RESEARCH: CANCER
FOLDING PROJECT #17730 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 118,949Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how proteins use ion gradients to move molecules across cell membranes. These proteins are important for many bodily functions and are targets for drugs treating diseases like cancer and diabetes. By studying them, we can learn more about how these proteins work across different types of organisms.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Projects 17711-17724 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 disease like cancer, diabetes, and neurological disorders.
These simulations 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 ions to transport molecules across cell membranes.
Secondary active transporters are crucial proteins found in all living organisms. They utilize an existing ion gradient to power the movement of various molecules across cell membranes. This process is essential for many cellular functions and makes these transporters important targets for treating diseases like cancer, diabetes, and neurological disorders.
Ion gradient
A difference in ion concentration across a cell membrane.
An ion gradient refers to an uneven distribution of charged particles (ions) on either side of a cell membrane. This imbalance in charge is essential for various cellular processes, including nerve impulse transmission and nutrient uptake. Secondary active transporters exploit this gradient to facilitate the movement of molecules across the membrane.
Drug targets
Molecules or cellular processes that are targeted by drugs.
Drug targets are specific molecules or cellular pathways that are involved in the development or progression of a disease. By targeting these molecules, drugs can aim to either block their function or enhance their activity, leading to therapeutic effects.
Simulations
Computer models used to represent and study complex systems.
Simulations are powerful tools in biotechnology research that allow scientists to create virtual representations of biological processes. These models can be used to test hypotheses, explore different scenarios, and gain insights into the behavior of complex systems like proteins or entire cells.
Cancer
A group of diseases characterized by uncontrolled cell growth.
Cancer is a broad term encompassing various diseases characterized by the uncontrolled growth and spread of abnormal cells. These cells can invade surrounding tissues and organs, leading to life-threatening complications.
Diabetes
A metabolic disorder characterized by high blood sugar levels.
Diabetes is a chronic disease affecting how the body regulates blood sugar (glucose). In type 1 diabetes, the immune system destroys insulin-producing cells. In type 2 diabetes, the body becomes resistant to insulin or doesn't produce enough. Both types lead to high blood sugar levels, which can damage various organs over time.
Neurological disorders
Conditions affecting the nervous system.
Neurological disorders encompass a wide range of conditions impacting the brain, spinal cord, and nerves. These disorders can affect various aspects of neurological function, including movement, sensation, cognition, and emotions.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:36:28|
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 | 7,160,294 | 129,255 | 55.40 | 0 hrs 26 mins |
| 2 | GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB] |
Nvidia | GA102 | 5,591,201 | 120,765 | 46.30 | 0 hrs 31 mins |
| 3 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,004,065 | 115,922 | 43.17 | 0 hrs 33 mins |
| 4 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 4,311,914 | 109,794 | 39.27 | 0 hrs 37 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,138,082 | 109,898 | 37.65 | 0 hrs 38 mins |
| 6 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,204,411 | 100,376 | 31.92 | 0 hrs 45 mins |
| 7 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,066,160 | 98,216 | 31.22 | 0 hrs 46 mins |
| 8 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,881,548 | 96,763 | 29.78 | 0 hrs 48 mins |
| 9 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,798,254 | 95,877 | 29.19 | 0 hrs 49 mins |
| 10 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,643,452 | 93,916 | 28.15 | 0 hrs 51 mins |
| 11 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,404,592 | 87,952 | 27.34 | 0 hrs 53 mins |
| 12 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,357,931 | 91,031 | 25.90 | 0 hrs 56 mins |
| 13 | GeForce RTX 2080 SUPER Mobile / Max-Q TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q] |
Nvidia | TU104M | 2,290,922 | 90,152 | 25.41 | 0 hrs 57 mins |
| 14 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 2,154,545 | 87,669 | 24.58 | 0 hrs 59 mins |
