RESEARCH: PROTEIN-DYNAMICS-DATASET
FOLDING PROJECT #17653 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 70,000
Core: 0x26
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

The project wants to create a huge dataset of moving proteins. This will help AI learn how proteins work. The dataset will include small, medium, and large proteins with different shapes.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

With the explosion of AI-based models and architectures, a ripe opportunity presents itself to use these statistical models to help us bridge the gap large scale simulations and functional insight.

In particular, with the explosion of methods like AlphaFold2, there is a clear potential for these models to potentially predict dynamics, or use them to predict different conformations of a system at extremely large scales for a diverse set of sequences. However, for folks to be able to generate those kinds of models, a broad set of training data is needed that captures dynamics across a variety of different protein topologies.

This project seeks to generate that dataset - capturing dynamics of systems across a variety of different protein sizes and topologies.

17651: Small proteins (20,000 atoms)
17652: medium sized proteins (40,000 atoms)
17653: Large sized proteins (70,000 atoms).

RELATED TERMS GLOSSARY AI BETA

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

AlphaFold2

A deep learning algorithm for protein structure prediction

Technical: Pharmaceuticals
Biotechnology / Protein Structure Prediction

AlphaFold2 is a powerful AI system that can predict the 3D shape of proteins from their amino acid sequence. This has revolutionized protein research by allowing scientists to understand how proteins fold and function.


Protein

A large biomolecule composed of chains of amino acids.

Scientific: Biopharmaceuticals
Biotechnology / Structural Biology

Proteins are the workhorses of our cells, carrying out a vast array of functions such as catalyzing reactions, transporting molecules, and providing structural support. Their shape is crucial to their function.


Topology

The arrangement of atoms or parts in a molecule.

Scientific: Biopharmaceuticals
Biotechnology / Structural Biology

Protein topology refers to the 3D arrangement of amino acids within a protein molecule. Understanding protein topology is essential for comprehending how proteins fold and interact with other molecules.


Dynamics

The movement and changes in shape of molecules over time.

Scientific: Biopharmaceuticals
Biotechnology / Structural Biology

Protein dynamics refers to the constant motion and flexibility of proteins. This dynamic behavior is crucial for protein function, allowing them to interact with other molecules and carry out their roles.


Conformation

A specific three-dimensional arrangement of a molecule.

Scientific: Biopharmaceuticals
Biotechnology / Structural Biology

A protein's conformation is its unique 3D shape. Proteins can exist in different conformations, and these changes are often involved in their function.


Amino Acid

The building blocks of proteins.

