RESEARCH: CANCER
FOLDING PROJECT #16479 PROFILE
PROJECT TEAM
Manager(s): Sukrit SinghInstitution: Memorial Sloan-Kettering Cancer-Center
Project URL: View Project Website
WORK UNIT INFO
Atoms: 187,583Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies Menin, a protein important for controlling cell growth in hormone-producing glands. Researchers are using computer models to understand how small molecules can block Menin's activity and how mutations in Menin affect this interaction. This knowledge could lead to new cancer treatments.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
In cancer treatment it is common to target multiple different putative proteins, because multiple proteins can malfunction in tumors to drive cancer.
One such protein, particularly known to be important in endocrine gland tumors (the places where hormones are secreted), is Menin-1 (Menin).
Menin is a protein found in the nucleus protein and plays a key role in regulating cell-signaling and gene expression (which genes turn on and off).
While the explicit details of Menin's behavior are not known, targeting it's inhibition with small-molecules (ligands) has demonstrated promising potential in blocking tumor growth.
However, like with many disease, mutations within Menin can *also* counteract this ligand-binding behavior.
Therefore, it is not just important to study how Menin works, or how to target it with small molecules, but also how mutations impact Menin-Ligand interactions.
This set of projects seeks to answer the latter two questions - how do small molecules inhibit Menin and how do mutations within Menin alter small-molecule affinity.
In projects 16472 & 16473, we simulate Menin by itself and Menin bound to a known small molecule inhibitor that is shown to treat tumors in patients! Thanks to the powerhouse efforts at cataloguing cancer mutations at Memorial Sloan-Kettering, we also know of 3 mutations that impact the ability of Menin to bind this inhibitor.
Projects 16474–16483 simulate either a) each of these Menin mutants or b) Menin mutants bound to this inhibitor. Bonus: Some of these structures are being simulated with the help of the AlphaFold database!.
RELATED TERMS GLOSSARY AI BETA
Menin
A protein found in the nucleus that regulates cell signaling and gene expression.
Menin is a crucial protein located inside the cell's nucleus. It plays a vital role in controlling how cells communicate with each other and which genes are turned on or off. Researchers are particularly interested in Menin because it can be affected by mutations, potentially contributing to the development of cancer.
Small-molecules
Molecules used in medications to target specific biological processes.
Small-molecules are tiny chemical compounds that can interact with and influence biological processes within the body. In medicine, they're often used as drugs to treat diseases like cancer by targeting specific proteins or pathways involved in disease development.
Ligands
Molecules that bind to specific proteins, often with a therapeutic effect.
Ligands are molecules that have a strong attraction to other molecules, like proteins. In medicine, they're often designed to specifically bind to disease-causing proteins, blocking their harmful activity or triggering beneficial effects.
Mutations
Permanent alterations in the DNA sequence of a gene.
Mutations are changes that occur in our DNA, the instruction manual for our cells. These changes can be caused by various factors and sometimes lead to diseases like cancer. In cancer, mutations often disrupt normal cellular processes, allowing uncontrolled growth and spread.
AlphaFold
A deep learning algorithm for predicting protein structures.
