RESEARCH: PARKINSONS
FOLDING PROJECT #17914 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 93,414Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project uses computer simulations to study the serotonin transporter protein. Serotonin affects mood, sleep, and other important functions. Problems with this transporter can lead to mental health issues like depression. The goal is to understand how changes in the protein affect its work and find new ways to treat these disorders.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
These projects 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 reabsorbs serotonin in the brain.
The serotonin transporter is a crucial protein found in neurons. It's responsible for removing serotonin from the spaces between nerve cells (synapses), effectively stopping the signal transmission. This process is essential for regulating mood, sleep, appetite, and other functions. Disruptions in this transporter can contribute to mental health disorders like depression.
neurotransmitter
A chemical messenger that transmits signals between neurons.
Neurotransmitters are the chemicals that allow nerve cells to communicate with each other. They carry signals across tiny gaps (synapses) between neurons, influencing various bodily functions like mood, movement, and thought.
serotonin
A neurotransmitter that regulates mood, sleep, and appetite.
Serotonin is a key neurotransmitter involved in regulating mood, sleep patterns, appetite, and other important functions. An imbalance in serotonin levels can contribute to mental health conditions like depression.
antidepressants
Medications that treat depression and other mood disorders.
Antidepressants are medications designed to alleviate symptoms of depression, anxiety, and other mental health conditions. They work by affecting the levels and activity of neurotransmitters like serotonin in the brain.
mutations
Changes in the DNA sequence.
Mutations are alterations in the genetic code (DNA). These changes can affect how genes function and may lead to various health conditions.
Parkinson's
A progressive neurodegenerative disorder.
Parkinson's disease is a neurological condition characterized by tremors, stiffness, slow movements, and balance problems. It occurs due to the loss of dopamine-producing cells in the brain.
psychatric disorders
Mental illnesses that affect mood, thinking, and behavior.
Psychiatric disorders are a range of mental health conditions affecting a person's thoughts, feelings, and behaviors. These can include depression, anxiety disorders, schizophrenia, and bipolar disorder.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:34:26|
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 | 8,525,501 | 360,297 | 23.66 | 1 hrs 1 mins |
| 2 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 7,318,150 | 343,227 | 21.32 | 1 hrs 8 mins |
| 3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,949,065 | 336,887 | 20.63 | 1 hrs 10 mins |
| 4 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,494,580 | 291,965 | 15.39 | 1 hrs 34 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,421,376 | 290,758 | 15.21 | 1 hrs 35 mins |
| 6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,325,877 | 286,939 | 15.08 | 1 hrs 36 mins |
| 7 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,195,311 | 284,720 | 14.73 | 1 hrs 38 mins |
| 8 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,028,075 | 263,353 | 15.30 | 1 hrs 34 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,779,931 | 262,816 | 14.38 | 1 hrs 40 mins |
| 10 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,158,606 | 259,915 | 12.15 | 1 hrs 58 mins |
| 11 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,107,997 | 257,538 | 12.07 | 1 hrs 59 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,081,634 | 227,570 | 9.15 | 2 hrs 37 mins |
| 13 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,056,139 | 224,956 | 9.14 | 2 hrs 38 mins |
| 14 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,002,312 | 220,185 | 9.09 | 2 hrs 38 mins |
| 15 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,964,694 | 218,826 | 8.98 | 2 hrs 40 mins |
| 16 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,654,291 | 208,505 | 7.93 | 3 hrs 1 mins |
| 17 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,529,445 | 206,755 | 7.40 | 3 hrs 15 mins |
| 18 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,423,409 | 200,781 | 7.09 | 3 hrs 23 mins |
| 19 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,107,869 | 183,280 | 6.04 | 3 hrs 58 mins |
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| 20 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,099,061 | 181,581 | 6.05 | 3 hrs 58 mins |
| 21 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 918,570 | 120,743 | 7.61 | 3 hrs 9 mins |
| 22 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 913,741 | 171,320 | 5.33 | 4 hrs 30 mins |
| 23 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 910,424 | 171,866 | 5.30 | 4 hrs 32 mins |
| 24 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 807,592 | 167,227 | 4.83 | 4 hrs 58 mins |
| 25 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 585,827 | 147,723 | 3.97 | 6 hrs 3 mins |
| 26 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 489,300 | 139,315 | 3.51 | 6 hrs 50 mins |
| 27 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 258,912 | 112,820 | 2.29 | 10 hrs 27 mins |
| 28 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 203,701 | 104,085 | 1.96 | 12 hrs 16 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:34:26|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|