RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17932 PROFILE
PROJECT TEAM
Manager(s): Arnav PaulInstitution: University of Illinois
WORK UNIT INFO
Atoms: 103,391Core: 0x23
Status: Public
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TLDR; PROJECT SUMMARY AI BETA
Secondary active transporters are proteins that use ions to move molecules across cell membranes. They're found in all living things and work the same way, even if they look different. This project will help us understand how these transporters use ion power, which is important for treating diseases like cancer and diabetes.
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
Secondary active transporters
Proteins that use ion gradients to transport molecules across cell membranes.
Secondary active transporters are essential proteins found in all living organisms. They work by using the energy stored in an ion gradient to move other molecules across cell membranes. This process is crucial for various cellular functions, including nutrient uptake, waste removal, and signal transduction. Many secondary active transporters are also drug targets, making them important for treating diseases like cancer, diabetes, and neurological disorders.
Ion gradient
A difference in concentration of ions across a cell membrane.
An ion gradient is a fundamental concept in cellular biology. It refers to the uneven distribution of charged atoms (ions) across a cell membrane. This difference in concentration creates an electrochemical potential that drives various cellular processes, including nutrient uptake, waste removal, and nerve impulse transmission. Secondary active transporters utilize ion gradients to facilitate the movement of other molecules across membranes.
Drug targets
Molecules or proteins that are involved in disease processes and can be targeted by drugs.
Drug targets are essential components of the drug development process. They refer to specific molecules or proteins that play a role in disease pathways. By targeting these molecules, drugs can disrupt the disease process and provide therapeutic benefits. Secondary active transporters are often considered drug targets due to their involvement in various physiological processes.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:33:59|
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 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 22,515,601 | 129,919 | 173.30 | 0 hrs 8 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 19,358,799 | 8,425 | 2297.78 | 0 hrs 1 mins |
| 3 | GeForce RTX 4080 SUPER AD103 [GeForce RTX 4080 SUPER] |
Nvidia | AD103 | 16,699,678 | 8,425 | 1982.16 | 0 hrs 1 mins |
| 4 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 10,087,059 | 97,059 | 103.93 | 0 hrs 14 mins |
| 5 | GeForce RTX 4070 SUPER AD104 [GeForce RTX 4070 SUPER] |
Nvidia | AD104 | 9,182,234 | 90,107 | 101.90 | 0 hrs 14 mins |
| 6 | Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE] |
AMD | Navi 31 | 6,907,833 | 88,070 | 78.44 | 0 hrs 18 mins |
| 7 | GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti] |
Nvidia | AD106 | 6,408,318 | 172,740 | 37.10 | 0 hrs 39 mins |
| 8 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,356,344 | 69,988 | 47.96 | 0 hrs 30 mins |
| 9 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 3,250,920 | 68,413 | 47.52 | 0 hrs 30 mins |
| 10 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,193,329 | 45,128 | 48.60 | 0 hrs 30 mins |
| 11 | GeForce RTX 3050 8GB GA107 [GeForce RTX 3050 8GB] |
Nvidia | GA107 | 1,778,296 | 56,409 | 31.53 | 0 hrs 46 mins |
| 12 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,417,626 | 52,750 | 26.87 | 0 hrs 54 mins |
| 13 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 946,810 | 45,679 | 20.73 | 1 hrs 9 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:33:59|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
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