RESEARCH: CANCER
FOLDING PROJECT #16475 PROFILE
PROJECT TEAM
Manager(s): Sukrit SinghInstitution: Memorial Sloan-Kettering Cancer-Center
Project URL: View Project Website
WORK UNIT INFO
Atoms: 187,489Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project explores how small molecules block the growth of cancer cells by targeting a protein called Menin. Researchers are using computer simulations to understand how these molecules interact with Menin and how changes in Menin's structure affect this binding. The goal is to find ways to overcome resistance to treatment caused by mutations in Menin.
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 tumor suppressor protein involved in gene expression regulation.
Menin is a protein found in the nucleus of cells and plays a crucial role in regulating cell signaling and gene expression. It helps control which genes are turned on or off, impacting various cellular processes. In cancer treatment, Menin is a target because its malfunction can contribute to tumor growth. Targeting Menin with small molecules has shown promise in blocking tumor development.
Tumor
An abnormal mass of tissue that can be benign or malignant.
A tumor is an abnormal growth of cells in the body. It can be benign (non-cancerous) and grow slowly without spreading, or it can be malignant (cancerous), invading surrounding tissues and potentially spreading to other parts of the body.
Protein
Large biomolecules essential for various biological functions.
Proteins are complex molecules made up of chains of amino acids. They perform diverse functions in living organisms, including catalyzing biochemical reactions, transporting molecules, providing structural support, and regulating cell processes.
Small Molecule
A molecule with a low molecular weight that can interact with biological targets.
Small molecules are organic compounds with relatively low molecular weights. They are often used as drugs because they can bind to specific proteins in the body, altering their function and producing therapeutic effects.
Mutation
A permanent alteration in the DNA sequence.
Mutations are changes in the DNA sequence that can occur spontaneously or be induced by environmental factors. They can alter gene function and contribute to diseases like cancer.
Gene Expression
The process by which information encoded in DNA is used to synthesize RNA and proteins.
Gene expression is the intricate process by which the instructions stored in our DNA are converted into functional molecules like proteins. It involves two main steps: transcription (copying DNA into RNA) and translation (using RNA to build proteins). This process is tightly regulated and essential for all cellular functions.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:31:19|
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 | 6,918,173 | 495,951 | 13.95 | 1 hrs 43 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,316,955 | 479,569 | 13.17 | 1 hrs 49 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,770,711 | 467,110 | 12.35 | 1 hrs 57 mins |
| 4 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,756,332 | 469,034 | 12.27 | 1 hrs 57 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,732,819 | 439,826 | 10.76 | 2 hrs 14 mins |
| 6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,598,775 | 434,490 | 10.58 | 2 hrs 16 mins |
| 7 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,281,832 | 424,658 | 10.08 | 2 hrs 23 mins |
| 8 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,326,512 | 390,810 | 8.51 | 2 hrs 49 mins |
| 9 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,280,094 | 389,585 | 8.42 | 2 hrs 51 mins |
| 10 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,842,018 | 371,810 | 7.64 | 3 hrs 8 mins |
| 11 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 2,759,786 | 366,742 | 7.53 | 3 hrs 11 mins |
| 12 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 2,629,800 | 359,757 | 7.31 | 3 hrs 17 mins |
| 13 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,605,464 | 360,338 | 7.23 | 3 hrs 19 mins |
| 14 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,450,542 | 353,549 | 6.93 | 3 hrs 28 mins |
