RESEARCH: ALZHEIMERS
FOLDING PROJECT #18263 PROFILE

PROJECT TEAM

Manager(s): Justin Miller
Institution: University of Pennsylvania

WORK UNIT INFO

Atoms: 1,224,788
Core: 0x27
Status: Public

TLDR; PROJECT SUMMARY AI BETA

Alzheimer's disease is bad for your memory and there's no cure. This project studies tau protein, which gets tangled up in Alzheimer's brains. Scientists are using computer models to see how different settings in the model affect how well it mimics real tau protein. They hope this will help everyone studying these tricky proteins.

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

OFFICAL PROJECT DESCRIPTION

Alzheimer's disease is a significant cause of death and memory loss and there are no effective treatments to halt or reverse disease progression.

One of the late hallmarks and primary biomarkers of Alzheimer's disease is the presence of neurofibrillary tangles, intracellular aggregates of the tau protein.

When behaving properly, tau interacts with microtubules- a critical portion of the cytoskeleton of cells- to help regulate their growth and stability.

However, tau misbehavior and aggregation is also closely linked to Alzheimer's disease among many other neurodegenerative diseases. Studying tau experimentally has been difficult as it is an Intrinsically Disordered Protein (IDP).

As such, traditional structural biology approaches are unable to capture the conformational states of tau in atomistic detail.

Recently, our collaborators have utilized single molecule FRET experiments to experimentally characterize tau by measuring the pairwise distance between different regions.

While simulations of tau could provide atomistic detail of the tau conformational ensemble, historically simulations of IDPs have been challenging as force fields (the parameters which govern the underlying physics of a simulation) and their accompyning models of waters have favored well-folded proteins.

In this project series we embark on an effort to characterize which force field and water models most accurately recapitulate tau experimental results.

We believe these findings will be broadly applicable to all researchers studying intrinsically disordered proteins, and aspire to keep performing these benchmarking simulations as new force field and waters are released.

We also expect these simulations to yield useful information about the tau conformational ensemble. N.B.

because tau is an intrinsically disordered protein, it can fully unfold and refold quite rapidly.

To ensure the protein remains in water the entire simulation, we have included a large number of waters in the system.

As a result these simulations are a good deal more RAM intensive than prior FAH simulations.

Accordingly, we have implemented a minimum system memory requirement of 8000 MiB to run 182[51-56,58,61,62].

and 12000 MiB to run 182[57,60] p18251 - amber99sb-disp with tip4pd water p18255- amber14sb with tip3p water p18256- amber03 with tip3p water p18257- amber19sb with opc water p18258- amber19sb with opc3 water p18260- amber99sb-star-ILDN with tip4p water p18261- amber19sb with opc3 pol water p18262 - charmm36m with tip3p water p18263 - amber99sb-star-ILDN with tip4pd water.

RELATED TERMS GLOSSARY AI BETA

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

Alzheimer's disease

A progressive neurodegenerative disease characterized by memory loss and cognitive decline.

Disease: Healthcare
Medicine / Neurology

Alzheimer's disease is a serious brain disorder that causes memory problems, thinking difficulties, and changes in behavior. It affects millions of people worldwide and currently has no cure. Researchers are working hard to understand the disease and develop effective treatments.


Neurofibrillary tangles

Abnormal accumulations of tau protein inside nerve cells.

Biological feature: Healthcare
Medicine / Neuropathology

Neurofibrillary tangles are a hallmark of Alzheimer's disease. They are clumps of twisted fibers made up of a protein called tau that build up inside brain cells. These tangles disrupt normal cell function and contribute to the progression of the disease.


Tau protein

A protein that helps stabilize microtubules in nerve cells.

Protein: Healthcare
Medicine / Neurobiology

Tau is a protein crucial for the healthy function of brain cells. It plays a vital role in maintaining the structure and stability of microtubules, which are essential for transporting nutrients and other materials within neurons. In Alzheimer's disease, tau becomes abnormal and forms tangles, disrupting normal cell function.


Microtubules

Hollow tubes made of protein that help maintain cell shape and transport materials.

Cellular Structure: Biotechnology
Biology / Cell Biology

Microtubules are essential components of the cytoskeleton, a network of protein fibers that provides structure and support to cells. They play a crucial role in various cellular processes, including cell division, movement, and the transport of organelles and other molecules.


Cytoskeleton

A network of protein fibers that provides support and shape to cells.

Cellular Structure: Biotechnology
Biology / Cell Biology

The cytoskeleton is a dynamic network of protein filaments that extends throughout the cytoplasm of cells. It plays a vital role in maintaining cell shape, facilitating movement, transporting materials within cells, and organizing cellular structures.


