RESEARCH: CANCER
FOLDING PROJECT #18453 PROFILE
PROJECT TEAM
Manager(s): Dylan NovackInstitution: Temple University
Project URL: View Project Website
WORK UNIT INFO
Atoms: 37,048Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how tiny proteins fold into their shapes. They found a way to predict how changing the protein's code affects its folding, using powerful computer simulations. They want to test this method on bigger proteins like MeCP2, which is important for brain development and causes Rett syndrome when it's faulty.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
The function of a protein depends on its native shape, or fold.
Deciphering the sequence-dependent process by which proteins reach their folded state has been the goal of much experimental and computational work, and the inspiration for the e Folding@home project.
Small “fast folding” mini-proteins, such as the protein G B1 domain (GB1) and hpin1 WW domain, have been studied extensively both experimentally and through simulation, producing a wealth of data on wild-type protein function, and much insight on how mutations affect the folding reaction.
In 2022, the Voelz lab published a study on the folding reaction of a transcription factor, FOXO1, in which a simple hydrophobic transfer model was used to accurately predict mutational effects from models derived from massively parallel Folding@home simulations (Novack et al.).
We found that this model made more accurate predictions than other state of the art methods of mutational analysis.
We hypothesize that this is because our simulations have more accurate descriptions of the unfolded ensemble of a protein than other methods, highlighting the importance of adequately describing the unfolded state of a protein in determining mutational effects on folding reaction.
In these projects, we aim to validate this hypothesis on the well studied miniproteins GB1 and hpin1 WW domain, as well as the MeCP2 protein.
MeCP2 is a protein that binds methylated DNA and is found in high levels in nerve cells.
the main disease associated with mutations of MeCP2 is Rett syndrome, a neurological disorder that severely impairs people’s ability to speak, walk, eat, and breathe.
The gene lives on X chromosomes, thus for people with an XY chromosomal configuration (lacking a complimentary natively functioning gene), this disease can be fatal within the first 2 years due to encephalopathy.
There are at least 4668 mutational variants of MeCP2 identified, with 1171 being in the only structured region of the protein, the MBD.
Stability effects of mutation in MeCP2 have been investigated both experimentally and computationally, which makes it a promising test case for both validation of hydrophobic transfer as a model of mutation effects, as well as an opportunity to gain atomic insight that can elucidate new avenues for therapeutics targeting MeCP2.
RELATED TERMS GLOSSARY AI BETA
protein
A large biomolecule composed of amino acids.
Proteins are essential molecules in all living organisms. They have a wide variety of functions, including catalyzing biochemical reactions, transporting molecules, and providing structural support. The shape and sequence of amino acids determine a protein's function.
fold
The three-dimensional shape of a protein.
A protein's fold refers to its unique 3D structure. This shape is crucial for its function as it determines how the protein interacts with other molecules.
mutation
A permanent alteration in the DNA sequence.
Mutations are changes in the genetic code. They can be spontaneous or caused by environmental factors. Some mutations have no effect, while others can alter protein function and lead to disease.
transcription factor
A protein that binds to DNA and regulates gene expression.
Transcription factors are proteins that control which genes are turned on or off. They play a vital role in cellular processes by regulating gene expression.
FOXO1
Forkhead box O1 transcription factor
FOXO1 is a protein that regulates various cellular processes, including growth, survival, and metabolism. It plays a role in aging and disease.
MeCP2
Methyl-CpG binding protein 2
MeCP2 is a protein that binds to methylated DNA. It plays a crucial role in regulating gene expression in the brain.
Rett syndrome
A rare genetic disorder that affects girls primarily.
