RESEARCH: CANCER
FOLDING PROJECT #17736 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 106,183Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how proteins use ions to move molecules across cell membranes. These proteins are important for many bodily functions and are also drug targets for diseases like cancer and diabetes. By studying them, we can learn more about how cells work.
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 a crucial type of protein found in all living organisms. They utilize the energy stored in ion gradients to move various molecules across cell membranes. This process is essential for many cellular functions, including nutrient uptake, waste removal, and signal transduction. Due to their importance in various biological processes, secondary active transporters have become attractive targets for drug development to treat diseases like cancer, diabetes, and neurological disorders.
Membrane transporters
Proteins that move molecules across cell membranes.
Membrane transporters are essential proteins embedded within the cell membrane. They facilitate the movement of various substances, such as nutrients, ions, and waste products, across the membrane barrier. This selective transport is crucial for maintaining cellular homeostasis, regulating signaling pathways, and enabling cells to interact with their environment.
Ion gradient
A difference in ion concentration across a membrane.
An ion gradient refers to the unequal distribution of ions (charged atoms) across a cell membrane. This concentration difference creates an electrochemical potential that drives various cellular processes. Ion gradients are essential for nerve impulse transmission, muscle contraction, and nutrient uptake.
Drug targets
Molecules or pathways that are altered to treat diseases.
Drug targets are specific biological molecules or cellular processes that are involved in the development or progression of a disease. By targeting these specific pathways, pharmaceutical drugs can aim to modulate their activity and alleviate disease symptoms. Identifying effective drug targets is a crucial step in the drug discovery process.
Cancer
A disease characterized by uncontrolled cell growth.
Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. This uncontrolled proliferation arises from genetic mutations that disrupt normal cellular processes, leading to tumor formation and potentially life-threatening complications.
Diabetes
A metabolic disorder characterized by high blood sugar levels.
Diabetes is a chronic condition affecting how the body regulates blood sugar. It occurs when the pancreas does not produce enough insulin or when the body becomes resistant to insulin's effects. This leads to elevated glucose levels in the bloodstream, potentially damaging organs and tissues over time.
Neurological disorders
Conditions affecting the nervous system.
Neurological disorders encompass a wide range of conditions that affect the brain, spinal cord, and peripheral nerves. These disorders can manifest in various ways, including cognitive impairment, movement problems, sensory disturbances, and emotional changes. Examples include Alzheimer's disease, Parkinson's disease, and multiple sclerosis.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:36:19|
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 | 7,243,647 | 119,109 | 60.82 | 0 hrs 24 mins |
| 2 | GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB] |
Nvidia | GA102 | 5,666,956 | 109,402 | 51.80 | 0 hrs 28 mins |
| 3 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,824,547 | 105,198 | 45.86 | 0 hrs 31 mins |
| 4 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,416,250 | 102,228 | 43.20 | 0 hrs 33 mins |
| 5 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 4,092,758 | 95,904 | 42.68 | 0 hrs 34 mins |
| 6 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 3,135,047 | 91,537 | 34.25 | 0 hrs 42 mins |
| 7 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,071,335 | 90,585 | 33.91 | 0 hrs 42 mins |
| 8 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,056,587 | 90,585 | 33.74 | 0 hrs 43 mins |
| 9 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,910,563 | 88,379 | 32.93 | 0 hrs 44 mins |
| 10 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,697,221 | 87,005 | 31.00 | 0 hrs 46 mins |
| 11 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 2,500,084 | 50,658 | 49.35 | 0 hrs 29 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,348,573 | 80,545 | 29.16 | 0 hrs 49 mins |
| 13 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,309,376 | 82,905 | 27.86 | 0 hrs 52 mins |
| 14 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,107,972 | 80,462 | 26.20 | 0 hrs 55 mins |
