RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17921 PROFILE
PROJECT TEAM
Manager(s): Austin WeigleInstitution: University of Illinois at Urbana-Champaign
Project URL: View Project Website
WORK UNIT INFO
Atoms: 65,919Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how sugar transporters in cells move different types of molecules, even those that don't seem related. Understanding this could help scientists design new drugs that specifically target certain transporters.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Membrane transporters are important for enabling molecules to go in and out of cells.
What is interesting is that while transporters typically have set functions, they can also transport molecules that do not necessarily relate to their function or cellular purpose.
For example, drugs often hijack transporters to enter cells without necessarily resembling the molecules or metabolites which that target transporter normally transports.
The goal of this project is to see how exactly a typical membrane transporter recognizes and transports molecules that look different from one another.
We choose a class of sugar transporters that transports a variety of different types of substrates to satisfy this goal.
Findings from this study can be generalized for the design of molecules (e.g., drugs) specific to a given transporter and its general mechanism.
RELATED TERMS GLOSSARY AI BETA
Membrane transporters
Proteins embedded in cell membranes that facilitate the movement of molecules across the membrane.
Membrane transporters are crucial proteins found within cell membranes. They act like gatekeepers, allowing specific molecules to enter and exit the cell. This process is essential for various cellular functions, including nutrient uptake, waste removal, and signal transduction.
Drugs
Substances used to treat, cure, or prevent diseases.
Drugs are chemical compounds designed to interact with biological systems and produce a desired effect. They can be used to treat various conditions, from infections to chronic illnesses, by targeting specific receptors or pathways in the body.
Molecules
Atoms or groups of atoms held together by chemical bonds.
Molecules are the building blocks of matter. They are formed when two or more atoms bond together. Molecules can be simple or complex, and they play essential roles in various biological and chemical processes.
Substrates
Substances that undergo a chemical reaction catalyzed by an enzyme.
Substrates are the molecules that enzymes act upon. Enzymes are proteins that speed up chemical reactions in living organisms. Substrates bind to the active site of an enzyme, where the chemical reaction takes place.
Transporters
Proteins that facilitate the movement of molecules across cell membranes.
Transporters are essential proteins found in cell membranes. They help move various molecules into and out of the cell, ensuring proper cellular function. Different types of transporters exist for specific molecules or groups of molecules.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:34:16|
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 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 14,225,966 | 335,949 | 42.35 | 0 hrs 34 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 13,049,862 | 336,075 | 38.83 | 0 hrs 37 mins |
| 3 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 10,030,325 | 306,724 | 32.70 | 0 hrs 44 mins |
| 4 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 7,131,745 | 273,384 | 26.09 | 0 hrs 55 mins |
| 5 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 7,062,494 | 273,889 | 25.79 | 0 hrs 56 mins |
| 6 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 7,002,452 | 272,215 | 25.72 | 0 hrs 56 mins |
| 7 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 6,035,646 | 259,659 | 23.24 | 1 hrs 2 mins |
| 8 | GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB] |
Nvidia | GA102 | 5,959,587 | 253,769 | 23.48 | 1 hrs 1 mins |
| 9 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,137,811 | 247,317 | 20.77 | 1 hrs 9 mins |
| 10 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,927,099 | 243,061 | 20.27 | 1 hrs 11 mins |
| 11 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,789,642 | 241,781 | 19.81 | 1 hrs 13 mins |
