RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17928 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 79,000
Core: 0x23
Status: Public

Related Projects

TLDR; 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.

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

OFFICAL 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.

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 facilitate the movement of molecules across.

Technical: Biotechnology, Pharmaceuticals
Cell Biology / Cellular Transport

Membrane transporters are proteins found within the membrane of cells. Their primary role is to control the movement of molecules both into and out of the cell. This process is essential for cellular function as it allows for the uptake of nutrients, removal of waste products, and signaling between cells.


Drugs

Chemical substances used for the diagnosis, treatment, or prevention of disease.

Technical: Pharmaceuticals
Pharmacology / Drug Delivery

Drugs are chemical compounds designed to have a specific effect on the body. They can be used to treat various conditions like infections, pain, and chronic diseases. Drug development involves complex research to ensure efficacy and safety.


Sugar transporters

Membrane proteins that facilitate the transport of sugar molecules across cell membranes.

Technical: Biotechnology, Pharmaceuticals
Biochemistry / Metabolism

Sugar transporters are a specialized type of membrane protein responsible for moving sugar molecules into and out of cells. They play a crucial role in cellular energy production, storage, and signaling pathways.


Substrates

Molecules that bind to an enzyme and undergo a chemical reaction catalyzed by the enzyme.

Technical: Biotechnology, Pharmaceuticals
Biochemistry / Enzyme Kinetics

In biochemistry, substrates are the molecules that enzymes act upon. Enzymes are biological catalysts that speed up chemical reactions. Substrates bind to the active site of an enzyme, where the reaction takes place.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:34:05
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

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:34:05
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make