RESEARCH: CANCER
FOLDING PROJECT #17778 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 103,413Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how proteins use energy from ions to move molecules across cell membranes. These proteins are found everywhere and help with important things like fighting disease. Studying them can teach us about how different proteins work together.
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 transporter
Proteins that use ion gradients to transport molecules across cell membranes.
Secondary active transporters are essential proteins found in all living organisms. They leverage the energy stored in an ion gradient to move other molecules across cell membranes. This process is crucial for various cellular functions, including nutrient uptake, waste removal, and signal transduction. These transporters are often targets for drugs used to treat diseases such as cancer, diabetes, and neurological disorders.
Ion gradient
A difference in concentration of ions across a membrane.
An ion gradient refers to the uneven distribution of charged particles (ions) across a cell membrane. This concentration difference creates an electrochemical potential that drives various cellular processes, including secondary active transport. The movement of ions down their concentration gradient generates energy used by transporters to move molecules against their concentration gradient.
Molecules
The basic units of matter.
Molecules are formed when two or more atoms bond together. They are the fundamental building blocks of all matter, including living organisms. In biology, molecules play crucial roles in various cellular processes, such as DNA replication, protein synthesis, and energy production.
Cell membrane
A thin layer that surrounds a cell.
The cell membrane is a selectively permeable barrier that encloses the contents of a cell. It regulates the passage of molecules in and out of the cell, maintaining cellular homeostasis. Composed primarily of phospholipids and proteins, the cell membrane plays a vital role in cell signaling, nutrient uptake, and waste removal.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:35:31|
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 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 7,209,481 | 175,230 | 41.14 | 0 hrs 35 mins |
| 2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 6,952,383 | 171,496 | 40.54 | 0 hrs 36 mins |
| 3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,249,744 | 166,799 | 37.47 | 0 hrs 38 mins |
| 4 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,459,453 | 149,197 | 29.89 | 0 hrs 48 mins |
| 5 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,850,775 | 142,386 | 27.04 | 0 hrs 53 mins |
| 6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,447,228 | 136,409 | 25.27 | 0 hrs 57 mins |
| 7 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,178,165 | 129,803 | 24.48 | 0 hrs 59 mins |
| 8 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,125,642 | 133,852 | 23.35 | 1 hrs 2 mins |
| 9 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,096,734 | 132,881 | 23.30 | 1 hrs 2 mins |
| 10 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,518,597 | 123,868 | 20.33 | 1 hrs 11 mins |
| 11 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,444,325 | 121,650 | 20.09 | 1 hrs 12 mins |
| 12 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,825,680 | 111,276 | 16.41 | 1 hrs 28 mins |
| 13 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,807,813 | 110,186 | 16.41 | 1 hrs 28 mins |
| 14 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,470,118 | 103,793 | 14.16 | 1 hrs 42 mins |
| 15 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,431,194 | 103,246 | 13.86 | 1 hrs 44 mins |
| 16 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,017,436 | 90,647 | 11.22 | 2 hrs 8 mins |
| 17 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 863,706 | 85,094 | 10.15 | 2 hrs 22 mins |
| 18 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 811,833 | 85,505 | 9.49 | 2 hrs 32 mins |
| 19 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 677,037 | 78,319 | 8.64 | 2 hrs 47 mins |
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| 20 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 551,630 | 74,911 | 7.36 | 3 hrs 16 mins |
| 21 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 412,722 | 67,670 | 6.10 | 3 hrs 56 mins |
| 22 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 357,205 | 64,953 | 5.50 | 4 hrs 22 mins |
| 23 | Radeon RX 6600/6600 XT/6600M Navi 23 [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 | 287,863 | 60,237 | 4.78 | 5 hrs 1 mins |
| 24 | Radeon RX 460 Baffin XT [Radeon RX 460] |
AMD | Baffin XT | 129,744 | 46,166 | 2.81 | 8 hrs 32 mins |
| 25 | Radeon RX 6400 / 6500 XT Navi 24 [Radeon RX 6400 / 6500 XT] |
AMD | Navi 24 | 125,514 | 45,682 | 2.75 | 8 hrs 44 mins |
| 26 | Radeon HD 7800 Series Pitcairn PRO [Radeon HD 7800 Series] |
AMD | Pitcairn PRO | 91,300 | 41,278 | 2.21 | 10 hrs 51 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:35:31|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|