Rett syndrome is a neurodevelopmental disorder that causes intellectual disability, autism spectrum disorder, and other neurological problems. It primarily affects females and is caused by mutations in the MECP2 gene.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:28:53|
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 | 2,746,981 | 125,274 | 21.93 | 1 hrs 6 mins |
| 2 | GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB] |
Nvidia | TU106 | 2,010,419 | 113,706 | 17.68 | 1 hrs 21 mins |
| 3 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,896,730 | 109,509 | 17.32 | 1 hrs 23 mins |
| 4 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,821,023 | 109,369 | 16.65 | 1 hrs 26 mins |
| 5 | TITAN V GV100 [TITAN V] M 12288 |
Nvidia | GV100 | 1,810,170 | 108,998 | 16.61 | 1 hrs 27 mins |
| 6 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,754,208 | 103,056 | 17.02 | 1 hrs 25 mins |
| 7 | GeForce RTX 2070 Mobile TU106BM [GeForce RTX 2070 Mobile] |
Nvidia | TU106BM | 1,711,409 | 107,283 | 15.95 | 1 hrs 30 mins |
| 8 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,560,084 | 98,976 | 15.76 | 1 hrs 31 mins |
| 9 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,557,002 | 88,745 | 17.54 | 1 hrs 22 mins |
| 10 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,541,385 | 95,911 | 16.07 | 1 hrs 30 mins |
| 11 | Tesla P100 16GB GP100GL [Tesla P100 16GB] 9340 |
Nvidia | GP100GL | 1,442,484 | 101,709 | 14.18 | 1 hrs 42 mins |
| 12 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,269,780 | 84,142 | 15.09 | 1 hrs 35 mins |
| 13 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,217,793 | 95,196 | 12.79 | 1 hrs 53 mins |
| 14 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,192,911 | 94,568 | 12.61 | 1 hrs 54 mins |
| 15 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,149,455 | 94,259 | 12.19 | 1 hrs 58 mins |
| 16 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,148,100 | 92,102 | 12.47 | 1 hrs 56 mins |
| 17 | GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile] |
Nvidia | TU116M | 1,103,369 | 22,126 | 49.87 | 0 hrs 29 mins |
| 18 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,043,685 | 87,280 | 11.96 | 2 hrs 0 mins |
| 19 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 1,036,244 | 90,761 | 11.42 | 2 hrs 6 mins |
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| 20 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 989,538 | 89,269 | 11.08 | 2 hrs 10 mins |
| 21 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 966,951 | 88,280 | 10.95 | 2 hrs 11 mins |
| 22 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 899,773 | 84,133 | 10.69 | 2 hrs 15 mins |
| 23 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 839,929 | 84,707 | 9.92 | 2 hrs 25 mins |
| 24 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 819,997 | 81,591 | 10.05 | 2 hrs 23 mins |
| 25 | Quadro P4000 GP104GL [Quadro P4000] |
Nvidia | GP104GL | 790,120 | 83,324 | 9.48 | 2 hrs 32 mins |
| 26 | Quadro P3200 Mobile GP104GLM [Quadro P3200 Mobile] |
Nvidia | GP104GLM | 701,886 | 79,850 | 8.79 | 2 hrs 44 mins |
| 27 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 668,877 | 75,655 | 8.84 | 2 hrs 43 mins |
| 28 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 663,349 | 77,712 | 8.54 | 2 hrs 49 mins |
| 29 | GeForce RTX 3050 Ti Mobile GA107M [GeForce RTX 3050 Ti Mobile] |
Nvidia | GA107M | 652,174 | 78,118 | 8.35 | 2 hrs 52 mins |
| 30 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 649,803 | 77,400 | 8.40 | 2 hrs 52 mins |
| 31 | TITAN X GP102 [TITAN X] 6144 |
Nvidia | GP102 | 601,911 | 63,532 | 9.47 | 2 hrs 32 mins |