| 12 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,283,374 | 231,868 | 18.47 | 1 hrs 18 mins |
| 13 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,870,534 | 222,487 | 17.40 | 1 hrs 23 mins |
| 14 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 3,249,817 | 212,494 | 15.29 | 1 hrs 34 mins |
| 15 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,126,564 | 207,912 | 15.04 | 1 hrs 36 mins |
| 16 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 3,064,925 | 206,830 | 14.82 | 1 hrs 37 mins |
| 17 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,047,829 | 206,438 | 14.76 | 1 hrs 38 mins |
| 18 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,948,136 | 204,098 | 14.44 | 1 hrs 40 mins |
| 19 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 2,855,883 | 203,368 | 14.04 | 1 hrs 43 mins |
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|||||||
| 20 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,542,634 | 194,885 | 13.05 | 1 hrs 50 mins |
| 21 | Radeon RX 7900XT/XTX Navi 31 [Radeon RX 7900XT/XTX] |
AMD | Navi 31 | 2,495,990 | 193,586 | 12.89 | 1 hrs 52 mins |
| 22 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,453,022 | 192,426 | 12.75 | 1 hrs 53 mins |
| 23 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,440,227 | 192,371 | 12.69 | 1 hrs 54 mins |
| 24 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,217,499 | 186,937 | 11.86 | 2 hrs 1 mins |
| 25 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,105,009 | 182,314 | 11.55 | 2 hrs 5 mins |
| 26 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,977,343 | 179,071 | 11.04 | 2 hrs 10 mins |
| 27 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 1,929,517 | 176,171 | 10.95 | 2 hrs 11 mins |
| 28 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,814,413 | 173,654 | 10.45 | 2 hrs 18 mins |
| 29 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,643,023 | 165,292 | 9.94 | 2 hrs 25 mins |
| 30 | Geforce RTX 3070 Ti Laptop GPU GA104 [Geforce RTX 3070 Ti Laptop GPU] |
Nvidia | GA104 | 1,438,561 | 160,557 | 8.96 | 2 hrs 41 mins |
| 31 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,398,080 | 159,713 | 8.75 | 2 hrs 45 mins |
| 32 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 1,344,480 | 154,226 | 8.72 | 2 hrs 45 mins |
| 33 | Radeon VII Vega 20 [Radeon VII] |
AMD | Vega 20 | 1,323,509 | 153,849 | 8.60 | 2 hrs 47 mins |
| 34 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,323,502 | 157,192 | 8.42 | 2 hrs 51 mins |
| 35 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 1,302,771 | 156,166 | 8.34 | 2 hrs 53 mins |
| 36 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,207,364 | 152,612 | 7.91 | 3 hrs 2 mins |
| 37 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,165,108 | 149,635 | 7.79 | 3 hrs 5 mins |
| 38 | Radeon RX 6650XT Navi 23 [Radeon RX 6650XT] |
AMD | Navi 23 | 1,077,392 | 147,251 | 7.32 | 3 hrs 17 mins |
| 39 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,017,819 | 134,663 | 7.56 | 3 hrs 11 mins |
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| 40 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 801,979 | 132,364 | 6.06 | 3 hrs 58 mins |
| 41 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 618,137 | 127,248 | 4.86 | 4 hrs 56 mins |
| 42 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 539,234 | 120,714 | 4.47 | 5 hrs 22 mins |
| 43 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 257,674 | 90,955 | 2.83 | 8 hrs 28 mins |
| 44 | Tesla K40m GK110 [Tesla K40m] 5046 |
Nvidia | GK110 | 231,793 | 93,033 | 2.49 | 9 hrs 38 mins |
| 45 | GeForce MX450 TU117M [GeForce MX450] |
Nvidia | TU117M | 207,229 | 81,105 | 2.56 | 9 hrs 24 mins |
| 46 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 187,327 | 82,427 | 2.27 | 10 hrs 34 mins |
| 47 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 187,245 | 81,420 | 2.30 | 10 hrs 26 mins |
| 48 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 133,880 | 73,201 | 1.83 | 13 hrs 7 mins |
| 49 | Radeon RX 460/560D Baffin [Radeon RX 460/560D] |
AMD | Baffin | 76,292 | 66,351 | 1.15 | 20 hrs 52 mins |
| 50 | RX 5500/5500M/Pro 5500M Navi 14 [RX 5500/5500M/Pro 5500M] |
AMD | Navi 14 | 59,914 | 44,485 | 1.35 | 17 hrs 49 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:34:16|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|