RESEARCH: PARKINSONS
FOLDING PROJECT #17915 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 107,425Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project uses computer simulations to study the serotonin transporter, a protein that affects mood and behavior. By looking at how changes in the transporter's structure affect its function, researchers hope to better understand mental disorders like depression and Parkinson's disease, and develop new treatments.
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 removes serotonin from the synapse.
The serotonin transporter is a crucial protein in the brain. It moves serotonin out of the spaces between neurons (synapses), effectively stopping its action and regulating mood, behavior, appetite, and sleep. Disruptions in this transporter can contribute to mental health conditions like depression and Parkinson's disease.
neurotransmission
The process of transmitting signals between neurons.
Neurotransmission is how our brain communicates. It involves the release of chemical messengers called neurotransmitters from one neuron (sender) across a tiny gap (synapse) to another neuron (receiver). This allows for complex information processing and control of bodily functions.
serotonin
A neurotransmitter that regulates mood, sleep, appetite, and other functions.
Serotonin is a chemical messenger in the brain. It plays a vital role in regulating mood, happiness, sleep, appetite, and even digestion. Low levels of serotonin are linked to depression and anxiety, while medications like antidepressants often work by increasing serotonin activity.
antidepressants
Medications that treat depression and other mood disorders.
Antidepressants are a class of drugs used to treat depression, anxiety, and other mental health conditions. They work by affecting the balance of certain chemicals in the brain, such as serotonin, norepinephrine, and dopamine. Common types include selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants.
Parkinson's
A neurodegenerative disorder that affects movement.
Parkinson's disease is a progressive brain disorder that causes tremors, stiffness, slow movements, and balance problems. It's caused by the loss of dopamine-producing cells in a part of the brain called the substantia nigra. There is no cure for Parkinson's, but medications and therapies can help manage symptoms.
mutations
Changes in the DNA sequence.
Mutations are alterations in the genetic code (DNA). They can be caused by errors during DNA replication, exposure to radiation or chemicals, or inherited from parents. Mutations can have various effects, ranging from harmless to causing diseases like cancer.
psychatric disorders
Mental illnesses that affect mood, thinking, and behavior.
Psychiatric disorders are a broad category of mental health conditions that can significantly impact an individual's thoughts, feelings, and actions. Examples include depression, anxiety disorders, bipolar disorder, schizophrenia, and obsessive-compulsive disorder.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:34:25|
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 | 8,188,684 | 422,705 | 19.37 | 1 hrs 14 mins |
| 2 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 7,385,663 | 409,442 | 18.04 | 1 hrs 20 mins |
| 3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 7,059,577 | 402,577 | 17.54 | 1 hrs 22 mins |
| 4 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,564,721 | 347,282 | 13.14 | 1 hrs 50 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,515,431 | 345,345 | 13.08 | 1 hrs 50 mins |
| 6 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,512,963 | 347,086 | 13.00 | 1 hrs 51 mins |
| 7 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,359,657 | 343,199 | 12.70 | 1 hrs 53 mins |
| 8 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,056,214 | 334,096 | 12.14 | 1 hrs 59 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,045,998 | 333,524 | 12.13 | 1 hrs 59 mins |
| 10 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,323,692 | 314,083 | 10.58 | 2 hrs 16 mins |
| 11 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,570,320 | 280,712 | 9.16 | 2 hrs 37 mins |
| 12 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,427,414 | 282,976 | 8.58 | 2 hrs 48 mins |
| 13 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,049,236 | 268,895 | 7.62 | 3 hrs 9 mins |
| 14 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,030,846 | 268,822 | 7.55 | 3 hrs 11 mins |
| 15 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,966,188 | 263,627 | 7.46 | 3 hrs 13 mins |
| 16 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,363,254 | 240,586 | 5.67 | 4 hrs 14 mins |
| 17 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,052,867 | 217,423 | 4.84 | 4 hrs 57 mins |
| 18 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,037,395 | 215,471 | 4.81 | 4 hrs 59 mins |
| 19 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 1,030,119 | 212,341 | 4.85 | 4 hrs 57 mins |
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| 20 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 709,963 | 110,727 | 6.41 | 3 hrs 45 mins |
| 21 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 612,654 | 179,778 | 3.41 | 7 hrs 3 mins |
| 22 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 549,356 | 173,160 | 3.17 | 7 hrs 34 mins |
| 23 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 474,149 | 166,791 | 2.84 | 8 hrs 27 mins |
| 24 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 303,781 | 153,943 | 1.97 | 12 hrs 10 mins |
| 25 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 47,489 | 79,305 | 0.60 | 40 hrs 5 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:34:25|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|