RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17937 PROFILE

PROJECT TEAM

Manager(s): Arnav Paul
Institution: University of Illinois

WORK UNIT INFO

Atoms: 187,712
Core: 0x23
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

The project relates to special proteins that move stuff across cell walls using energy from ions. These proteins are found everywhere and help treat diseases like cancer and diabetes. Studying them can teach us how different types of proteins work together.

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

OFFICAL 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.

RELATED TERMS GLOSSARY AI BETA

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

Secondary active transporters

Proteins that use ion gradients to transport molecules across cell membranes.

Technical: Biotechnology
Cell Biology / Membrane Transport

Secondary active transporters are essential proteins found in all living organisms. They work by using the energy stored in an ion gradient (difference in electrical charge) across a cell membrane to move other molecules against their concentration gradient – meaning from an area of low concentration to an area of high concentration. This process is crucial for many cellular functions, including nutrient uptake, waste removal, and signal transduction. Many secondary active transporters are also targets for drug development, as they play roles in various diseases like cancer, diabetes, and neurological disorders.


Ion gradient

A difference in concentration of ions across a cell membrane.

Technical: Medicine
Biochemistry / Membrane Transport

An ion gradient refers to an uneven distribution of electrically charged atoms (ions) across a cell membrane. This difference in charge can be maintained by active transport processes, which use energy to move ions against their concentration gradient. Ion gradients are crucial for many cellular functions, including nerve impulse transmission, muscle contraction, and nutrient uptake.


Membrane Transport

The movement of molecules across cell membranes.

Technical: Biotechnology
Cell Biology / Cellular Processes

Membrane transport is the process by which substances move into and out of cells. This is essential for maintaining cellular homeostasis – keeping a stable internal environment. There are various types of membrane transport, including passive transport (movement without energy expenditure) and active transport (requiring energy). Membrane transport plays a crucial role in nutrient uptake, waste removal, signal transduction, and cell communication.


Simulations

Computer models used to mimic biological processes.

Technical: Biotechnology
Computational Biology / Molecular Modeling

Simulations are powerful tools in computational biology, allowing scientists to model and study complex biological systems using computer programs. These simulations can be used to understand how molecules interact, predict protein structures, and explore the dynamics of cellular processes. Simulations have become increasingly important in drug discovery, disease modeling, and understanding fundamental biological mechanisms.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:33:51
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 11,598,418 196,986 58.88 0 hrs 24 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 9,117,109 179,472 50.80 0 hrs 28 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 9,028,796 180,805 49.94 0 hrs 29 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 8,694,075 173,925 49.99 0 hrs 29 mins
5 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 8,316,542 172,748 48.14 0 hrs 30 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 6,979,098 21,070 331.23 0 hrs 4 mins
7 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,625,142 142,872 32.37 0 hrs 44 mins
8 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 4,583,098 143,042 32.04 0 hrs 45 mins
9 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 3,652,981 21,070 173.37 0 hrs 8 mins
10 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 3,384,748 129,164 26.21 0 hrs 55 mins
11 Radeon RX 6800/6800XT/6900XT
Navi 21 [Radeon RX 6800/6800XT/6900XT]
AMD Navi 21 3,257,107 127,955 25.46 0 hrs 57 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,814,850 69,611 40.44 0 hrs 36 mins
13 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,311,621 21,070 109.71 0 hrs 13 mins
14 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,105,143 95,255 22.10 1 hrs 5 mins
15 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 2,059,370 112,593 18.29 1 hrs 19 mins
16 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,376,562 91,727 15.01 1 hrs 36 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:33:51
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make