RESEARCH: ALZHEIMERS
FOLDING PROJECT #18261 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 causes memory loss and there's no cure. A protein called tau goes bad in the brain, forming harmful clumps. This project uses computer simulations to study how tau works, finding the best way to model it. This will help scientists understand Alzheimer's and other diseases better.

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].

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 tip4pd water p18261- amber19sb with opc3 pol water p18262 - charmm36m with tip3p 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 disorder affecting memory and cognitive function.

Clinical Condition: Healthcare
Neurology / Dementia

Alzheimer's disease is a serious brain disorder that causes memory loss, thinking problems, and behavioral changes. It is the most common cause of dementia.


neurofibrillary tangles

Twisted fibers of tau protein found in brain cells of people with Alzheimer's disease.

Pathological Feature: Healthcare
Neurology / Alzheimer's Disease

Neurofibrillary tangles are abnormal accumulations of tau protein inside nerve cells. They are a hallmark of Alzheimer's disease and contribute to the damage of brain cells.


tau protein

A microtubule-associated protein involved in stabilizing and regulating the structure of neurons.

Protein: Biotechnology
Biology / Neurobiology

Tau is a protein that plays an important role in maintaining the structure of nerve cells. In Alzheimer's disease, tau becomes abnormal and forms tangles, which damage brain cells.


microtubules

Long, hollow protein fibers that form part of the cytoskeleton and are involved in cell shape, transport, and division.

Cellular Structure: Biotechnology
Biology / Cell Structure

Microtubules are tiny tubes made of proteins that act as a scaffolding within cells. They help maintain cell shape, transport materials, and play a role in cell division.


cytoskeleton

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

Cellular Structure: Biotechnology
Biology / Cell Structure

The cytoskeleton is a complex network of protein filaments that gives cells their shape, helps them move, and plays a role in transporting materials within the cell.


Intrinsically Disordered Protein (IDP)

A protein that lacks a well-defined three-dimensional structure.

Protein Classification: Biotechnology
Biology / Protein Structure

Intrinsically disordered proteins (IDPs) are proteins that do not have a fixed shape. They can adopt different conformations depending on their environment and interactions with other molecules.


force field

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

Computational Model: Biotechnology
Biotechnology / Molecular Simulation

Force fields are used in computer simulations to model the behavior of molecules. They provide a way to calculate the forces acting between atoms and predict how molecules will move and interact.


FRET

Förster Resonance Energy Transfer.