Intrinsically Disordered Protein (IDP)

A protein that lacks a stable three-dimensional structure.

Protein type: Biotechnology
Biochemistry / Structural Biology

Intrinsically disordered proteins (IDPs) are unique because they don't have a fixed shape. Unlike most proteins, which fold into specific structures, IDPs exist in a flexible and dynamic state. This allows them to interact with other molecules in various ways and perform diverse functions.


Single molecule FRET experiments

A method used to study the distance between two molecules in real time.

Experimental technique: Biotechnology
Biophysics / Structural Biology

Single molecule FRET experiments involve attaching fluorescent tags to specific molecules and measuring the energy transfer between them. By analyzing the changes in fluorescence, researchers can determine the distance between the tagged molecules and gain insights into their interactions and dynamics.


Force field

A set of mathematical equations that describe the interactions between atoms in a simulation.

Computational model: Biotechnology
Computational Biology / Molecular Dynamics

Force fields are essential components of molecular dynamics simulations. They provide the rules governing how atoms interact with each other, allowing researchers to simulate the behavior of molecules over time.


Water models

Representations of water molecules used in simulations.

Computational model: Biotechnology
Computational Biology / Molecular Dynamics

Water models are crucial for accurately simulating biological systems. They capture the dynamic behavior of water molecules and their interactions with other atoms.


Atomistic detail

A level of detail that represents individual atoms in a simulation.