| 32 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 529,294 | 72,525 | 7.30 | 3 hrs 17 mins |
| 33 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 521,165 | 72,175 | 7.22 | 3 hrs 19 mins |
| 34 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 474,896 | 70,176 | 6.77 | 3 hrs 33 mins |
| 35 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 465,845 | 69,879 | 6.67 | 3 hrs 36 mins |
| 36 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 3091 |
Nvidia | TU116 | 407,867 | 60,588 | 6.73 | 3 hrs 34 mins |
| 37 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 399,932 | 66,652 | 6.00 | 3 hrs 60 mins |
| 38 | RX 5500/5500M/Pro 5500M Navi 14 [RX 5500/5500M/Pro 5500M] |
AMD | Navi 14 | 377,926 | 66,099 | 5.72 | 4 hrs 12 mins |
| 39 | Quadro P2200 GP106GL [Quadro P2200] |
Nvidia | GP106GL | 354,783 | 64,388 | 5.51 | 4 hrs 21 mins |
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| 40 | GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile] |
Nvidia | GP106M | 340,562 | 61,131 | 5.57 | 4 hrs 18 mins |
| 41 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 335,266 | 62,663 | 5.35 | 4 hrs 29 mins |
| 42 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 319,660 | 61,275 | 5.22 | 4 hrs 36 mins |
| 43 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 308,106 | 60,169 | 5.12 | 4 hrs 41 mins |
| 44 | GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile] |
Nvidia | GP107M | 271,951 | 58,125 | 4.68 | 5 hrs 8 mins |
| 45 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 222,994 | 54,505 | 4.09 | 5 hrs 52 mins |
| 46 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 198,871 | 49,667 | 4.00 | 5 hrs 60 mins |
| 47 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 184,053 | 50,981 | 3.61 | 6 hrs 39 mins |
| 48 | Tesla K40m GK110 [Tesla K40m] 5046 |
Nvidia | GK110 | 177,862 | 52,904 | 3.36 | 7 hrs 8 mins |
| 49 | RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590] |
AMD | Ellesmere XT | 173,692 | 50,514 | 3.44 | 6 hrs 59 mins |
| 50 | RX Vega M GH Polaris 22 XT [RX Vega M GH] |
AMD | Polaris 22 XT | 164,295 | 49,717 | 3.30 | 7 hrs 16 mins |
| 51 | R9 280X/HD 7900/8970 OEM Tahiti XT [R9 280X/HD 7900/8970 OEM] |
AMD | Tahiti XT | 150,647 | 48,439 | 3.11 | 7 hrs 43 mins |
| 52 | Radeon R9 285/380 Tonga PRO [Radeon R9 285/380] |
AMD | Tonga PRO | 144,246 | 47,600 | 3.03 | 7 hrs 55 mins |
| 53 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 128,482 | 45,195 | 2.84 | 8 hrs 27 mins |
| 54 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 123,600 | 47,069 | 2.63 | 9 hrs 8 mins |
| 55 | GeForce MX150 GP107M [GeForce MX150] |
Nvidia | GP107M | 120,465 | 44,502 | 2.71 | 8 hrs 52 mins |
| 56 | GeForce MX450 TU117M [GeForce MX450] |
Nvidia | TU117M | 103,078 | 41,013 | 2.51 | 9 hrs 33 mins |
| 57 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 100,296 | 41,219 | 2.43 | 9 hrs 52 mins |
| 58 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 86,417 | 43,701 | 1.98 | 12 hrs 8 mins |
| 59 | Radeon RX 460/560D Baffin [Radeon RX 460/560D] |
AMD | Baffin | 66,013 | 40,103 | 1.65 | 14 hrs 35 mins |
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| 60 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 63,058 | 35,640 | 1.77 | 13 hrs 34 mins |
| 61 | Quadro K620 GM107GL [Quadro K620] |
Nvidia | GM107GL | 34,029 | 33,821 | 1.01 | 23 hrs 51 mins |
| 62 | GeForce GT 730 GK208B [GeForce GT 730] 692.7 |
Nvidia | GK208B | 17,676 | 23,220 | 0.76 | 31 hrs 32 mins |
| 63 | GeForce GT 710 GK208B [GeForce GT 710] 366 |
Nvidia | GK208B | 10,251 | 22,126 | 0.46 | 51 hrs 48 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:28:53|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|