Technique: Research
Biochemistry / Fluorescence Spectroscopy

FRET is a technique used to measure the distance between two molecules labeled with fluorescent probes. It can be used to study protein interactions and conformational changes.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 23 June 2026 15:30:05
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 5090
GB202 [GeForce RTX 5090]
Nvidia GB202 35,186,372 66,000 533.13 0 hrs 3 mins
2 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 28,241,777 702,122 40.22 0 hrs 36 mins
3 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 19,421,777 66,000 294.27 0 hrs 5 mins
4 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 15,698,265 582,128 26.97 0 hrs 53 mins
5 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 14,539,224 604,944 24.03 0 hrs 60 mins
6 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 13,481,121 185,435 72.70 0 hrs 20 mins
7 GeForce RTX 4070 Ti SUPER
AD103 [GeForce RTX 4070 Ti SUPER]
Nvidia AD103 10,570,443 408,982 25.85 0 hrs 56 mins
8 RTX PRO 4000 Blackwell
GB203GL [RTX PRO 4000 Blackwell]
Unknown GB203GL 10,297,086 66,000 156.02 0 hrs 9 mins
9 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 9,528,818 357,899 26.62 0 hrs 54 mins
10 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 9,313,166 432,137 21.55 1 hrs 7 mins
11 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 8,729,070 66,000 132.26 0 hrs 11 mins
12 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 8,376,644 163,888 51.11 0 hrs 28 mins
13 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 7,659,881 483,156 15.85 1 hrs 31 mins
14 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,388,957 455,051 16.24 1 hrs 29 mins
15 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 6,092,424 66,000 92.31 0 hrs 16 mins
16 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 5,695,186 66,000 86.29 0 hrs 17 mins
17 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 5,561,486 417,831 13.31 1 hrs 48 mins
18 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 5,490,473 399,862 13.73 1 hrs 45 mins
19 GeForce RTX 5060
GB206 [GeForce RTX 5060]
Nvidia GB206 5,303,595 66,000 80.36 0 hrs 18 mins
20 Radeon RX 9070(XT)
Navi 48 [Radeon RX 9070(XT)]
AMD Navi 48 5,114,169 338,514 15.11 1 hrs 35 mins
21 GeForce RTX 4070 Max-Q / Mobile
AD106M [GeForce RTX 4070 Max-Q / Mobile]
Nvidia AD106M 5,083,020 66,000 77.02 0 hrs 19 mins
22 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,968,017 298,238 16.66 1 hrs 26 mins
23 Radeon RX 6800(XT)/6900XT
Navi 21 [Radeon RX 6800(XT)/6900XT]
AMD Navi 21 4,860,816 402,090 12.09 1 hrs 59 mins
24 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 4,713,433 401,516 11.74 2 hrs 3 mins
25 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 4,134,897 394,128 10.49 2 hrs 17 mins
26 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,757,365 328,675 11.43 2 hrs 6 mins
27 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 3,731,567 374,997 9.95 2 hrs 25 mins
28 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 3,729,124 342,960 10.87 2 hrs 12 mins
29 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 3,692,730 325,398 11.35 2 hrs 7 mins
30 RTX 4000 SFF Ada Generation
AD104GL [RTX 4000 SFF Ada Generation]
Nvidia AD104GL 3,164,323 66,000 47.94 0 hrs 30 mins
31 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 3,062,760 338,647 9.04 2 hrs 39 mins
32 GeForce RTX 5060 Ti
GB206 [GeForce RTX 5060 Ti]
Nvidia GB206 3,040,345 66,000 46.07 0 hrs 31 mins
33 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 2,995,012 66,000 45.38 0 hrs 32 mins
34 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,912,085 333,196 8.74 2 hrs 45 mins
35 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,902,822 356,460 8.14 2 hrs 57 mins
36 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,792,979 326,246 8.56 2 hrs 48 mins
37 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 2,605,089 279,841 9.31 2 hrs 35 mins
38 Radeon RX 9060(XT)
Navi 44 [Radeon RX 9060(XT)]
AMD Navi 44 2,526,510 66,000 38.28 0 hrs 38 mins
39 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,448,104 339,002 7.22 3 hrs 19 mins
40 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,236,609 329,321 6.79 3 hrs 32 mins
41 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,813,633 305,616 5.93 4 hrs 3 mins
42 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,557,128 299,001 5.21 4 hrs 37 mins
43 Radeon RX 6600(XT/M)
Navi 23 XT-XL [Radeon RX 6600(XT/M)]
AMD Navi 23 XT-XL 1,545,091 66,000 23.41 1 hrs 2 mins
44 RTX A2000
GA106 [RTX A2000]
Nvidia GA106 1,474,261 66,000 22.34 1 hrs 4 mins
45 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,379,352 281,720 4.90 4 hrs 54 mins
46 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,363,905 281,579 4.84 4 hrs 57 mins
47 Radeon PRO W6400
Navi 24 [Radeon PRO W6400]
AMD Navi 24 792,299 66,000 12.00 1 hrs 60 mins
48 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 573,275 224,493 2.55 9 hrs 24 mins
49 Radeon RX 6400/6500XT
Navi 24 [Radeon RX 6400/6500XT]
AMD Navi 24 385,972 183,767 2.10 11 hrs 26 mins
50 Radeon RX 6400 / 6500 XT
Navi 24 [Radeon RX 6400 / 6500 XT]
AMD Navi 24 338,584 66,000 5.13 4 hrs 41 mins
51 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 278,644 163,892 1.70 14 hrs 7 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 23 June 2026 15:30:05
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make