RESEARCH: SIGNALING PROTEIN
FOLDING PROJECT #18907 PROFILE
PROJECT TEAM
Manager(s): Jiming ChenInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 36,143Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project relates to how small changes in signaling proteins can cause big problems with how cells communicate. These changes can lead to diseases, and many drugs target these proteins.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Impact of mutations on signaling proteins Mutations in proteins are often found to have dramatic functional consequences through changes in conformational dynamics, ligand binding, and association with signaling partners.
These changes sometimes lead to pathological outcomes.
Additionally, proteins involved in cell signaling are the target of over half of approved drugs.
This project aims to understand how a small number of mutations in signaling proteins can cause a dramatic change in how they modulate cell signaling pathways.
RELATED TERMS GLOSSARY AI BETA
mutations
Alterations in the DNA sequence of a gene.
Mutations are changes in the genetic code that can affect how proteins function. They can be caused by environmental factors, errors during DNA replication, or inherited from parents. Mutations can have a wide range of effects, from being harmless to causing serious diseases.
signaling proteins
Proteins that transmit signals within cells and between cells.
Signaling proteins are crucial for communication within and between cells. They relay information about various stimuli, such as growth factors, hormones, and nutrients, triggering specific cellular responses.
conformational dynamics
The changes in shape of a protein over time.
Conformational dynamics refer to the flexibility and movement of proteins. This constant shifting allows proteins to interact with other molecules and carry out their functions effectively.
ligand binding
The process of a molecule attaching to a protein.
Ligand binding is essential for many cellular processes. It allows molecules, such as hormones or neurotransmitters, to interact with specific proteins and trigger a response.
pathological outcomes
Abnormal conditions that result in disease or dysfunction.
Pathological outcomes are the undesirable consequences of disease or injury. They can range from mild symptoms to life-threatening complications.
cell signaling pathways
Series of molecular interactions that transmit signals within a cell.
Cell signaling pathways are intricate networks of molecules that allow cells to communicate with each other and respond to their environment. They play crucial roles in growth, development, and disease.
drugs
Substances that are used to treat, prevent, or diagnose disease.
Drugs are chemical compounds designed to interact with specific targets in the body to produce a therapeutic effect. They can be administered orally, intravenously, or through other routes.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:26:59|
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 | 4,837,423 | 78,954 | 61.27 | 0 hrs 24 mins |
| 2 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,111,697 | 77,259 | 53.22 | 0 hrs 27 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 3,959,224 | 73,225 | 54.07 | 0 hrs 27 mins |
| 4 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 3,509,670 | 70,622 | 49.70 | 0 hrs 29 mins |
| 5 | GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 3,428,521 | 71,528 | 47.93 | 0 hrs 30 mins |
| 6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,261,216 | 70,523 | 46.24 | 0 hrs 31 mins |
| 7 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,233,376 | 70,385 | 45.94 | 0 hrs 31 mins |
| 8 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 3,139,795 | 70,397 | 44.60 | 0 hrs 32 mins |
| 9 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,066,239 | 67,976 | 45.11 | 0 hrs 32 mins |
| 10 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 2,744,984 | 59,293 | 46.30 | 0 hrs 31 mins |
| 11 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,645,646 | 65,237 | 40.55 | 0 hrs 36 mins |
| 12 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 2,594,756 | 65,356 | 39.70 | 0 hrs 36 mins |
| 13 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,261,279 | 62,223 | 36.34 | 0 hrs 40 mins |
| 14 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,257,013 | 62,582 | 36.06 | 0 hrs 40 mins |
| 15 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,204,730 | 61,588 | 35.80 | 0 hrs 40 mins |
| 16 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,114,371 | 60,235 | 35.10 | 0 hrs 41 mins |
| 17 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,704,861 | 56,770 | 30.03 | 0 hrs 48 mins |
| 18 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 1,688,304 | 56,401 | 29.93 | 0 hrs 48 mins |
| 19 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,682,120 | 56,400 | 29.82 | 0 hrs 48 mins |
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| 20 | GeForce RTX 3060 GA104 [GeForce RTX 3060] |
Nvidia | GA104 | 1,668,359 | 57,001 | 29.27 | 0 hrs 49 mins |
| 21 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,483,807 | 54,134 | 27.41 | 0 hrs 53 mins |
| 22 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,331,378 | 52,550 | 25.34 | 0 hrs 57 mins |
| 23 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,283,404 | 51,541 | 24.90 | 0 hrs 58 mins |
| 24 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,261,002 | 51,179 | 24.64 | 0 hrs 58 mins |
| 25 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,201,369 | 50,205 | 23.93 | 1 hrs 0 mins |
| 26 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,101,939 | 49,054 | 22.46 | 1 hrs 4 mins |
| 27 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,087,144 | 48,857 | 22.25 | 1 hrs 5 mins |
| 28 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 905,644 | 46,120 | 19.64 | 1 hrs 13 mins |
| 29 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 881,131 | 45,373 | 19.42 | 1 hrs 14 mins |
| 30 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 852,463 | 44,086 | 19.34 | 1 hrs 14 mins |
| 31 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 722,426 | 43,107 | 16.76 | 1 hrs 26 mins |
| 32 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 578,149 | 40,133 | 14.41 | 1 hrs 40 mins |
| 33 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 398,326 | 34,882 | 11.42 | 2 hrs 6 mins |
| 34 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 375,232 | 35,540 | 10.56 | 2 hrs 16 mins |
| 35 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 357,596 | 33,561 | 10.66 | 2 hrs 15 mins |
| 36 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 345,565 | 33,483 | 10.32 | 2 hrs 20 mins |
| 37 | Quadro M2000 GM206GL [Quadro M2000] |
Nvidia | GM206GL | 128,637 | 23,899 | 5.38 | 4 hrs 28 mins |
| 38 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 81,518 | 20,813 | 3.92 | 6 hrs 8 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:26:59|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|