RESEARCH: CANCER
FOLDING PROJECT #16476 PROFILE

PROJECT TEAM

Manager(s): Sukrit Singh
Institution: Memorial Sloan-Kettering Cancer-Center
Project URL: View Project Website

WORK UNIT INFO

Atoms: 187,564
Core: OPENMM_22
Status: Public

TLDR; PROJECT SUMMARY AI BETA

Cancer often involves many faulty proteins. This project focuses on Menin, a protein important for hormone-producing tumors. Researchers will use computer models to study how drugs block Menin and how cancer mutations affect this interaction. This could lead to better treatments for these types of cancers.

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

Note: Glossary items are a high level summary and may not be 100% accurate.

Menin

A protein found in the nucleus that plays a key role in regulating cell-signaling and gene expression.

Protein: Biotechnology
Oncology / Tumor Biology

Menin is a crucial protein located within the cell's nucleus. It's responsible for controlling how cells communicate with each other and which genes are turned on or off. This makes Menin vital for normal cell growth and function. In cancer, mutations in Menin can disrupt its activity, contributing to tumor development.


Ligands

Molecules that bind to a specific target (e.g., protein) and elicit a biological response.

Chemical Compound: Biotechnology
Pharmacology / Drug Discovery

Ligands are molecules that attach to specific targets within the body, like proteins. When they bind, they can trigger various biological effects. In drug development, ligands are often designed to interact with disease-causing proteins, aiming to treat or prevent illness.


Mutations

Permanent alterations in the DNA sequence.

Genetic Change: Biotechnology
Genetics / Oncogenomics

Mutations are changes in the DNA code that makes up our genes. These changes can occur spontaneously or be caused by environmental factors like radiation. While some mutations are harmless, others can disrupt gene function and lead to diseases like cancer.


AlphaFold

An AI system that predicts the 3D structure of proteins from their amino acid sequence.

Database: Biotechnology
Bioinformatics / Protein Structure Prediction

AlphaFold is a powerful artificial intelligence tool used to predict the shape of proteins based on their building blocks (amino acids). Understanding protein structure is crucial for drug discovery and other biological research.

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 7,193,197 506,539 14.20 1 hrs 41 mins
2 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 5,896,334 475,696 12.40 1 hrs 56 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 5,778,418 467,078 12.37 1 hrs 56 mins
4 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,751,004 454,046 12.67 1 hrs 54 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,902,907 447,972 10.94 2 hrs 12 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,887,008 445,982 10.96 2 hrs 11 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,381,935 430,717 10.17 2 hrs 22 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,467,369 398,851 8.69 2 hrs 46 mins
9 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 3,464,494 399,655 8.67 2 hrs 46 mins
10 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,825,603 370,012 7.64 3 hrs 9 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,688,907 366,816 7.33 3 hrs 16 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,656,771 366,245 7.25 3 hrs 19 mins
13 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 2,642,650 364,723 7.25 3 hrs 19 mins
14 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,516,474 359,140 7.01 3 hrs 26 mins
15 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,478,731 357,056 6.94 3 hrs 27 mins
16 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,247,926 345,868 6.50 3 hrs 42 mins
17 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 2,181,421 342,845 6.36 3 hrs 46 mins
18 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,114,714 336,573 6.28 3 hrs 49 mins
19 TITAN X
GP102 [TITAN X] 6144
Nvidia GP102 2,071,967 335,534 6.18 3 hrs 53 mins
20 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,955,910 330,512 5.92 4 hrs 3 mins
21 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,741,696 316,745 5.50 4 hrs 22 mins
22 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,737,687 317,407 5.47 4 hrs 23 mins
23 Tesla P40
GP102GL [Tesla P40] 11760
Nvidia GP102GL 1,692,524 314,111 5.39 4 hrs 27 mins
24 Radeon VII
Vega 20 [Radeon VII] 13,284
AMD Vega 20 1,598,802 302,492 5.29 4 hrs 32 mins
25 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,543,633 304,160 5.08 4 hrs 44 mins
26 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,480,991 273,495 5.42 4 hrs 26 mins
27 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,355,421 291,947 4.64 5 hrs 10 mins
28 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,316,550 289,586 4.55 5 hrs 17 mins
29 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,274,235 285,520 4.46 5 hrs 23 mins
30 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,237,185 281,411 4.40 5 hrs 28 mins
31 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q] 4550
Nvidia TU106M 1,204,886 281,136 4.29 5 hrs 36 mins
32 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,180,338 279,064 4.23 5 hrs 40 mins
33 Radeon RX 5600 OEM/5600 XT/5700/5700 XT
Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]
AMD Navi 10 1,154,970 262,531 4.40 5 hrs 27 mins
34 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,070,741 241,034 4.44 5 hrs 24 mins
35 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 1,020,122 251,650 4.05 5 hrs 55 mins
36 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 911,731 255,476 3.57 6 hrs 44 mins
37 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 763,597 241,498 3.16 7 hrs 35 mins
38 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 702,253 234,609 2.99 8 hrs 1 mins
39 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 604,123 223,483 2.70 8 hrs 53 mins
40 P106-100
GP106 [P106-100]
Nvidia GP106 510,731 211,044 2.42 9 hrs 55 mins
41 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 465,224 205,175 2.27 10 hrs 35 mins
42 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 439,566 198,920 2.21 10 hrs 52 mins
43 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 358,740 144,134 2.49 9 hrs 39 mins
44 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 356,050 135,164 2.63 9 hrs 7 mins
45 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 311,398 179,496 1.73 13 hrs 50 mins
46 P106-090
GP106 [P106-090]
Nvidia GP106 288,299 174,623 1.65 14 hrs 32 mins
47 GeForce GTX 1050 Ti Mobile
GP107M [GeForce GTX 1050 Ti Mobile]
Nvidia GP107M 252,373 159,586 1.58 15 hrs 11 mins
48 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 252,243 166,545 1.51 15 hrs 51 mins
49 Radeon R9 200/300 Series
Hawaii [Radeon R9 200/300 Series]
AMD Hawaii 157,775 85,875 1.84 13 hrs 4 mins
50 Radeon HD 7800 Series
Pitcairn PRO [Radeon HD 7800 Series]
AMD Pitcairn PRO 99,704 121,212 0.82 29 hrs 11 mins
51 GeForce GTX 960M
GM107 [GeForce GTX 960M] 1439
Nvidia GM107 63,787 76,290 0.84 28 hrs 42 mins
52 Radeon RX Vega gfx902
raven [Radeon RX Vega gfx902]
AMD raven 11,946 70,811 0.17 142 hrs 16 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