RESEARCH: SIGNALING PROTEIN
FOLDING PROJECT #18906 PROFILE
PROJECT TEAM
Manager(s): Jiming ChenInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 38,594Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project relates to how small changes in proteins that send signals within cells can cause big problems with how our bodies work. These changes can lead to diseases and are often targeted by medicines.
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
Permanent alterations in the DNA sequence.
Mutations are changes in the genetic code that can affect how genes work. They can be caused by environmental factors or errors during DNA replication. Mutations can have a wide range of effects, from being harmless to causing disease.
signaling proteins
Proteins that transmit signals within cells or between cells.
Signaling proteins are essential for communication within and between cells. They relay messages from one part of a cell to another or from one cell to another, triggering various cellular responses such as growth, differentiation, and movement.
conformational dynamics
Changes in the shape of a protein.
Conformational dynamics refers to the various shapes a protein can adopt. These shape changes are crucial for protein function, allowing them to interact with other molecules and carry out their roles.
ligand binding
The interaction between a protein and a small molecule.
Ligand binding is the process where a small molecule (ligand) attaches to a protein. This interaction often triggers a change in the protein's shape or activity, leading to various cellular responses.
signaling partners
Other proteins that interact with signaling proteins.
Signaling partners are proteins that work together with signaling proteins to transmit signals within cells. They can amplify or modify the signal, ensuring accurate and coordinated cellular responses.
pathological outcomes
Harmful or abnormal changes in the body.
Pathological outcomes are the negative consequences that can result from disease or other medical conditions. They can range from mild symptoms to life-threatening complications.
drugs
Substances that are used to treat or prevent disease.
Drugs are chemical substances designed to have a specific effect on the body. They can be used to treat various conditions, from infections to chronic diseases.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:27:00|
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 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,375,615 | 68,560 | 78.41 | 0 hrs 18 mins |
| 2 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,304,504 | 65,623 | 80.83 | 0 hrs 18 mins |
| 3 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 4,573,712 | 62,198 | 73.53 | 0 hrs 20 mins |
| 4 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,014,038 | 61,181 | 65.61 | 0 hrs 22 mins |
| 5 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,490,144 | 57,647 | 60.54 | 0 hrs 24 mins |
| 6 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 3,189,059 | 58,508 | 54.51 | 0 hrs 26 mins |
| 7 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,117,127 | 55,838 | 55.82 | 0 hrs 26 mins |
| 8 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 2,706,287 | 48,546 | 55.75 | 0 hrs 26 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,585,753 | 52,362 | 49.38 | 0 hrs 29 mins |
| 10 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 2,567,187 | 52,950 | 48.48 | 0 hrs 30 mins |
| 11 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,468,503 | 52,805 | 46.75 | 0 hrs 31 mins |
| 12 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,346,965 | 50,826 | 46.18 | 0 hrs 31 mins |
| 13 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,144,306 | 49,161 | 43.62 | 0 hrs 33 mins |
| 14 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,051,415 | 49,510 | 41.43 | 0 hrs 35 mins |
| 15 | GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q] |
Nvidia | GA104M | 1,982,193 | 48,432 | 40.93 | 0 hrs 35 mins |
| 16 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,736,311 | 46,485 | 37.35 | 0 hrs 39 mins |
| 17 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,653,413 | 46,009 | 35.94 | 0 hrs 40 mins |
| 18 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,282,733 | 41,648 | 30.80 | 0 hrs 47 mins |
| 19 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,270,473 | 41,480 | 30.63 | 0 hrs 47 mins |
|
|
|||||||
| 20 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,147,437 | 40,786 | 28.13 | 0 hrs 51 mins |
| 21 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,133,804 | 40,010 | 28.34 | 0 hrs 51 mins |
| 22 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,115,872 | 39,515 | 28.24 | 0 hrs 51 mins |
| 23 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,067,268 | 39,057 | 27.33 | 0 hrs 53 mins |
| 24 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 923,068 | 36,020 | 25.63 | 0 hrs 56 mins |
| 25 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 914,005 | 37,025 | 24.69 | 0 hrs 58 mins |
| 26 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 809,867 | 35,778 | 22.64 | 1 hrs 4 mins |
| 27 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 706,174 | 33,914 | 20.82 | 1 hrs 9 mins |
| 28 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 634,555 | 33,553 | 18.91 | 1 hrs 16 mins |
| 29 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 627,932 | 33,393 | 18.80 | 1 hrs 17 mins |
| 30 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 599,529 | 32,286 | 18.57 | 1 hrs 18 mins |
| 31 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 398,415 | 23,568 | 16.90 | 1 hrs 25 mins |
| 32 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 330,438 | 26,727 | 12.36 | 1 hrs 56 mins |
| 33 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 217,003 | 23,090 | 9.40 | 2 hrs 33 mins |
| 34 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 208,646 | 23,083 | 9.04 | 2 hrs 39 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:27:00|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|