RESEARCH: CANCER
FOLDING PROJECT #12913 PROFILE
PROJECT TEAM
Manager(s): Diego KleimanInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 13,564Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Proteins are made up of chains that fold into specific shapes. Sometimes, changes in the protein's code can mess up this folding, causing diseases like cancer and Alzheimer's. This project looks at how different changes affect how proteins fold to help us understand and predict these problems.
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
Large biomolecules essential for various biological functions.
Proteins are complex molecules that perform many crucial tasks in living organisms. They act as enzymes, antibodies, structural components, and more. Understanding protein structure and function is fundamental to comprehending life processes.
Misfolding
Failure of a protein to adopt its correct three-dimensional shape.
Protein misfolding occurs when a protein cannot fold into its proper shape. This can lead to dysfunctional proteins that may aggregate and cause diseases like Alzheimer's and Parkinson's.
Mutation
A permanent alteration in the DNA sequence.
Mutations are changes in the genetic code (DNA). They can arise spontaneously or due to environmental factors. Mutations can have various effects, ranging from being harmless to causing disease.
Conformation
The three-dimensional shape of a molecule.
Conformation refers to the specific arrangement of atoms within a molecule. This shape is crucial for a molecule's function. Changes in conformation can alter its activity.
Cancer
Uncontrolled growth and spread of abnormal cells.
Cancer is a group of diseases characterized by the uncontrolled division and spread of abnormal cells. It can affect various organs and tissues in the body.
Alzheimer's
A progressive neurodegenerative disease.
Alzheimer's disease is a brain disorder that progressively destroys memory and cognitive function. It is the most common cause of dementia.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:33:55|
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 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 3,008,578 | 189,119 | 15.91 | 1 hrs 31 mins |
| 2 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,954,380 | 184,838 | 15.98 | 1 hrs 30 mins |
| 3 | GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB] |
Nvidia | TU106 | 2,496,515 | 174,875 | 14.28 | 1 hrs 41 mins |
| 4 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,239,618 | 168,553 | 13.29 | 1 hrs 48 mins |
| 5 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,143,945 | 55,734 | 38.47 | 0 hrs 37 mins |
| 6 | GeForce RTX 3050 8GB GA107 [GeForce RTX 3050 8GB] |
Nvidia | GA107 | 1,858,182 | 157,882 | 11.77 | 2 hrs 2 mins |
| 7 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,639,794 | 150,138 | 10.92 | 2 hrs 12 mins |
| 8 | GeForce GTX 1060 6GB GP104 [GeForce GTX 1060 6GB] |
Nvidia | GP104 | 937,860 | 127,019 | 7.38 | 3 hrs 15 mins |
| 9 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 884,823 | 123,675 | 7.15 | 3 hrs 21 mins |
| 10 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 865,973 | 123,730 | 7.00 | 3 hrs 26 mins |
| 11 | Quadro P3200 Mobile GP104GLM [Quadro P3200 Mobile] |
Nvidia | GP104GLM | 831,374 | 78,813 | 10.55 | 2 hrs 17 mins |
| 12 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 729,468 | 100,917 | 7.23 | 3 hrs 19 mins |
| 13 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 688,506 | 113,839 | 6.05 | 3 hrs 58 mins |
| 14 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 654,329 | 31,000 | 21.11 | 1 hrs 8 mins |
| 15 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 560,801 | 31,000 | 18.09 | 1 hrs 20 mins |
| 16 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 458,721 | 45,935 | 9.99 | 2 hrs 24 mins |
| 17 | Quadro P2200 GP106GL [Quadro P2200] |
Nvidia | GP106GL | 417,105 | 101,085 | 4.13 | 5 hrs 49 mins |
| 18 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 349,603 | 92,210 | 3.79 | 6 hrs 20 mins |
| 19 | GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile] |
Nvidia | GP107M | 278,287 | 84,156 | 3.31 | 7 hrs 15 mins |
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| 20 | GeForce GTX 1050 3 GB Max-Q GP107M [GeForce GTX 1050 3 GB Max-Q] |
Nvidia | GP107M | 227,057 | 81,298 | 2.79 | 8 hrs 36 mins |
| 21 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 212,984 | 72,161 | 2.95 | 8 hrs 8 mins |
| 22 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 145,299 | 68,220 | 2.13 | 11 hrs 16 mins |
| 23 | GeForce MX150 GP107M [GeForce MX150] |
Nvidia | GP107M | 138,289 | 66,510 | 2.08 | 11 hrs 33 mins |
| 24 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 88,378 | 64,365 | 1.37 | 17 hrs 29 mins |
| 25 | GeForce GT 710 GK208B [GeForce GT 710] 366 |
Nvidia | GK208B | 13,899 | 31,000 | 0.45 | 53 hrs 32 mins |
| 26 | Quadro NVS 510 GK107 [Quadro NVS 510] |
Nvidia | GK107 | 8,263 | 31,000 | 0.27 | 90 hrs 2 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:33:55|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|