RESEARCH: PARKINSONS
FOLDING PROJECT #17912 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 85,685Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how changes in the serotonin transporter protein can cause mental health problems like depression. By simulating these changes, scientists hope to learn more about how 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
Protein responsible for terminating neurotransmitter serotonin signaling.
The serotonin transporter is a protein found in neurons that plays a crucial role in regulating mood, behavior, appetite, and sleep. It works by reabsorbing serotonin from the synapse, the space between neurons, effectively stopping its action. Malfunctions in this transporter are linked to mental health disorders like depression and Parkinson's disease.
neurotransmission
The process of transmitting signals across synapses.
Neurotransmission is the complex process by which neurons communicate with each other. It involves the release of chemical messengers called neurotransmitters, which travel across a small gap called a synapse and bind to receptors on the receiving neuron. This triggers a cascade of events that ultimately leads to a change in the receiving neuron's activity.
serotonin
A neurotransmitter that regulates mood, sleep, appetite, and other functions.
Serotonin is a chemical messenger in the brain that plays a vital role in regulating mood, sleep, appetite, and many other bodily functions. Imbalances in serotonin levels have been linked to depression, anxiety, and other mental health disorders.
mutation
A permanent change in the DNA sequence.
A mutation is a change in the genetic code (DNA) of an organism. These changes can occur spontaneously or be caused by environmental factors like radiation. Mutations can have various effects, ranging from being harmless to causing diseases like cancer.
psychatric
Relating to the treatment of mental disorders.
Psychiatric refers to the field of medicine that deals with the diagnosis, treatment, and prevention of mental health disorders. Psychiatrists are medical doctors who specialize in treating these conditions using a variety of therapies, medications, and other interventions.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:34:30|
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 | 7,328,946 | 304,135 | 24.10 | 0 hrs 60 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,228,302 | 299,529 | 20.79 | 1 hrs 9 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 6,026,988 | 297,071 | 20.29 | 1 hrs 11 mins |
| 4 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 4,914,224 | 242,609 | 20.26 | 1 hrs 11 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,590,525 | 270,527 | 16.97 | 1 hrs 25 mins |
| 6 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,341,742 | 266,925 | 16.27 | 1 hrs 29 mins |
| 7 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,208,348 | 264,037 | 15.94 | 1 hrs 30 mins |
| 8 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,089,452 | 260,999 | 15.67 | 1 hrs 32 mins |
| 9 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,848,982 | 250,968 | 15.34 | 1 hrs 34 mins |
| 10 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,391,241 | 235,328 | 14.41 | 1 hrs 40 mins |
| 11 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,314,940 | 242,582 | 13.67 | 1 hrs 45 mins |
| 12 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,916,919 | 224,212 | 13.01 | 1 hrs 51 mins |
| 13 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,369,614 | 217,334 | 10.90 | 2 hrs 12 mins |
| 14 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,127,607 | 209,487 | 10.16 | 2 hrs 22 mins |
| 15 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,813,436 | 199,196 | 9.10 | 2 hrs 38 mins |
| 16 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,802,770 | 192,470 | 9.37 | 2 hrs 34 mins |
| 17 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,614,625 | 191,533 | 8.43 | 2 hrs 51 mins |
| 18 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,417,199 | 174,211 | 8.13 | 2 hrs 57 mins |
| 19 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,286,562 | 173,939 | 7.40 | 3 hrs 15 mins |
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| 20 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,195,970 | 146,499 | 8.16 | 2 hrs 56 mins |
| 21 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,184,746 | 174,283 | 6.80 | 3 hrs 32 mins |
| 22 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,107,131 | 167,219 | 6.62 | 3 hrs 37 mins |
| 23 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,030,982 | 165,432 | 6.23 | 3 hrs 51 mins |
| 24 | GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile] |
Nvidia | TU116M | 1,004,468 | 163,681 | 6.14 | 3 hrs 55 mins |
| 25 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 947,014 | 159,846 | 5.92 | 4 hrs 3 mins |
| 26 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 887,571 | 156,903 | 5.66 | 4 hrs 15 mins |
| 27 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 716,015 | 146,919 | 4.87 | 4 hrs 55 mins |
| 28 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 606,647 | 138,398 | 4.38 | 5 hrs 29 mins |
| 29 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 472,167 | 127,449 | 3.70 | 6 hrs 29 mins |
| 30 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 419,188 | 127,957 | 3.28 | 7 hrs 20 mins |
| 31 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 369,388 | 118,790 | 3.11 | 7 hrs 43 mins |
| 32 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 249,363 | 103,287 | 2.41 | 9 hrs 56 mins |
| 33 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 176,672 | 91,773 | 1.93 | 12 hrs 28 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:34:30|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|