 XT-XL 1,483,536 85,740 17.30 1 hrs 23 mins
8 RX 5600 OEM/5600XT/5700/5700XT
Navi 10 [RX 5600 OEM/5600XT/5700/5700XT]
AMD Navi 10 966,158 85,740 11.27 2 hrs 8 mins