RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #19200 PROFILE

PROJECT TEAM

Manager(s): Tanner Dean
Institution: University of Illinois

WORK UNIT INFO

Atoms: 84,576
Core: OPENMM_22
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

The project relates to how tiny proteins in cell membranes move things around. They come in three types: uniporters (move one thing), symporters (move two things together), and antiporters (move two things in opposite directions). By comparing similar proteins that work differently, we can learn more about how these transporters control the flow of important stuff like nutrients and medicine across cell membranes.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

A United Picture of Transporter Functions
Membrane transporters are an integral part of the cell and serve many roles across their involvement in the transport of ions, nutrients, neurotransmitters, and many drugs across cellular membranes.

There are three major classes of membrane transport proteins that facilitate the transport of various solutes.

These classes are Uniporters, which transport one solute across the membrane in one direction, Symporters, which transport two solutes across the membrane in the same direction, and Antiporters, which transfer two solutes in opposite directions across the membrane.

These classes follow different mechanisms of transport to move their solute(s) across the membrane.
Simulations for this project will be primarily focused on studying how structural differences, sequence level differences, and energetic level differences account for the difference in transport mechanisms across membrane transporters with high sequence similarity and similar solutes, yet varying classes of transporter.

By evaluating the differences in mechanism of transport arising in similar transporters of different classes, we hope to further improve our understanding of the controlling mechanisms behind membrane transport.

RELATED TERMS GLOSSARY AI BETA

Note: Glossary items are a high level summary and may not be 100% accurate.

Membrane transporters

Proteins embedded in cell membranes that move substances across.

Scientific: Biotechnology
Cellular Biology / Transport

Membrane transporters are essential proteins found within cell membranes. They act as gatekeepers, selectively allowing specific molecules like nutrients, ions, and drugs to enter or exit the cell. This process is crucial for maintaining cellular balance and function.


Uniporters

Membrane proteins that transport one molecule across the membrane.

Scientific: Biotechnology
Cellular Biology / Transport

Uniporters are a type of membrane transporter protein that move a single molecule across the cell membrane in one direction. This unidirectional transport is essential for processes like nutrient uptake and waste removal.


Symporters

Membrane proteins that transport two molecules across the membrane in the same direction.

Scientific: Biotechnology
Cellular Biology / Transport

Symporters are membrane transporter proteins that facilitate the movement of two different molecules across the cell membrane simultaneously in the same direction. This co-transport mechanism is crucial for processes like nutrient absorption and signal transduction.


Antiporters

Membrane proteins that transport two molecules across the membrane in opposite directions.

Scientific: Biotechnology
Cellular Biology / Transport

Antiporters are membrane transporter proteins that move two different molecules across the cell membrane in opposite directions. This counter-transport mechanism is essential for processes like ion balance and waste elimination.


Structural differences

Variations in the arrangement of atoms within a molecule.

Technical: Biotechnology
Biochemistry / Protein Structure

Structural differences refer to variations in the way atoms are arranged within a molecule. These differences can significantly impact a molecule's shape, function, and interactions with other molecules.


Sequence level differences

Variations in the order of amino acids within a protein.

Technical: Biotechnology
Molecular Biology / Protein Sequencing

Sequence level differences refer to variations in the order of amino acids that make up a protein. These differences can alter a protein's structure, function, and interactions with other molecules.


Energetic level differences

Variations in the energy required for a process.

Technical: Biotechnology
Biochemistry / Thermodynamics

Energetic level differences refer to variations in the amount of energy required for a biological process. These differences can influence the rate and efficiency of biochemical reactions.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:26:16
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 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,680,283 113,483 67.68 0 hrs 21 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 6,595,330 108,678 60.69 0 hrs 24 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,451,105 108,113 59.67 0 hrs 24 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,749,529 98,949 48.00 0 hrs 30 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,721,366 97,172 48.59 0 hrs 30 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,634,491 96,552 48.00 0 hrs 30 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,555,780 95,919 47.50 0 hrs 30 mins
8 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 4,187,182 93,389 44.84 0 hrs 32 mins
9 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,753,028 89,846 41.77 0 hrs 34 mins
10 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,169,232 85,237 37.18 0 hrs 39 mins
11 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,166,551 85,700 36.95 0 hrs 39 mins
12 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,886,802 82,379 35.04 0 hrs 41 mins
13 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,554,588 100,507 25.42 0 hrs 57 mins
14 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,478,472 78,640 31.52 0 hrs 46 mins
15 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,146,765 74,872 28.67 0 hrs 50 mins
16 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,910,273 72,195 26.46 0 hrs 54 mins
17 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,773,762 70,252 25.25 0 hrs 57 mins
18 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,297,417 63,173 20.54 1 hrs 10 mins
19 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,201,676 62,149 19.34 1 hrs 14 mins
20 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,128,142 59,058 19.10 1 hrs 15 mins
21 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,023,766 57,151 17.91 1 hrs 20 mins
22 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 989,934 58,433 16.94 1 hrs 25 mins
23 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 956,674 58,311 16.41 1 hrs 28 mins
24 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 806,018 54,725 14.73 1 hrs 38 mins
25 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 697,440 51,376 13.58 1 hrs 46 mins
26 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 590,740 48,372 12.21 1 hrs 58 mins
27 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 568,932 48,305 11.78 2 hrs 2 mins
28 P106-090
GP106 [P106-090]
Nvidia GP106 314,979 39,444 7.99 3 hrs 0 mins
29 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 310,707 39,230 7.92 3 hrs 2 mins
30 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 132,873 29,974 4.43 5 hrs 25 mins
31 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 77,464 24,327 3.18 7 hrs 32 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 03:26:16
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make