RESEARCH: PARKINSONS
FOLDING PROJECT #17913 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 83,598Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project simulates how the serotonin transporter protein works. Serotonin affects mood, sleep, and appetite. Changes in this protein are linked to depression and Parkinson's disease. By studying these simulations, scientists hope to understand how mutations affect the protein and find new treatments for mental health 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
Protein responsible for terminating serotonin signaling in neurons.
The serotonin transporter is a protein found in the brain that helps regulate mood and behavior. It works by removing serotonin from the spaces between nerve cells (synapses), effectively stopping its signal. Problems with this transporter can contribute to mental health conditions like depression.
neurotransmitter
A chemical messenger that transmits signals across a synapse between neurons.
Neurotransmitters are chemicals that allow nerve cells to communicate with each other. They travel across tiny gaps called synapses and trigger responses in receiving neurons. Examples include serotonin, dopamine, and acetylcholine.
serotonin
A neurotransmitter that regulates mood, sleep, appetite, and other functions.
Serotonin is a brain chemical that plays a vital role in regulating mood, happiness, sleep, and appetite. Imbalances in serotonin levels can contribute to conditions like depression and anxiety.
antidepressants
Medications used to treat depression and other mental health disorders.
Antidepressants are a class of medications that help improve mood and manage symptoms of depression. They work by affecting the levels of certain neurotransmitters in the brain, such as serotonin and norepinephrine.
mutations
Permanent changes in the DNA sequence.
Mutations are alterations in the genetic code (DNA). They can occur spontaneously or be induced by factors like radiation. Mutations can have various effects, ranging from being harmless to causing diseases.
psychatric disorders
Mental health conditions that affect mood, thinking, and behavior.
Psychiatric disorders encompass a wide range of mental health conditions that impact a person's emotional well-being, thoughts, and behaviors. These disorders can include depression, anxiety, bipolar disorder, schizophrenia, and others.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:34:28|
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 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 9,187,296 | 329,526 | 27.88 | 0 hrs 52 mins |
| 2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 8,150,718 | 317,326 | 25.69 | 0 hrs 56 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 7,231,555 | 305,120 | 23.70 | 1 hrs 1 mins |
| 4 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,490,588 | 294,690 | 22.03 | 1 hrs 5 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,823,570 | 264,906 | 18.21 | 1 hrs 19 mins |
| 6 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,455,870 | 261,171 | 17.06 | 1 hrs 24 mins |
| 7 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,298,039 | 257,678 | 16.68 | 1 hrs 26 mins |
| 8 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,270,521 | 261,500 | 16.33 | 1 hrs 28 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,895,980 | 248,745 | 15.66 | 1 hrs 32 mins |
| 10 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,668,534 | 230,566 | 15.91 | 1 hrs 31 mins |
| 11 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,312,349 | 235,177 | 14.08 | 1 hrs 42 mins |
| 12 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,896,092 | 224,769 | 12.88 | 1 hrs 52 mins |
| 13 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,220,314 | 205,359 | 10.81 | 2 hrs 13 mins |
| 14 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,024,680 | 198,666 | 10.19 | 2 hrs 21 mins |
| 15 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,984,921 | 199,282 | 9.96 | 2 hrs 25 mins |
| 16 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 1,890,941 | 208,977 | 9.05 | 2 hrs 39 mins |
| 17 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,611,822 | 183,940 | 8.76 | 2 hrs 44 mins |
| 18 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,437,449 | 177,361 | 8.10 | 2 hrs 58 mins |
| 19 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,374,314 | 172,718 | 7.96 | 3 hrs 1 mins |
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| 20 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,281,870 | 173,895 | 7.37 | 3 hrs 15 mins |
| 21 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,209,808 | 145,728 | 8.30 | 2 hrs 53 mins |
| 22 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,115,966 | 166,528 | 6.70 | 3 hrs 35 mins |
| 23 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,070,218 | 159,513 | 6.71 | 3 hrs 35 mins |
| 24 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 961,346 | 156,270 | 6.15 | 3 hrs 54 mins |
| 25 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 911,475 | 147,193 | 6.19 | 3 hrs 53 mins |
| 26 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 880,004 | 152,637 | 5.77 | 4 hrs 10 mins |
| 27 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 645,648 | 137,469 | 4.70 | 5 hrs 7 mins |
| 28 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 623,497 | 135,351 | 4.61 | 5 hrs 13 mins |
| 29 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 396,098 | 116,479 | 3.40 | 7 hrs 3 mins |
| 30 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 261,765 | 101,958 | 2.57 | 9 hrs 21 mins |
| 31 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 203,050 | 93,748 | 2.17 | 11 hrs 5 mins |
| 32 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 91,424 | 71,564 | 1.28 | 18 hrs 47 mins |
| 33 | Quadro K620 GM107GL [Quadro K620] |
Nvidia | GM107GL | 53,828 | 53,724 | 1.00 | 23 hrs 57 mins |
| 34 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 43,953 | 52,037 | 0.84 | 28 hrs 25 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:34:28|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|