RESEARCH: PARKINSONS
FOLDING PROJECT #17704 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 65,672Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how changes to a protein called the serotonin transporter affect brain function. Serotonin is important for mood, sleep, and other things, and problems with this transporter are linked to mental health issues like depression. By studying these changes, scientists hope to find better ways to treat these disorders.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
The 17000-17710 project series contains simulations of the serotonin transporter, the protein responsible for terminating neurotransmission in neurons.
The neurotransmitter serotonin regulates various functions in the body such as mood, behavior, appettite, and sleep, and is a major drug targets for antidepressants.
Malfunctions in the serotonin transporter have been assoicated with mental disorders including depression and Parkinson's.
Our goal in performing these simulations is to understand how mutations affect the structure and dynamics of the serotonin transporter and provide insights to treat psychatric disorders assoicated with these mutations.
RELATED TERMS GLOSSARY AI BETA
serotonin transporter
A protein that moves serotonin across neuronal membranes.
The serotonin transporter is a crucial protein responsible for regulating the levels of serotonin in the brain. It transports serotonin from the synapse back into the neuron, effectively stopping its signaling. This process is essential for mood regulation, sleep, appetite, and other functions.
neurotransmitter
A chemical messenger that transmits signals between neurons.
Neurotransmitters are the brain's chemical messengers. They allow communication between nerve cells (neurons), transmitting signals across tiny gaps called synapses. Examples include serotonin, dopamine, and acetylcholine.
mutation
A permanent change in the DNA sequence.
Mutations are alterations in the genetic code (DNA). They can arise spontaneously or be induced by environmental factors. While some mutations are harmless, others can lead to diseases or changes in an organism's traits.
psychatric disorders
Mental health conditions that affect mood, thinking, and behavior.
Psychiatric disorders are a broad category of mental illnesses that encompass various conditions affecting emotional well-being, thought processes, and behavior. Examples include depression, anxiety disorders, bipolar disorder, and schizophrenia.
antidepressants
Medications used to treat depression and other mood disorders.
Antidepressants are a class of medications primarily used to alleviate symptoms of depression. They work by affecting the balance of neurotransmitters in the brain, particularly serotonin and norepinephrine.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:37:08|
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 | 5,915,233 | 156,480 | 37.80 | 0 hrs 38 mins |
| 2 | GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB] |
Nvidia | GA102 | 4,273,787 | 136,048 | 31.41 | 0 hrs 46 mins |
| 3 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,152,671 | 138,855 | 29.91 | 0 hrs 48 mins |
| 4 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,235,388 | 125,616 | 25.76 | 0 hrs 56 mins |
| 5 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,099,258 | 126,815 | 24.44 | 0 hrs 59 mins |
| 6 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,789,626 | 122,692 | 22.74 | 1 hrs 3 mins |
| 7 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 2,762,777 | 121,785 | 22.69 | 1 hrs 3 mins |
| 8 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,688,930 | 118,997 | 22.60 | 1 hrs 4 mins |
| 9 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 2,533,001 | 117,257 | 21.60 | 1 hrs 7 mins |
| 10 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,329,641 | 114,910 | 20.27 | 1 hrs 11 mins |
| 11 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,150,240 | 110,788 | 19.41 | 1 hrs 14 mins |
| 12 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,791,455 | 104,291 | 17.18 | 1 hrs 24 mins |
| 13 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,718,434 | 104,154 | 16.50 | 1 hrs 27 mins |
| 14 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,642,718 | 102,669 | 16.00 | 1 hrs 30 mins |
| 15 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,540,708 | 99,088 | 15.55 | 1 hrs 33 mins |
| 16 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,446,513 | 98,449 | 14.69 | 1 hrs 38 mins |
| 17 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,395,740 | 94,654 | 14.75 | 1 hrs 38 mins |
| 18 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,388,295 | 92,847 | 14.95 | 1 hrs 36 mins |
| 19 | Radeon VII Vega 20 [Radeon VII] 13,284 |
AMD | Vega 20 | 1,203,176 | 92,174 | 13.05 | 1 hrs 50 mins |
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| 20 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,045,388 | 88,152 | 11.86 | 2 hrs 1 mins |
| 21 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,033,047 | 83,293 | 12.40 | 1 hrs 56 mins |
| 22 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 977,477 | 84,590 | 11.56 | 2 hrs 5 mins |
| 23 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 972,565 | 86,157 | 11.29 | 2 hrs 8 mins |
| 24 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 875,347 | 83,054 | 10.54 | 2 hrs 17 mins |
| 25 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 867,509 | 82,364 | 10.53 | 2 hrs 17 mins |
| 26 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 834,698 | 80,967 | 10.31 | 2 hrs 20 mins |
| 27 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 679,254 | 76,479 | 8.88 | 2 hrs 42 mins |
| 28 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 610,113 | 73,582 | 8.29 | 2 hrs 54 mins |
| 29 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 523,267 | 70,186 | 7.46 | 3 hrs 13 mins |
| 30 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 438,684 | 66,122 | 6.63 | 3 hrs 37 mins |
| 31 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 434,762 | 66,133 | 6.57 | 3 hrs 39 mins |
| 32 | Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series] |
AMD | Hawaii | 311,411 | 58,823 | 5.29 | 4 hrs 32 mins |
| 33 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 235,746 | 53,674 | 4.39 | 5 hrs 28 mins |
| 34 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 190,015 | 50,168 | 3.79 | 6 hrs 20 mins |
| 35 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 187,325 | 50,091 | 3.74 | 6 hrs 25 mins |
| 36 | Radeon R9 200/300 Series Tonga [Radeon R9 200/300 Series] |
AMD | Tonga | 167,078 | 48,169 | 3.47 | 6 hrs 55 mins |
| 37 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 140,411 | 45,353 | 3.10 | 7 hrs 45 mins |
| 38 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 134,466 | 44,689 | 3.01 | 7 hrs 59 mins |
| 39 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 115,345 | 42,482 | 2.72 | 8 hrs 50 mins |
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| 40 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 97,901 | 40,168 | 2.44 | 9 hrs 51 mins |
| 41 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 78,030 | 37,253 | 2.09 | 11 hrs 27 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:37:08|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|