RESEARCH: ALZHEIMERS
FOLDING PROJECT #18255 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 919,221
Core: 0x27
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

Alzheimer's disease is linked to tangles of a protein called tau. The project relates to finding the best computer models to understand how tau behaves because it's hard to study directly. These models could help us learn about Alzheimer's and other diseases.

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 these simulations.

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 p18259 - amber19sb with opc3 pol water p18260- amber99sb-star-ILDN with tip4pd water p18261- 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 that causes memory loss, cognitive decline, and behavioral changes.

Disease: Healthcare
Neurology / Dementia

Alzheimer's disease is a serious brain condition that affects thinking, memory, and behavior. People with Alzheimer's may struggle with everyday tasks and eventually lose the ability to care for themselves. There is no cure for Alzheimer's, but treatments can help manage symptoms.


Neurofibrillary tangles

Abnormal accumulations of tau protein inside neurons.

Medical Finding: Healthcare
Neurology / Pathology

Neurofibrillary tangles are clumps of a protein called tau that form inside brain cells. These tangles are a hallmark of Alzheimer's disease and other neurodegenerative disorders.


Tau protein

A microtubule-associated protein that plays a role in stabilizing neuronal structures.

Protein: Biotechnology
Biochemistry / Neurobiology

Tau is a protein found in brain cells. It helps to support the structure of neurons and keep them healthy. In Alzheimer's disease, tau becomes tangled and clumps together, damaging the brain.


Microtubules

Tubular protein structures that provide structural support and facilitate intracellular transport.

Cellular Structure: Biotechnology
Cell Biology / Cytoskeleton

Microtubules are long, hollow tubes made of protein that help cells maintain their shape and move materials around. They play a crucial role in cell division and other important cellular processes.


Intrinsically Disordered Protein (IDP)

A protein that lacks a stable, defined three-dimensional structure.

Protein Type: Biotechnology
Biochemistry / Structural Biology

Intrinsically disordered proteins are unique because they don't have a fixed shape. They can adopt different conformations depending on their environment and interactions with other molecules. This flexibility allows them to perform diverse functions in the cell.


Single molecule FRET

A technique used to measure the distance between two molecules labeled with fluorescent probes.

Experimental Technique: Research
Biochemistry / Structural Biology

Single molecule FRET (Förster Resonance Energy Transfer) is a powerful tool for studying the structure and dynamics of biomolecules. It allows researchers to track the movement of individual molecules and measure their interactions in real time.


Force fields

Mathematical models that describe the interactions between atoms in a molecule.

Computational Tool: Research
Computer Science / Biomolecular Simulation

Force fields are used in computer simulations to predict how molecules will behave. They provide a way to simulate the forces that act between atoms, allowing researchers to study chemical reactions, protein folding, and other complex phenomena.


Water models

Mathematical representations of water molecules used in computer simulations.

