Research section Research projects and references

Research: CANCER Folding Project #17795

Project #17795 overview

Project Summary AI Beta

Secondary active transporters are proteins that use ion gradients to move molecules across cell membranes. They're found everywhere and help treat diseases like cancer and diabetes. The project uses simulations to understand how these proteins work, no matter their shape or type.
Automated summary; simplified and may not be fully accurate.

Project team

Manager(s)
Matthew Chan
Institution
University of Illinois Urbana-Champaign

Work unit

Atoms
65,600
Core
OPENMM_22
Status
Public
Source material

Official Project Description

Molecular basis of secondary active transporters. Secondary active membrane transporters are proteins that utilize ions to transport an assortment of molecules across cell membranes.

These proteins are found in all domains in life and surprisingly, despite vastly different structures, operate under the same mechanism by using an ion gradient to assist in small molecule transport.

Furthermore, many of these secondary active transporters are drug targets to treat diseases like cancer, diabetes, and neurological disorders.

The simulations in this project will allow us to understand a universal role of ion-coupling across different families of proteins.

Performance data

Hardware Performance for Project 17795

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

Data as of Sunday, 02 August 2026 21:55:43

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 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 6,604,557 161,188 40.97 0 hrs 35 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 6,134,551 156,537 39.19 0 hrs 37 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 5,599,064 154,073 36.34 0 hrs 40 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 5,031,734 151,418 33.23 0 hrs 43 mins
5 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 4,474,117 144,995 30.86 0 hrs 47 mins
6 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,035,159 139,802 28.86 0 hrs 50 mins
7 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 3,954,491 139,089 28.43 0 hrs 51 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,445,952 132,909 25.93 0 hrs 56 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,245,907 130,210 24.93 0 hrs 58 mins
10 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,654,931 151,852 17.48 1 hrs 22 mins
11 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,609,059 120,790 21.60 1 hrs 7 mins
12 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,518,094 119,493 21.07 1 hrs 8 mins
13 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,117,408 112,732 18.78 1 hrs 17 mins
14 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,253,811 94,326 13.29 1 hrs 48 mins
15 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 1,119,186 91,642 12.21 1 hrs 58 mins
16 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 552,662 72,246 7.65 3 hrs 8 mins