Research section Research projects and references

Research: CANCER Folding Project #13008

Project #13008 overview

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.
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

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 206 double mutants systems of yellow fluorescent protein with a negative charge of 31.

Performance data

Hardware Performance for Project 13008

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

Data as of Sunday, 02 August 2026 22:07:56

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 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
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