RESEARCH: CANCER
FOLDING PROJECT #17768 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 100,957Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how proteins use ion power to move molecules across cell membranes. These proteins are found everywhere in life and help transport important things like medicine! Studying them can lead to new treatments for diseases.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Projects 17745-17750 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 crucial 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 essential 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 concentration of ions across a membrane.
An ion gradient is a crucial concept in cellular transport. It refers to the uneven distribution of electrically charged atoms (ions) across a cell membrane. This difference in concentration creates an electrochemical potential that drives the movement of ions and other molecules across the membrane. Secondary active transporters rely on these gradients to power their function.
Membrane Transporters
Proteins embedded in cell membranes that facilitate the movement of molecules across them.
Membrane transporters are a diverse group of proteins found within cell membranes. They play a vital role in transporting various substances into and out of cells. These transporters can be classified as passive or active, depending on whether they require energy to move molecules across the membrane. They are essential for maintaining cellular homeostasis, nutrient uptake, waste removal, and signaling.
Proteins
Large complex molecules essential for all biological processes.
Proteins are the workhorses of cells, carrying out a vast array of functions. They are composed of chains of amino acids linked together by peptide bonds. Proteins can act as enzymes, catalyzing biochemical reactions, transport molecules across membranes, provide structural support, and regulate cellular processes. Their diverse structures and functions make them essential for life.
Ion
An atom or molecule with a net electrical charge.
Ions are atoms or molecules that have gained or lost electrons, resulting in a net electrical charge. Positively charged ions are called cations, while negatively charged ions are called anions. Ions play crucial roles in various biological processes, including nerve impulse transmission, muscle contraction, and maintaining fluid balance.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:35:47|
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 | 6,990,339 | 165,633 | 42.20 | 0 hrs 34 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,438,151 | 159,850 | 40.28 | 0 hrs 36 mins |
| 3 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,249,118 | 151,884 | 34.56 | 0 hrs 42 mins |
| 4 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,726,796 | 146,276 | 32.31 | 0 hrs 45 mins |
| 5 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,230,969 | 141,402 | 29.92 | 0 hrs 48 mins |
| 6 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 4,228,996 | 141,945 | 29.79 | 0 hrs 48 mins |
| 7 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,833,378 | 137,540 | 27.87 | 0 hrs 52 mins |
| 8 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,789,999 | 135,984 | 27.87 | 0 hrs 52 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,945,612 | 124,234 | 23.71 | 1 hrs 1 mins |
| 10 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,577,292 | 119,495 | 21.57 | 1 hrs 7 mins |
| 11 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,478,078 | 118,118 | 20.98 | 1 hrs 9 mins |
| 12 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,033,651 | 110,627 | 18.38 | 1 hrs 18 mins |
| 13 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,897,958 | 107,639 | 17.63 | 1 hrs 22 mins |
| 14 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,825,740 | 108,122 | 16.89 | 1 hrs 25 mins |
| 15 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 1,510,361 | 100,011 | 15.10 | 1 hrs 35 mins |
| 16 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 1,387,195 | 96,889 | 14.32 | 1 hrs 41 mins |
| 17 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,227,551 | 93,771 | 13.09 | 1 hrs 50 mins |
| 18 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 1,139,435 | 91,431 | 12.46 | 1 hrs 56 mins |
| 19 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 1,135,093 | 91,122 | 12.46 | 1 hrs 56 mins |
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| 20 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,121,419 | 90,748 | 12.36 | 1 hrs 57 mins |
| 21 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,053,374 | 87,753 | 12.00 | 1 hrs 60 mins |
| 22 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 923,362 | 85,226 | 10.83 | 2 hrs 13 mins |
| 23 | Radeon Pro W5700 Navi 10 [Radeon Pro W5700] |
AMD | Navi 10 | 881,062 | 78,255 | 11.26 | 2 hrs 8 mins |
| 24 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 676,017 | 73,324 | 9.22 | 2 hrs 36 mins |
| 25 | Radeon RX 6700/6700 XT / 6800M Navi 22 [Radeon RX 6700/6700 XT / 6800M] |
AMD | Navi 22 | 673,837 | 71,752 | 9.39 | 2 hrs 33 mins |
| 26 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 585,294 | 73,380 | 7.98 | 3 hrs 1 mins |
| 27 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 527,062 | 70,641 | 7.46 | 3 hrs 13 mins |
| 28 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 428,872 | 66,141 | 6.48 | 3 hrs 42 mins |
| 29 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 353,213 | 61,788 | 5.72 | 4 hrs 12 mins |
| 30 | Radeon RX Vega M XT/ M GH [Radeon RX Vega M XT/ M GH] |
AMD | 237,352 | 53,822 | 4.41 | 5 hrs 27 mins | |
| 31 | Radeon RX 6400 / 6500 XT Navi 24 [Radeon RX 6400 / 6500 XT] |
AMD | Navi 24 | 137,235 | 44,844 | 3.06 | 7 hrs 51 mins |
| 32 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 110,335 | 42,147 | 2.62 | 9 hrs 10 mins |
| 33 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 96,745 | 40,340 | 2.40 | 10 hrs 0 mins |
| 34 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 80,018 | 37,643 | 2.13 | 11 hrs 17 mins |
| 35 | Radeon Pro WX 2100 (Lexa) Polaris Pro [Radeon Pro WX 2100 (Lexa)] |
AMD | Polaris Pro | 38,057 | 29,514 | 1.29 | 18 hrs 37 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:35:47|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|