| 15 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,105,051 | 87,497 | 24.06 | 0 hrs 60 mins |
| 16 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,923,340 | 81,757 | 23.53 | 1 hrs 1 mins |
| 17 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,859,122 | 84,184 | 22.08 | 1 hrs 5 mins |
| 18 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,792,865 | 83,017 | 21.60 | 1 hrs 7 mins |
| 19 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 1,542,723 | 77,828 | 19.82 | 1 hrs 13 mins |
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| 20 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,390,629 | 76,695 | 18.13 | 1 hrs 19 mins |
| 21 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,262,451 | 74,658 | 16.91 | 1 hrs 25 mins |
| 22 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 1,166,126 | 72,335 | 16.12 | 1 hrs 29 mins |
| 23 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,058,855 | 69,641 | 15.20 | 1 hrs 35 mins |
| 24 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,022,180 | 65,016 | 15.72 | 1 hrs 32 mins |
| 25 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 927,531 | 67,063 | 13.83 | 1 hrs 44 mins |
| 26 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 830,282 | 64,372 | 12.90 | 1 hrs 52 mins |
| 27 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 790,682 | 63,204 | 12.51 | 1 hrs 55 mins |
| 28 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 556,015 | 56,353 | 9.87 | 2 hrs 26 mins |
| 29 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 534,453 | 53,035 | 10.08 | 2 hrs 23 mins |
| 30 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 522,764 | 55,179 | 9.47 | 2 hrs 32 mins |
| 31 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 511,068 | 55,131 | 9.27 | 2 hrs 35 mins |
| 32 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 500,290 | 52,484 | 9.53 | 2 hrs 31 mins |
| 33 | Radeon R9 200/300 Series Hawaii [Radeon R9 200/300 Series] |
AMD | Hawaii | 448,834 | 52,690 | 8.52 | 2 hrs 49 mins |
| 34 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 376,609 | 49,448 | 7.62 | 3 hrs 9 mins |
| 35 | Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series] |
AMD | Hawaii | 349,744 | 48,303 | 7.24 | 3 hrs 19 mins |
| 36 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 330,236 | 45,440 | 7.27 | 3 hrs 18 mins |
| 37 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 322,125 | 47,126 | 6.84 | 3 hrs 31 mins |
| 38 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 309,799 | 40,959 | 7.56 | 3 hrs 10 mins |
| 39 | Quadro M4000 GM204GL [Quadro M4000] |
Nvidia | GM204GL | 275,981 | 44,957 | 6.14 | 3 hrs 55 mins |
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| 40 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 228,771 | 41,834 | 5.47 | 4 hrs 23 mins |
| 41 | Radeon R9 280/HD 7900/8950 Tahiti PRO [Radeon R9 280/HD 7900/8950] |
AMD | Tahiti PRO | 220,257 | 41,009 | 5.37 | 4 hrs 28 mins |
| 42 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 206,803 | 40,668 | 5.09 | 4 hrs 43 mins |
| 43 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 146,901 | 33,384 | 4.40 | 5 hrs 27 mins |
| 44 | Radeon HD 7800 Pitcairn [Radeon HD 7800] |
AMD | Pitcairn | 116,599 | 33,586 | 3.47 | 6 hrs 55 mins |
| 45 | Radeon RX Vega M XL [Radeon RX Vega M XL] |
AMD | Vega | 116,134 | 33,530 | 3.46 | 6 hrs 56 mins |
| 46 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 114,867 | 33,419 | 3.44 | 6 hrs 59 mins |
| 47 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 111,532 | 33,106 | 3.37 | 7 hrs 7 mins |
| 48 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 110,772 | 32,807 | 3.38 | 7 hrs 6 mins |
| 49 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 108,814 | 32,241 | 3.38 | 7 hrs 7 mins |
| 50 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 105,849 | 31,587 | 3.35 | 7 hrs 10 mins |
| 51 | GeForce GTX 960M GM107 [GeForce GTX 960M] 1439 |
Nvidia | GM107 | 101,981 | 31,008 | 3.29 | 7 hrs 18 mins |
| 52 | Radeon RX 460 Baffin XT [Radeon RX 460] |
AMD | Baffin XT | 99,932 | 31,972 | 3.13 | 7 hrs 41 mins |
| 53 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 87,671 | 30,472 | 2.88 | 8 hrs 21 mins |
| 54 | GTX 650 Ti Boost GK106 [GTX 650 Ti Boost] |
Nvidia | GK106 | 78,261 | 29,490 | 2.65 | 9 hrs 3 mins |
| 55 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 75,522 | 29,065 | 2.60 | 9 hrs 14 mins |
| 56 | Radeon R7/R6 360 Series Bonaire [Radeon R7/R6 360 Series] |
AMD | Bonaire | 48,070 | 22,588 | 2.13 | 11 hrs 17 mins |
| 57 | Radeon R7 250/HD 7700 R575A [Radeon R7 250/HD 7700] |
AMD | R575A | 31,029 | 21,655 | 1.43 | 16 hrs 45 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:36:28|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|