AlphaFold is a powerful computer program that uses artificial intelligence to predict the 3D shapes of proteins. This information is crucial for understanding how proteins function and designing new drugs.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:31:17|
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 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 6,787,511 | 492,995 | 13.77 | 1 hrs 45 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,478,348 | 487,927 | 13.28 | 1 hrs 48 mins |
| 3 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,659,323 | 468,351 | 12.08 | 1 hrs 59 mins |
| 4 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,475,848 | 460,582 | 11.89 | 2 hrs 1 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,892,655 | 446,239 | 10.96 | 2 hrs 11 mins |
| 6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,743,314 | 435,726 | 10.89 | 2 hrs 12 mins |
| 7 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,706,510 | 440,512 | 10.68 | 2 hrs 15 mins |
| 8 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,341,879 | 393,490 | 8.49 | 2 hrs 50 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,334,269 | 390,071 | 8.55 | 2 hrs 48 mins |
| 10 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 2,883,670 | 379,986 | 7.59 | 3 hrs 10 mins |
| 11 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,762,919 | 369,331 | 7.48 | 3 hrs 12 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,761,168 | 370,334 | 7.46 | 3 hrs 13 mins |
| 13 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,613,129 | 362,684 | 7.20 | 3 hrs 20 mins |
| 14 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,529,843 | 358,878 | 7.05 | 3 hrs 24 mins |
| 15 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,208,550 | 342,879 | 6.44 | 3 hrs 44 mins |
| 16 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 2,171,053 | 339,627 | 6.39 | 3 hrs 45 mins |
| 17 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,126,873 | 337,475 | 6.30 | 3 hrs 48 mins |
| 18 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,084,546 | 336,376 | 6.20 | 3 hrs 52 mins |
| 19 | TITAN X GP102 [TITAN X] 6144 |
Nvidia | GP102 | 2,078,968 | 335,623 | 6.19 | 3 hrs 52 mins |
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|
|||||||
| 20 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,052,308 | 333,143 | 6.16 | 3 hrs 54 mins |
| 21 | Radeon VII Vega 20 [Radeon VII] 13,284 |
AMD | Vega 20 | 1,812,530 | 321,229 | 5.64 | 4 hrs 15 mins |
| 22 | GeForce RTX 3070 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,729,721 | 316,528 | 5.46 | 4 hrs 24 mins |
| 23 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,704,412 | 305,760 | 5.57 | 4 hrs 18 mins |
| 24 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,679,706 | 313,134 | 5.36 | 4 hrs 28 mins |
| 25 | Tesla P40 GP102GL [Tesla P40] 11760 |
Nvidia | GP102GL | 1,671,028 | 311,133 | 5.37 | 4 hrs 28 mins |
| 26 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,633,060 | 311,210 | 5.25 | 4 hrs 34 mins |
| 27 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,542,075 | 303,964 | 5.07 | 4 hrs 44 mins |
| 28 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,373,882 | 292,845 | 4.69 | 5 hrs 7 mins |
| 29 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,272,723 | 284,212 | 4.48 | 5 hrs 22 mins |
| 30 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 1,251,341 | 283,892 | 4.41 | 5 hrs 27 mins |
| 31 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,157,934 | 277,179 | 4.18 | 5 hrs 45 mins |
| 32 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,151,588 | 258,588 | 4.45 | 5 hrs 23 mins |
| 33 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,135,277 | 271,262 | 4.19 | 5 hrs 44 mins |
| 34 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 1,006,487 | 260,352 | 3.87 | 6 hrs 12 mins |
| 35 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,000,949 | 156,684 | 6.39 | 3 hrs 45 mins |
| 36 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 932,610 | 257,585 | 3.62 | 6 hrs 38 mins |
| 37 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 743,858 | 240,463 | 3.09 | 7 hrs 46 mins |
| 38 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 699,171 | 233,902 | 2.99 | 8 hrs 2 mins |
| 39 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 597,366 | 221,528 | 2.70 | 8 hrs 54 mins |
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|
|||||||
| 40 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 512,213 | 211,002 | 2.43 | 9 hrs 53 mins |
| 41 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 462,617 | 202,184 | 2.29 | 10 hrs 29 mins |
| 42 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 338,954 | 132,826 | 2.55 | 9 hrs 24 mins |
| 43 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 293,077 | 172,619 | 1.70 | 14 hrs 8 mins |
| 44 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 284,340 | 173,292 | 1.64 | 14 hrs 38 mins |
| 45 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 275,676 | 171,202 | 1.61 | 14 hrs 54 mins |
| 46 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 257,397 | 144,493 | 1.78 | 13 hrs 28 mins |
| 47 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 252,296 | 166,265 | 1.52 | 15 hrs 49 mins |
| 48 | GeForce GTX 670/GTX 760Ti OEM GK104 [GeForce GTX 670/GTX 760Ti OEM] 2634 |
Nvidia | GK104 | 241,390 | 164,441 | 1.47 | 16 hrs 21 mins |
| 49 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 213,537 | 157,735 | 1.35 | 17 hrs 44 mins |
| 50 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 207,504 | 151,602 | 1.37 | 17 hrs 32 mins |
| 51 | Radeon RX Vega M XL [Radeon RX Vega M XL] |
AMD | Vega | 168,488 | 134,782 | 1.25 | 19 hrs 12 mins |
| 52 | GRID M40 GM107GL [GRID M40] |
Nvidia | GM107GL | 103,723 | 113,293 | 0.92 | 26 hrs 13 mins |
| 53 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 94,899 | 120,424 | 0.79 | 30 hrs 27 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:31:17|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|