Specificity level: Biotechnology
Computational Biology / Molecular Dynamics

Atomistic detail refers to the ability of a simulation to capture the movements and interactions of individual atoms. It allows researchers to study complex molecular systems at a very precise level.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:30:35
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 RTX PRO 6000 Blackwell Workstation Edition
GB202GL [RTX PRO 6000 Blackwell Workstation Edition]
Nvidia GB202GL 65,929,554 671,614 98.17 0 hrs 15 mins
2 GeForce RTX 5090
GB202 [GeForce RTX 5090]
Nvidia GB202 46,497,820 671,614 69.23 0 hrs 21 mins
3 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 24,657,413 864,472 28.52 0 hrs 50 mins
4 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 21,517,070 671,614 32.04 0 hrs 45 mins
5 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 19,715,468 2,899,602 6.80 3 hrs 32 mins
6 GeForce RTX 5090 Max-Q / Mobile
GB203M / GN22 [GeForce RTX 5090 Max-Q / Mobile]
Nvidia GB203M / GN22 17,581,647 671,614 26.18 0 hrs 55 mins
7 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 17,493,013 1,864,586 9.38 2 hrs 33 mins
8 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 17,271,556 893,050 19.34 1 hrs 14 mins
9 GeForce RTX 4070 Ti SUPER
AD103 [GeForce RTX 4070 Ti SUPER]
Nvidia AD103 13,382,102 700,362 19.11 1 hrs 15 mins
10 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 11,374,023 671,614 16.94 1 hrs 25 mins
11 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 10,141,623 1,818,543 5.58 4 hrs 18 mins
12 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 10,081,855 1,905,475 5.29 4 hrs 32 mins
13 GeForce RTX 4090 Laptop GPU
AD103M / GN21-X11 [GeForce RTX 4090 Laptop GPU]
Nvidia AD103M / GN21-X11 9,276,494 671,614 13.81 1 hrs 44 mins
14 GeForce RTX 3080 12GB
GA102 [GeForce RTX 3080 12GB]
Nvidia GA102 9,020,472 671,614 13.43 1 hrs 47 mins
15 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 8,229,465 1,049,697 7.84 3 hrs 4 mins
16 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 8,072,224 717,660 11.25 2 hrs 8 mins
17 GeForce RTX 3090 Ti
GA102 [GeForce RTX 3090 Ti]
Nvidia GA102 7,880,028 671,614 11.73 2 hrs 3 mins
18 GeForce RTX 4070 Ti SUPER
AD102 [GeForce RTX 4070 Ti SUPER]
Nvidia AD102 7,795,647 671,614 11.61 2 hrs 4 mins
19 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,693,380 797,586 9.65 2 hrs 29 mins
20 Radeon PRO W7900 Dual Slot
Navi 31 [Radeon PRO W7900 Dual Slot]
AMD Navi 31 7,616,499 671,614 11.34 2 hrs 7 mins
21 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 7,581,893 671,614 11.29 2 hrs 8 mins
22 GeForce RTX 5060 Ti
GB206 [GeForce RTX 5060 Ti]
Nvidia GB206 7,555,166 671,614 11.25 2 hrs 8 mins
23 GeForce RTX 5070 Ti Mobile
GB205M [GeForce RTX 5070 Ti Mobile]
Nvidia GB205M 6,615,372 671,614 9.85 2 hrs 26 mins
24 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 6,453,244 671,614 9.61 2 hrs 30 mins
25 Radeon RX 9070(XT)
Navi 48 [Radeon RX 9070(XT)]
AMD Navi 48 6,018,793 892,171 6.75 3 hrs 33 mins
26 GeForce RTX 5060
GB206 [GeForce RTX 5060]
Nvidia GB206 5,743,449 671,614 8.55 2 hrs 48 mins
27 GeForce RTX 4060 Ti
AD104 [GeForce RTX 4060 Ti]
Nvidia AD104 5,595,251 671,614 8.33 2 hrs 53 mins
28 Radeon RX 6800(XT)/6900XT
Navi 21 [Radeon RX 6800(XT)/6900XT]
AMD Navi 21 5,512,196 932,634 5.91 4 hrs 4 mins
29 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 5,317,086 967,122 5.50 4 hrs 22 mins
30 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,866,311 1,484,141 3.28 7 hrs 19 mins
31 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,760,912 671,614 7.09 3 hrs 23 mins
32 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 4,596,724 671,614 6.84 3 hrs 30 mins
33 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 4,512,982 1,215,759 3.71 6 hrs 28 mins
34 Intel Arc B580 Graphics
Battlemage G21 [Intel Arc B580 Graphics]
Intel Battlemage G21 4,441,804 671,614 6.61 3 hrs 38 mins
35 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,278,099 671,614 6.37 3 hrs 46 mins
36 Radeon 8050S/8060S
Strix Halo [Radeon 8050S/8060S]
AMD Strix Halo 4,272,684 671,614 6.36 3 hrs 46 mins
37 Radeon RX 7700XT/7800XT
Navi 32 [Radeon RX 7700XT/7800XT]
AMD Navi 32 3,706,194 671,614 5.52 4 hrs 21 mins
38 RTX 4000 SFF Ada Generation
AD104GL [RTX 4000 SFF Ada Generation]
Nvidia AD104GL 3,545,913 671,614 5.28 4 hrs 33 mins
39 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,519,045 702,378 5.01 4 hrs 47 mins
40 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,258,836 783,938 4.16 5 hrs 46 mins
41 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 3,170,819 1,724,184 1.84 13 hrs 3 mins
42 GeForce RTX 4070 Max-Q / Mobile
AD106M [GeForce RTX 4070 Max-Q / Mobile]
Nvidia AD106M 3,147,266 671,614 4.69 5 hrs 7 mins
43 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 3,012,724 671,614 4.49 5 hrs 21 mins
44 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,968,008 910,021 3.26 7 hrs 22 mins
45 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 2,948,041 671,614 4.39 5 hrs 28 mins
46 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,900,809 671,614 4.32 5 hrs 33 mins
47 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,806,093 671,614 4.18 5 hrs 45 mins
48 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,786,461 826,682 3.37 7 hrs 7 mins
49 Radeon RX 6700(XT)/6800M
Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]
AMD Navi 22 XT-XL 2,728,678 671,614 4.06 5 hrs 54 mins
50 GeForce RTX 4060 Max-Q / Mobile
AD107M [GeForce RTX 4060 Max-Q / Mobile]
Nvidia AD107M 2,727,023 671,614 4.06 5 hrs 55 mins
51 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,667,047 671,614 3.97 6 hrs 3 mins
52 Radeon RX 9060(XT)
Navi 44 [Radeon RX 9060(XT)]
AMD Navi 44 2,583,079 671,614 3.85 6 hrs 14 mins
53 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 2,441,211 671,614 3.63 6 hrs 36 mins
54 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,321,415 671,614 3.46 6 hrs 57 mins
55 RTX A2000
GA106 [RTX A2000]
Nvidia GA106 2,240,793 671,614 3.34 7 hrs 12 mins
56 Radeon RX 6650 XT
Navi 23 [Radeon RX 6650 XT]
AMD Navi 23 2,082,777 671,614 3.10 7 hrs 44 mins
57 Geforce RTX 3050
GA106 [Geforce RTX 3050]
Nvidia GA106 1,166,138 671,614 1.74 13 hrs 49 mins
58 Radeon RX 6600(XT/M)
Navi 23 XT-XL [Radeon RX 6600(XT/M)]
AMD Navi 23 XT-XL 1,122,191 671,614 1.67 14 hrs 22 mins
59 Radeon PRO W6400
Navi 24 [Radeon PRO W6400]
AMD Navi 24 342,466 671,614 0.51 47 hrs 4 mins
60 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 278,638 671,614 0.41 57 hrs 51 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:30:35
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make