RESEARCH: CANCER
FOLDING PROJECT #12909 PROFILE
PROJECT TEAM
Manager(s): Diego KleimanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 13,780Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Proteins need to fold into specific shapes to work properly. Sometimes, changes in the protein's code (mutations) mess up this folding, leading to diseases like cancer and Alzheimer's. The project relates to studying how these mutations affect how proteins fold so we can better understand and prevent these diseases.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Protein misfolding occurs when a peptide cannot fold into its native structure.
Mutations in the protein sequence may cause alterations of the native folded conformation, leading to diseases such as cancer and Alzheimer's.
Understanding protein misfolding as a function of mutations is currently one of the biggest challenges in the biological sciences.
We aim to systematically study folding rates of diverse mutated proteins to better understand and predict folding dynamics.
RELATED TERMS GLOSSARY AI BETA
Protein
A large biomolecule composed of amino acids linked in a chain.
Proteins are essential molecules found in all living organisms. They perform a wide range of functions, including catalyzing biochemical reactions, providing structural support, transporting molecules, and regulating cellular processes.
Misfolding
The process by which a protein fails to attain its correct three-dimensional structure.
Protein misfolding occurs when a protein cannot fold into its proper shape. This can disrupt the protein's function and lead to diseases.
Mutations
Changes in the DNA sequence of a gene.
Mutations are alterations in the genetic code. They can be inherited or acquired during an organism's lifetime and can have various effects on protein function.
Conformation
The three-dimensional shape of a molecule.
Conformation refers to the arrangement of atoms in a molecule. Proteins can have different conformations depending on their environment and function.
Cancer
A disease characterized by uncontrolled cell growth.
Cancer is a group of diseases involving abnormal cell growth and spread. It can affect various organs and tissues in the body.
Alzheimer's
A neurodegenerative disease characterized by memory loss and cognitive decline.
Alzheimer's disease is a progressive brain disorder that affects memory, thinking, and behavior. It is the most common cause of dementia.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:33:57|
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 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 4,428,411 | 337,633 | 13.12 | 1 hrs 50 mins |
| 2 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,529,847 | 174,999 | 14.46 | 1 hrs 40 mins |
| 3 | GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB] |
Nvidia | TU106 | 2,342,299 | 170,219 | 13.76 | 1 hrs 45 mins |
| 4 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,226,171 | 124,847 | 17.83 | 1 hrs 21 mins |
| 5 | GeForce RTX 3050 8GB GA107 [GeForce RTX 3050 8GB] |
Nvidia | GA107 | 1,774,033 | 156,105 | 11.36 | 2 hrs 7 mins |
| 6 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,353,202 | 140,579 | 9.63 | 2 hrs 30 mins |
| 7 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,277,120 | 143,550 | 8.90 | 2 hrs 42 mins |
| 8 | GeForce GTX 1060 6GB GP104 [GeForce GTX 1060 6GB] |
Nvidia | GP104 | 891,098 | 125,050 | 7.13 | 3 hrs 22 mins |
| 9 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 790,065 | 119,112 | 6.63 | 3 hrs 37 mins |
| 10 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 727,709 | 38,906 | 18.70 | 1 hrs 17 mins |
| 11 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 695,222 | 114,756 | 6.06 | 3 hrs 58 mins |
| 12 | Quadro P3200 Mobile GP104GLM [Quadro P3200 Mobile] |
Nvidia | GP104GLM | 692,184 | 85,342 | 8.11 | 2 hrs 58 mins |
| 13 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 640,136 | 31,000 | 20.65 | 1 hrs 10 mins |
| 14 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 616,044 | 31,000 | 19.87 | 1 hrs 12 mins |
| 15 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 491,277 | 97,645 | 5.03 | 4 hrs 46 mins |
| 16 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 393,016 | 50,238 | 7.82 | 3 hrs 4 mins |
| 17 | Quadro P2200 GP106GL [Quadro P2200] |
Nvidia | GP106GL | 382,083 | 79,171 | 4.83 | 4 hrs 58 mins |
| 18 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 322,251 | 88,984 | 3.62 | 6 hrs 38 mins |
| 19 | GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile] |
Nvidia | GP107M | 271,772 | 83,540 | 3.25 | 7 hrs 23 mins |
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| 20 | Quadro M4000 GM204GL [Quadro M4000] |
Nvidia | GM204GL | 254,122 | 81,834 | 3.11 | 7 hrs 44 mins |
| 21 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 248,848 | 81,119 | 3.07 | 7 hrs 49 mins |
| 22 | GeForce GTX 1050 3 GB Max-Q GP107M [GeForce GTX 1050 3 GB Max-Q] |
Nvidia | GP107M | 248,832 | 83,322 | 2.99 | 8 hrs 2 mins |
| 23 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 243,140 | 49,370 | 4.92 | 4 hrs 52 mins |
| 24 | GeForce MX150 GP107M [GeForce MX150] |
Nvidia | GP107M | 126,534 | 62,811 | 2.01 | 11 hrs 55 mins |
| 25 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 86,519 | 48,111 | 1.80 | 13 hrs 21 mins |
| 26 | GeForce GTX 650 Ti GK106 [GeForce GTX 650 Ti] |
Nvidia | GK106 | 54,765 | 48,999 | 1.12 | 21 hrs 28 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:33:57|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|