Scientific: Biopharmaceuticals
Biotechnology / Molecular Biology

Amino acids are organic molecules that link together to form polypeptide chains, which then fold into proteins. There are 20 different amino acids commonly found in proteins.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:37:27
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 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 17,304,432 20,450 846.18 0 hrs 2 mins
2 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 15,995,482 21,861 731.69 0 hrs 2 mins
3 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 13,417,039 593,874 22.59 1 hrs 4 mins
4 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 13,385,646 149,379 89.61 0 hrs 16 mins
5 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 13,005,572 33,342 390.07 0 hrs 4 mins
6 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 11,474,295 20,450 561.09 0 hrs 3 mins
7 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 8,223,984 20,450 402.15 0 hrs 4 mins
8 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 6,571,292 216,237 30.39 0 hrs 47 mins
9 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 6,362,725 20,450 311.14 0 hrs 5 mins
10 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 6,154,054 182,586 33.70 0 hrs 43 mins
11 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,134,336 209,134 29.33 0 hrs 49 mins
12 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 5,240,419 434,962 12.05 1 hrs 60 mins
13 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 5,225,731 20,450 255.54 0 hrs 6 mins
14 RTX 4000 SFF Ada Generation
AD104GL [RTX 4000 SFF Ada Generation]
Nvidia AD104GL 4,674,241 20,450 228.57 0 hrs 6 mins
15 Radeon RX 6800/6800XT/6900XT
Navi 21 [Radeon RX 6800/6800XT/6900XT]
AMD Navi 21 4,298,914 105,396 40.79 0 hrs 35 mins
16 Radeon RX 7700XT/7800XT
Navi 32 [Radeon RX 7700XT/7800XT]
AMD Navi 32 3,925,928 20,450 191.98 0 hrs 8 mins
17 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,160,531 24,468 129.17 0 hrs 11 mins
18 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,463,068 20,450 120.44 0 hrs 12 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,445,719 155,364 15.74 1 hrs 31 mins
20 Radeon RX 6700/6700XT/6800M
Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M]
AMD Navi 22 XT-XL 2,408,383 56,600 42.55 0 hrs 34 mins
21 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,046,224 117,597 17.40 1 hrs 23 mins
22 GeForce RTX 3050 8GB
GA107 [GeForce RTX 3050 8GB]
Nvidia GA107 1,573,246 133,341 11.80 2 hrs 2 mins
23 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,481,825 131,618 11.26 2 hrs 8 mins
24 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,426,748 20,450 69.77 0 hrs 21 mins
25 RX 5600 OEM/5600XT/5700/5700XT
Navi 10 [RX 5600 OEM/5600XT/5700/5700XT]
AMD Navi 10 1,391,373 20,450 68.04 0 hrs 21 mins
26 GeForce RTX 3050 Ti Mobile
GA107M [GeForce RTX 3050 Ti Mobile]
Nvidia GA107M 1,187,455 122,497 9.69 2 hrs 29 mins
27 RTX A1000
GA107GL [RTX A1000]
Nvidia GA107GL 1,175,007 20,450 57.46 0 hrs 25 mins
28 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 1,160,676 20,450 56.76 0 hrs 25 mins
29 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,124,494 20,450 54.99 0 hrs 26 mins
30 P106-100
GP106 [P106-100]
Nvidia GP106 851,607 109,988 7.74 3 hrs 6 mins
31 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 820,706 20,450 40.13 0 hrs 36 mins
32 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 761,989 20,450 37.26 0 hrs 39 mins
33 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 683,175 100,560 6.79 3 hrs 32 mins
34 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 661,580 20,450 32.35 0 hrs 45 mins
35 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 638,637 20,450 31.23 0 hrs 46 mins
36 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 613,685 20,450 30.01 0 hrs 48 mins
37 R9 Fury X/NANO
Fiji XT [R9 Fury X/NANO]
AMD Fiji XT 525,367 20,450 25.69 0 hrs 56 mins
38 RX 470/480/570/580/590
Ellesmere XT [RX 470/480/570/580/590]
AMD Ellesmere XT 506,034 73,865 6.85 3 hrs 30 mins
39 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 475,479 85,555 5.56 4 hrs 19 mins
40 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 472,061 20,450 23.08 1 hrs 2 mins
41 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 379,306 83,330 4.55 5 hrs 16 mins
42 R9 380X/R9 M295X
Tonga XT/Amethyst XT [R9 380X/R9 M295X]
AMD Tonga XT/Amethyst XT 267,393 75,462 3.54 6 hrs 46 mins
43 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 257,410 70,088 3.67 6 hrs 32 mins
44 RX Vega M GL
Polaris 22 XL [RX Vega M GL]
AMD Polaris 22 XL 210,979 20,450 10.32 2 hrs 20 mins
45 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 191,019 66,611 2.87 8 hrs 22 mins
46 Radeon RX 460/560D
Baffin [Radeon RX 460/560D]
AMD Baffin 156,775 20,450 7.67 3 hrs 8 mins
47 Ryzen 7000 Series iGPU
Raphael [Ryzen 7000 Series iGPU]
AMD Raphael 121,060 37,593 3.22 7 hrs 27 mins
48 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 104,076 54,470 1.91 12 hrs 34 mins
49 Vega Mobile APU
Lucienne [Vega Mobile APU]
AMD Lucienne 12,781 23,766 0.54 44 hrs 38 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:37:27
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 CORE I7-8705G CPU @ 3.10GHZ 8 Intel