| 15 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,414,674 | 351,256 | 6.87 | 3 hrs 29 mins |
| 16 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,336,565 | 345,865 | 6.76 | 3 hrs 33 mins |
| 17 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,174,818 | 339,493 | 6.41 | 3 hrs 45 mins |
| 18 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 2,104,233 | 336,681 | 6.25 | 3 hrs 50 mins |
| 19 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,072,625 | 332,805 | 6.23 | 3 hrs 51 mins |
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|
|||||||
| 20 | GeForce RTX 3070 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 2,058,075 | 332,759 | 6.18 | 3 hrs 53 mins |
| 21 | TITAN X GP102 [TITAN X] 6144 |
Nvidia | GP102 | 2,043,654 | 332,134 | 6.15 | 3 hrs 54 mins |
| 22 | Radeon VII Vega 20 [Radeon VII] 13,284 |
AMD | Vega 20 | 1,773,236 | 317,078 | 5.59 | 4 hrs 17 mins |
| 23 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,718,174 | 313,055 | 5.49 | 4 hrs 22 mins |
| 24 | Tesla P40 GP102GL [Tesla P40] 11760 |
Nvidia | GP102GL | 1,702,088 | 312,828 | 5.44 | 4 hrs 25 mins |
| 25 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,699,895 | 312,499 | 5.44 | 4 hrs 25 mins |
| 26 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,376,103 | 291,661 | 4.72 | 5 hrs 5 mins |
| 27 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,233,191 | 272,308 | 4.53 | 5 hrs 18 mins |
| 28 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,169,511 | 269,612 | 4.34 | 5 hrs 32 mins |
| 29 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,160,486 | 275,536 | 4.21 | 5 hrs 42 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 | 1,159,434 | 273,967 | 4.23 | 5 hrs 40 mins |
| 31 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 1,012,817 | 249,058 | 4.07 | 5 hrs 54 mins |
| 32 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 932,723 | 256,059 | 3.64 | 6 hrs 35 mins |
| 33 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 755,152 | 233,594 | 3.23 | 7 hrs 25 mins |
| 34 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 746,561 | 238,002 | 3.14 | 7 hrs 39 mins |
| 35 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 738,045 | 236,902 | 3.12 | 7 hrs 42 mins |
| 36 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 703,664 | 233,628 | 3.01 | 7 hrs 58 mins |
| 37 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 692,679 | 231,971 | 2.99 | 8 hrs 2 mins |
| 38 | Radeon RX 6600/6600 XT/6600M Navi 23 [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 | 463,045 | 202,447 | 2.29 | 10 hrs 30 mins |
| 39 | Quadro T2000 Mobile / Max-Q TU117GLM [Quadro T2000 Mobile / Max-Q] |
Nvidia | TU117GLM | 461,433 | 203,343 | 2.27 | 10 hrs 35 mins |
|
|
|||||||
| 40 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 412,911 | 194,421 | 2.12 | 11 hrs 18 mins |
| 41 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 294,617 | 173,931 | 1.69 | 14 hrs 10 mins |
| 42 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 289,295 | 173,233 | 1.67 | 14 hrs 22 mins |
| 43 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 251,850 | 166,111 | 1.52 | 15 hrs 50 mins |
| 44 | GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile] |
Nvidia | GP107M | 203,769 | 154,576 | 1.32 | 18 hrs 12 mins |
| 45 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 134,674 | 134,542 | 1.00 | 23 hrs 59 mins |
| 46 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 132,551 | 133,921 | 0.99 | 24 hrs 15 mins |
| 47 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 114,080 | 127,460 | 0.90 | 26 hrs 49 mins |
| 48 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 98,723 | 92,470 | 1.07 | 22 hrs 29 mins |
| 49 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 94,111 | 119,491 | 0.79 | 30 hrs 28 mins |
| 50 | GRID M40 GM107GL [GRID M40] |
Nvidia | GM107GL | 80,206 | 113,438 | 0.71 | 33 hrs 57 mins |
| 51 | Radeon WX 3100 [Radeon WX 3100] |
AMD | 78,469 | 112,409 | 0.70 | 34 hrs 23 mins | |
| 52 | Radeon RX Vega gfx902 raven [Radeon RX Vega gfx902] |
AMD | raven | 9,496 | 69,680 | 0.14 | 176 hrs 6 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:31:19|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|