Research section Research projects and references

Research: MEMBRANE TRANSPORT Folding Project #17928

Project #17928 overview

Project Summary AI Beta

This project investigates how membrane transporters work. These proteins help move molecules into and out of cells. The project focuses on sugar transporters that can move different types of sugars. By understanding how these transporters recognize different molecules, researchers can design new drugs that specifically target certain transporters.
Automated summary; simplified and may not be fully accurate.

Project team

Manager(s)
Arnav Paul
Institution
University of Illinois

Work unit

Atoms
79,000
Core
0x23
Status
Public
Source material

Official Project Description

Membrane transporters are important for enabling molecules to go in and out of cells.

What is interesting is that while transporters typically have set functions, they can also transport molecules that do not necessarily relate to their function or cellular purpose.

For example, drugs often hijack transporters to enter cells without necessarily resembling the molecules or metabolites which that target transporter normally transports.

The goal of this project is to see how exactly a typical membrane transporter recognizes and transports molecules that look different from one another.

We choose a class of sugar transporters that transports a variety of different types of substrates to satisfy this goal.

Findings from this study can be generalized for the design of molecules (e.g., drugs) specific to a given transporter and its general mechanism.

Performance data

Hardware Performance for Project 17928

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

Data as of Sunday, 02 August 2026 21:55:03

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 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 15,010,458 174,063 86.24 0 hrs 17 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 12,068,002 161,552 74.70 0 hrs 19 mins
3 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 9,440,927 149,299 63.24 0 hrs 23 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 8,810,981 145,249 60.66 0 hrs 24 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 7,023,041 15,660 448.47 0 hrs 3 mins
6 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,377,164 130,702 48.79 0 hrs 30 mins
7 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 5,559,084 126,728 43.87 0 hrs 33 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 5,157,037 122,682 42.04 0 hrs 34 mins
9 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 3,959,609 15,660 252.85 0 hrs 6 mins
10 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,103,598 57,375 54.09 0 hrs 27 mins
11 GeForce RTX 4060 Max-Q / Mobile
AD107M [GeForce RTX 4060 Max-Q / Mobile]
Nvidia AD107M 2,871,738 94,235 30.47 0 hrs 47 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,853,038 81,125 35.17 0 hrs 41 mins
13 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 2,776,243 99,769 27.83 0 hrs 52 mins
14 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,638,543 96,917 27.22 0 hrs 53 mins
15 GeForce RTX 3050 8GB
GA107 [GeForce RTX 3050 8GB]
Nvidia GA107 1,915,861 87,955 21.78 1 hrs 6 mins
16 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 633,380 60,431 10.48 2 hrs 17 mins