Research section Research projects and references

Research: MEMBRANE TRANSPORT Folding Project #17927

Project #17927 overview

Project Summary AI Beta

This project studies how sugar transporters work. They usually move sugar molecules, but can also move other things like drugs. By figuring out how they recognize different molecules, scientists hope to design better drugs that target specific 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 17927

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

Data as of Friday, 14 August 2026 15:29:29

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 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 17,939,763 14,690 1221.22 0 hrs 1 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 11,459,783 151,283 75.75 0 hrs 19 mins
3 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 9,285,164 142,334 65.24 0 hrs 22 mins
4 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 9,221,576 141,972 64.95 0 hrs 22 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 6,400,856 14,690 435.73 0 hrs 3 mins
6 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,055,398 121,523 49.83 0 hrs 29 mins
7 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 5,539,244 119,059 46.53 0 hrs 31 mins
8 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 4,977,383 116,830 42.60 0 hrs 34 mins
9 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,261,603 108,946 39.12 0 hrs 37 mins
10 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 3,438,333 14,690 234.06 0 hrs 6 mins
11 Radeon RX 6800/6800XT/6900XT
Navi 21 [Radeon RX 6800/6800XT/6900XT]
AMD Navi 21 3,073,941 99,043 31.04 0 hrs 46 mins
12 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 3,047,791 98,938 30.81 0 hrs 47 mins
13 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 3,030,188 99,200 30.55 0 hrs 47 mins
14 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 2,833,288 54,176 52.30 0 hrs 28 mins
15 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 2,622,553 95,090 27.58 0 hrs 52 mins
16 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,423,029 54,791 44.22 0 hrs 33 mins
17 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,191,157 89,010 24.62 0 hrs 58 mins
18 GeForce RTX 4060 Max-Q / Mobile
AD107M [GeForce RTX 4060 Max-Q / Mobile]
Nvidia AD107M 1,617,669 79,291 20.40 1 hrs 11 mins