| 15 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,072,560 | 79,666 | 26.02 | 0 hrs 55 mins |
| 16 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 1,820,116 | 75,286 | 24.18 | 0 hrs 60 mins |
| 17 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,759,415 | 75,798 | 23.21 | 1 hrs 2 mins |
| 18 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 1,750,113 | 75,224 | 23.27 | 1 hrs 2 mins |
| 19 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,503,647 | 71,295 | 21.09 | 1 hrs 8 mins |
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|||||||
| 20 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,338,428 | 68,880 | 19.43 | 1 hrs 14 mins |
| 21 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,282,569 | 56,229 | 22.81 | 1 hrs 3 mins |
| 22 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,103,927 | 65,131 | 16.95 | 1 hrs 25 mins |
| 23 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,074,648 | 64,234 | 16.73 | 1 hrs 26 mins |
| 24 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 1,055,072 | 64,721 | 16.30 | 1 hrs 28 mins |
| 25 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 985,766 | 59,761 | 16.50 | 1 hrs 27 mins |
| 26 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 959,375 | 61,806 | 15.52 | 1 hrs 33 mins |
| 27 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 903,800 | 60,735 | 14.88 | 1 hrs 37 mins |
| 28 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 806,539 | 58,627 | 13.76 | 1 hrs 45 mins |
| 29 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 609,908 | 53,294 | 11.44 | 2 hrs 6 mins |
| 30 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 578,880 | 48,621 | 11.91 | 2 hrs 1 mins |
| 31 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 545,827 | 48,243 | 11.31 | 2 hrs 7 mins |
| 32 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 506,254 | 48,633 | 10.41 | 2 hrs 18 mins |
| 33 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 503,635 | 50,046 | 10.06 | 2 hrs 23 mins |
| 34 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 486,876 | 49,524 | 9.83 | 2 hrs 26 mins |
| 35 | Quadro T2000 Mobile / Max-Q TU117GLM [Quadro T2000 Mobile / Max-Q] |
Nvidia | TU117GLM | 452,273 | 48,516 | 9.32 | 2 hrs 34 mins |
| 36 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 417,534 | 45,463 | 9.18 | 2 hrs 37 mins |
| 37 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 415,580 | 47,050 | 8.83 | 2 hrs 43 mins |
| 38 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 402,679 | 45,754 | 8.80 | 2 hrs 44 mins |
| 39 | Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series] |
AMD | Hawaii | 329,669 | 43,417 | 7.59 | 3 hrs 10 mins |
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|
|||||||
| 40 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 279,467 | 41,350 | 6.76 | 3 hrs 33 mins |
| 41 | Radeon R9 200/300 Series Hawaii [Radeon R9 200/300 Series] |
AMD | Hawaii | 278,051 | 35,138 | 7.91 | 3 hrs 2 mins |
| 42 | Radeon Vega Frontier Edition Vega 10 XTX [Radeon Vega Frontier Edition] |
AMD | Vega 10 XTX | 270,394 | 40,706 | 6.64 | 3 hrs 37 mins |
| 43 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 221,309 | 38,194 | 5.79 | 4 hrs 9 mins |
| 44 | Radeon R9 280/HD 7900/8950 Tahiti PRO [Radeon R9 280/HD 7900/8950] |
AMD | Tahiti PRO | 220,362 | 37,496 | 5.88 | 4 hrs 5 mins |
| 45 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 209,041 | 37,363 | 5.59 | 4 hrs 17 mins |
| 46 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 154,601 | 33,067 | 4.68 | 5 hrs 8 mins |
| 47 | Radeon RX Vega M XL [Radeon RX Vega M XL] |
AMD | Vega | 126,000 | 31,504 | 4.00 | 6 hrs 0 mins |
| 48 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 111,399 | 30,283 | 3.68 | 6 hrs 31 mins |
| 49 | Radeon Rx 270/370 Curacao Pro [Radeon Rx 270/370] |
AMD | Curacao Pro | 91,267 | 27,130 | 3.36 | 7 hrs 8 mins |
| 50 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 89,150 | 28,149 | 3.17 | 7 hrs 35 mins |
| 51 | GTX 650 Ti Boost GK106 [GTX 650 Ti Boost] |
Nvidia | GK106 | 61,056 | 22,235 | 2.75 | 8 hrs 44 mins |
| 52 | Radeon RX Vega gfx902 raven [Radeon RX Vega gfx902] |
AMD | raven | 29,391 | 19,526 | 1.51 | 15 hrs 57 mins |
| 53 | Radeon R7 250/HD 7700 R575A [Radeon R7 250/HD 7700] |
AMD | R575A | 28,336 | 19,422 | 1.46 | 16 hrs 27 mins |
| 54 | Ryzen 4900HS mobile Renoir [Ryzen 4900HS mobile] |
AMD | Renoir | 23,217 | 17,722 | 1.31 | 18 hrs 19 mins |
| 55 | Radeon APU A4-6000 R2 Mullins [Radeon APU A4-6000 R2] |
AMD | Mullins | 2,716 | 10,620 | 0.26 | 93 hrs 51 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:36:19|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|