RESEARCH: CANCER
FOLDING PROJECT #17738 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 49,809Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project explores how proteins use ion gradients to move molecules across cell membranes. These 'secondary active transporters' are found everywhere and play a role in treating diseases like cancer and diabetes. By studying them, we can learn how different proteins work together.
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 transporter
Proteins that use ions to transport molecules across cell membranes.
Secondary active transporters are a type of protein found in all living organisms. They play a crucial role in moving various molecules across cell membranes by utilizing an existing ion gradient. This process is essential for many cellular functions, including nutrient uptake, waste removal, and signal transduction. These transporters are also important 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 refers to the unequal distribution of charged particles (ions) across a cell membrane. This difference in concentration creates an electrochemical potential that can be used by cells to power various processes, such as nerve impulse transmission and nutrient uptake.
cell membrane
The outer boundary of a cell that separates its internal environment from the outside.
The cell membrane is a thin, flexible barrier that surrounds every cell. It plays a crucial role in regulating what enters and exits the cell, maintaining its shape, and communicating with other cells.
proteins
Large, complex molecules that perform a wide variety of functions in living organisms.
Proteins are the workhorses of cells, carrying out essential tasks such as building and repairing tissues, transporting molecules, catalyzing chemical reactions, and defending against disease.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:36:16|
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 | 6,121,745 | 84,273 | 72.64 | 0 hrs 20 mins |
| 2 | GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB] |
Nvidia | GA102 | 5,164,996 | 80,305 | 64.32 | 0 hrs 22 mins |
| 3 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,479,183 | 75,207 | 59.56 | 0 hrs 24 mins |
| 4 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 4,020,506 | 73,465 | 54.73 | 0 hrs 26 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 3,740,158 | 72,439 | 51.63 | 0 hrs 28 mins |
| 6 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,042,680 | 67,564 | 45.03 | 0 hrs 32 mins |
| 7 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,963,503 | 66,644 | 44.47 | 0 hrs 32 mins |
| 8 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,920,782 | 67,037 | 43.57 | 0 hrs 33 mins |
| 9 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,847,011 | 66,026 | 43.12 | 0 hrs 33 mins |
| 10 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,629,238 | 63,384 | 41.48 | 0 hrs 35 mins |
| 11 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,352,678 | 62,094 | 37.89 | 0 hrs 38 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,314,877 | 61,254 | 37.79 | 0 hrs 38 mins |
| 13 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,308,500 | 61,847 | 37.33 | 0 hrs 39 mins |
| 14 | GeForce RTX 2080 SUPER Mobile / Max-Q TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q] |
Nvidia | TU104M | 2,129,789 | 59,847 | 35.59 | 0 hrs 40 mins |
| 15 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 1,985,971 | 58,724 | 33.82 | 0 hrs 43 mins |
| 16 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,980,572 | 58,664 | 33.76 | 0 hrs 43 mins |
| 17 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,925,750 | 57,705 | 33.37 | 0 hrs 43 mins |
| 18 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,818,201 | 59,122 | 30.75 | 0 hrs 47 mins |
| 19 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,711,634 | 55,480 | 30.85 | 0 hrs 47 mins |
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| 20 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,354,333 | 51,893 | 26.10 | 0 hrs 55 mins |
| 21 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,345,426 | 51,583 | 26.08 | 0 hrs 55 mins |
| 22 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 1,156,810 | 49,539 | 23.35 | 1 hrs 2 mins |
| 23 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,156,807 | 49,196 | 23.51 | 1 hrs 1 mins |
| 24 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,081,303 | 48,143 | 22.46 | 1 hrs 4 mins |
| 25 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 939,259 | 46,160 | 20.35 | 1 hrs 11 mins |
| 26 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 726,346 | 42,149 | 17.23 | 1 hrs 24 mins |
| 27 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 690,541 | 41,395 | 16.68 | 1 hrs 26 mins |
| 28 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 683,446 | 41,393 | 16.51 | 1 hrs 27 mins |
| 29 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 573,552 | 39,166 | 14.64 | 1 hrs 38 mins |
| 30 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 456,737 | 35,947 | 12.71 | 1 hrs 53 mins |
| 31 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 440,479 | 35,780 | 12.31 | 1 hrs 57 mins |
| 32 | GeForce GTX 1650 Ti Mobile TU117M [GeForce GTX 1650 Ti Mobile] |
Nvidia | TU117M | 415,070 | 35,131 | 11.81 | 2 hrs 2 mins |
| 33 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 370,626 | 33,618 | 11.02 | 2 hrs 11 mins |
| 34 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 370,239 | 34,056 | 10.87 | 2 hrs 12 mins |
| 35 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 290,503 | 31,264 | 9.29 | 2 hrs 35 mins |
| 36 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 209,597 | 27,816 | 7.54 | 3 hrs 11 mins |
| 37 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 189,703 | 26,467 | 7.17 | 3 hrs 21 mins |
| 38 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 170,366 | 26,140 | 6.52 | 3 hrs 41 mins |
| 39 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 150,594 | 25,076 | 6.01 | 3 hrs 60 mins |
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|||||||
| 40 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 120,961 | 23,301 | 5.19 | 4 hrs 37 mins |
| 41 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 110,066 | 22,574 | 4.88 | 4 hrs 55 mins |
| 42 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 106,713 | 22,335 | 4.78 | 5 hrs 1 mins |
| 43 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 105,086 | 21,251 | 4.94 | 4 hrs 51 mins |
| 44 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 83,450 | 20,589 | 4.05 | 5 hrs 55 mins |
| 45 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 73,243 | 19,716 | 3.71 | 6 hrs 28 mins |
| 46 | GTX 650 Ti Boost GK106 [GTX 650 Ti Boost] |
Nvidia | GK106 | 70,043 | 19,176 | 3.65 | 6 hrs 34 mins |
| 47 | GeForce MX110 GM108M [GeForce MX110] |
Nvidia | GM108M | 22,851 | 13,515 | 1.69 | 14 hrs 12 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:36:16|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|