RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17945 PROFILE
PROJECT TEAM
Manager(s): Arnav PaulInstitution: University of Illinois
WORK UNIT INFO
Atoms: 117,096Core: 0x23
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project relates to proteins that use ions to move molecules across cell membranes. These proteins are important for many processes and are being studied to develop new drugs.
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 from an existing ion gradient to move other molecules across cell membranes. This process is vital for various cellular functions, including nutrient uptake, waste removal, and signal transduction. Many secondary active transporters are also drug targets for treating diseases like cancer, diabetes, and neurological disorders.
Ion gradient
A difference in ion concentration across a cell membrane.
An ion gradient is a separation of electrically charged particles (ions) between two areas. In cells, this often refers to a difference in ion concentration across the cell membrane. This gradient creates potential energy that can be used to drive various cellular processes, including transporting molecules across the membrane.
Drug targets
Molecules or biological pathways that are targeted by drugs to treat diseases.
Drug targets are specific molecules or processes within the body that pharmaceutical companies aim to influence with medications. By targeting these specific areas, drugs can effectively treat various diseases and conditions.
Simulations
Computer programs that mimic real-world processes or systems.
Simulations are powerful tools used in various scientific fields to study complex systems and phenomena. By creating computer models that replicate real-world interactions, researchers can gain insights into how things work, test hypotheses, and predict outcomes.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:33:40|
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 | 18,016,185 | 117,653 | 153.13 | 0 hrs 9 mins |
| 2 | GeForce RTX 4080 SUPER AD103 [GeForce RTX 4080 SUPER] |
Nvidia | AD103 | 16,398,165 | 8,878 | 1847.06 | 0 hrs 1 mins |
| 3 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 15,235,283 | 78,997 | 192.86 | 0 hrs 7 mins |
| 4 | GeForce RTX 4070 SUPER AD104 [GeForce RTX 4070 SUPER] |
Nvidia | AD104 | 10,943,059 | 8,878 | 1232.60 | 0 hrs 1 mins |
| 5 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 7,593,138 | 62,761 | 120.98 | 0 hrs 12 mins |
| 6 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 4,654,997 | 81,024 | 57.45 | 0 hrs 25 mins |
| 7 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,560,662 | 72,984 | 48.79 | 0 hrs 30 mins |
| 8 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 2,998,362 | 68,941 | 43.49 | 0 hrs 33 mins |
| 9 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 2,844,361 | 8,878 | 320.38 | 0 hrs 4 mins |
| 10 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,258,270 | 62,464 | 36.15 | 0 hrs 40 mins |
| 11 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,027,101 | 25,460 | 79.62 | 0 hrs 18 mins |
| 12 | GeForce RTX 3050 8GB GA107 [GeForce RTX 3050 8GB] |
Nvidia | GA107 | 1,582,162 | 56,527 | 27.99 | 0 hrs 51 mins |
| 13 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 1,241,995 | 8,878 | 139.90 | 0 hrs 10 mins |
| 14 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 550,796 | 8,878 | 62.04 | 0 hrs 23 mins |
| 15 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 311,105 | 33,374 | 9.32 | 2 hrs 34 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:33:40|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
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