RESEARCH: SIGNALING PROTEIN
FOLDING PROJECT #18905 PROFILE
PROJECT TEAM
Manager(s): Jiming ChenInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 43,328Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project relates to how small changes in proteins that control cell signals can cause big problems in how our cells work. These proteins are important because many medicines target them.
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 DNA sequence that make up genes. These changes can be caused by errors during DNA replication or exposure to mutagens like radiation. Mutations can have a wide range of effects, from being harmless to causing disease.
Signaling Proteins
Proteins that transmit signals within cells and between cells.
Signaling proteins are essential for cell communication. They relay messages from the outside of a cell to the inside, triggering specific responses. These responses can include changes in gene expression, cell growth, or movement.
Conformational Dynamics
The changes in shape that a protein undergoes.
Conformational dynamics refer to the flexibility and movement of proteins. Proteins can change shape depending on their environment and interactions with other molecules. These shape changes are crucial for their function.
Ligand Binding
The attachment of a molecule to a protein.
Ligand binding is the process where a molecule called a ligand binds to a specific site on a protein. This interaction can activate or inhibit the protein's function.
Pathological Outcomes
Disease states or abnormal conditions.
Pathological outcomes refer to the development of diseases or abnormal conditions. These can result from various factors, including genetic mutations, environmental exposures, and infections.
Cell Signaling Pathways
Series of molecular events that transmit signals within cells.
Cell signaling pathways are intricate networks of molecules that allow cells to communicate with each other and respond to their environment. These pathways involve a cascade of interactions, transmitting signals from the cell surface to the nucleus, ultimately regulating gene expression and cellular functions.
Drugs
Substances that alter biological processes.
Drugs are chemical compounds designed to have a specific effect on the body. They can treat diseases, prevent infections, manage pain, and modify various physiological functions.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:27:02|
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 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,979,078 | 80,180 | 74.57 | 0 hrs 19 mins |
| 2 | GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 5,422,871 | 78,171 | 69.37 | 0 hrs 21 mins |
| 3 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,395,935 | 78,084 | 69.10 | 0 hrs 21 mins |
| 4 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 5,167,570 | 77,921 | 66.32 | 0 hrs 22 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,346,861 | 72,934 | 59.60 | 0 hrs 24 mins |
| 6 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 4,190,953 | 70,495 | 59.45 | 0 hrs 24 mins |
| 7 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,513,750 | 68,300 | 51.45 | 0 hrs 28 mins |
| 8 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,370,846 | 67,441 | 49.98 | 0 hrs 29 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,986,470 | 64,793 | 46.09 | 0 hrs 31 mins |
| 10 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 2,751,663 | 62,825 | 43.80 | 0 hrs 33 mins |
| 11 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,496,378 | 59,527 | 41.94 | 0 hrs 34 mins |
| 12 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,429,129 | 61,157 | 39.72 | 0 hrs 36 mins |
| 13 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,323,766 | 59,613 | 38.98 | 0 hrs 37 mins |
| 14 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,320,747 | 59,150 | 39.23 | 0 hrs 37 mins |
| 15 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,315,522 | 58,214 | 39.78 | 0 hrs 36 mins |
| 16 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,848,330 | 54,857 | 33.69 | 0 hrs 43 mins |
| 17 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,700,559 | 53,473 | 31.80 | 0 hrs 45 mins |
| 18 | GeForce RTX 3060 GA104 [GeForce RTX 3060] |
Nvidia | GA104 | 1,700,175 | 53,395 | 31.84 | 0 hrs 45 mins |
| 19 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,288,496 | 48,720 | 26.45 | 0 hrs 54 mins |
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| 20 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,269,602 | 48,660 | 26.09 | 0 hrs 55 mins |
| 21 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,243,481 | 47,898 | 25.96 | 0 hrs 55 mins |
| 22 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,089,325 | 45,997 | 23.68 | 1 hrs 1 mins |
| 23 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,055,509 | 45,158 | 23.37 | 1 hrs 2 mins |
| 24 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,051,903 | 45,536 | 23.10 | 1 hrs 2 mins |
| 25 | GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile] |
Nvidia | TU116M | 981,185 | 44,648 | 21.98 | 1 hrs 6 mins |
| 26 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 923,004 | 43,151 | 21.39 | 1 hrs 7 mins |
| 27 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 885,966 | 42,882 | 20.66 | 1 hrs 10 mins |
| 28 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 533,870 | 36,023 | 14.82 | 1 hrs 37 mins |
| 29 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 419,459 | 33,179 | 12.64 | 1 hrs 54 mins |
| 30 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 351,035 | 31,432 | 11.17 | 2 hrs 9 mins |
| 31 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 212,609 | 27,210 | 7.81 | 3 hrs 4 mins |
| 32 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 128,546 | 22,540 | 5.70 | 4 hrs 12 mins |
| 33 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 126,280 | 22,884 | 5.52 | 4 hrs 21 mins |
| 34 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 100,953 | 20,875 | 4.84 | 4 hrs 58 mins |
| 35 | Quadro K620 GM107GL [Quadro K620] |
Nvidia | GM107GL | 54,447 | 17,102 | 3.18 | 7 hrs 32 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:27:02|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|