Computational Tool: Research
Computer Science / Biomolecular Simulation

Water models are essential for simulating biological systems because water plays a critical role in many cellular processes. Accurate water models allow researchers to capture the effects of hydration on protein structure, folding, and function.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:30:45
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 46,152,414 40,000 1153.81 0 hrs 1 mins
2 RTX PRO 6000 Blackwell Server Edition
GB202GL [RTX PRO 6000 Blackwell Server Edition]
Nvidia GB202GL 39,354,953 40,000 983.87 0 hrs 1 mins
3 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 25,015,612 345,240 72.46 0 hrs 20 mins
4 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 19,473,817 323,936 60.12 0 hrs 24 mins
5 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 19,447,981 40,000 486.20 0 hrs 3 mins
6 RTX PRO 6000 Blackwell Max-Q Workstation Edition
GB202GL [RTX PRO 6000 Blackwell Max-Q Workstation Edition]
Nvidia GB202GL 18,827,467 40,000 470.69 0 hrs 3 mins
7 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 18,218,971 131,940 138.09 0 hrs 10 mins
8 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 16,980,226 81,347 208.74 0 hrs 7 mins
9 GeForce RTX 5090 Max-Q / Mobile
GB203M / GN22 [GeForce RTX 5090 Max-Q / Mobile]
Nvidia GB203M / GN22 15,615,859 40,000 390.40 0 hrs 4 mins
10 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 11,829,887 335,902 35.22 0 hrs 41 mins
11 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 11,366,256 40,000 284.16 0 hrs 5 mins
12 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 11,259,837 100,671 111.85 0 hrs 13 mins
13 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 10,255,090 144,319 71.06 0 hrs 20 mins
14 GeForce RTX 5080 Max-Q / Mobile
GB203M / GN22-X9 [GeForce RTX 5080 Max-Q / Mobile]
Nvidia GB203M / GN22-X9 9,734,274 40,000 243.36 0 hrs 6 mins
15 GeForce RTX 4090 Laptop GPU
AD103M / GN21-X11 [GeForce RTX 4090 Laptop GPU]
Nvidia AD103M / GN21-X11 8,658,319 40,000 216.46 0 hrs 7 mins
16 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 8,621,266 365,380 23.60 1 hrs 1 mins
17 GeForce RTX 4070 Ti SUPER
AD103 [GeForce RTX 4070 Ti SUPER]
Nvidia AD103 8,497,087 173,249 49.05 0 hrs 29 mins
18 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 8,394,271 357,226 23.50 1 hrs 1 mins
19 GeForce RTX 5060 Ti
GB206 [GeForce RTX 5060 Ti]
Nvidia GB206 7,680,732 314,467 24.42 0 hrs 59 mins
20 Radeon RX 6800(XT)/6900XT
Navi 21 [Radeon RX 6800(XT)/6900XT]
AMD Navi 21 6,986,550 282,782 24.71 0 hrs 58 mins
21 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,814,551 328,188 20.76 1 hrs 9 mins
22 GeForce RTX 4080 Max-Q / Mobile
AD104M [GeForce RTX 4080 Max-Q / Mobile]
Nvidia AD104M 6,427,653 325,316 19.76 1 hrs 13 mins
23 Radeon RX 9070(XT)
Navi 48 [Radeon RX 9070(XT)]
AMD Navi 48 6,105,492 111,667 54.68 0 hrs 26 mins
24 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 5,707,390 140,098 40.74 0 hrs 35 mins
25 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 5,288,884 56,248 94.03 0 hrs 15 mins
26 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 5,237,712 297,739 17.59 1 hrs 22 mins
27 Radeon RX 7700XT/7800XT
Navi 32 [Radeon RX 7700XT/7800XT]
AMD Navi 32 5,227,436 48,633 107.49 0 hrs 13 mins
28 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 4,932,077 278,392 17.72 1 hrs 21 mins
29 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,901,457 261,305 18.76 1 hrs 17 mins
30 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 4,489,248 234,131 19.17 1 hrs 15 mins
31 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,368,152 113,948 38.33 0 hrs 38 mins
32 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,281,167 40,000 107.03 0 hrs 13 mins
33 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,052,002 231,137 17.53 1 hrs 22 mins
34 GeForce RTX 4070 Max-Q / Mobile
AD106M [GeForce RTX 4070 Max-Q / Mobile]
Nvidia AD106M 3,821,430 40,000 95.54 0 hrs 15 mins
35 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 3,564,470 275,682 12.93 1 hrs 51 mins
36 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,377,381 106,716 31.65 0 hrs 46 mins
37 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 3,113,034 40,000 77.83 0 hrs 19 mins
38 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 2,926,204 40,000 73.16 0 hrs 20 mins
39 Radeon RX 6700(XT)/6800M
Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]
AMD Navi 22 XT-XL 2,878,319 40,000 71.96 0 hrs 20 mins
40 Radeon RX 9060(XT)
Navi 44 [Radeon RX 9060(XT)]
AMD Navi 44 2,857,387 64,917 44.02 0 hrs 33 mins
41 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,845,340 253,669 11.22 2 hrs 8 mins
42 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,641,206 247,092 10.69 2 hrs 15 mins
43 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,510,717 166,884 15.04 1 hrs 36 mins
44 Radeon RX 6650XT
Navi 23 [Radeon RX 6650XT]
AMD Navi 23 2,481,246 244,162 10.16 2 hrs 22 mins
45 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,354,669 238,170 9.89 2 hrs 26 mins
46 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 2,293,354 40,000 57.33 0 hrs 25 mins
47 Radeon RX 6600(XT/M)
Navi 23 XT-XL [Radeon RX ж600(XT/M)]
AMD Navi 23 XT-XL 2,109,051 224,963 9.38 2 hrs 34 mins
48 Radeon RX 6600(XT/M)
Navi 23 XT-XL [Radeon RX 6600(XT/M)]
AMD Navi 23 XT-XL 2,109,051 224,963 9.38 2 hrs 34 mins
49 RTX A2000
GA106 [RTX A2000]
Nvidia GA106 1,584,180 40,000 39.60 0 hrs 36 mins
50 Radeon RX 6650 XT
Navi 23 [Radeon RX 6650 XT]
AMD Navi 23 1,341,433 40,000 33.54 0 hrs 43 mins
51 GeForce RTX 4060 Max-Q / Mobile
AD107M [GeForce RTX 4060 Max-Q / Mobile]
Nvidia AD107M 1,254,238 40,000 31.36 0 hrs 46 mins
52 GeForce RTX 3070 Mobile / Max-Q
GA104M [GeForce RTX 3070 Mobile / Max-Q]
Nvidia GA104M 1,000,553 40,000 25.01 0 hrs 58 mins
53 RX 5500(M)/Pro 5500M
Navi 14 [RX 5500(M)/Pro 5500M]
AMD Navi 14 666,736 48,884 13.64 1 hrs 46 mins
54 Radeon 880M/890M
Strix Point [Radeon 880M/890M]
AMD Strix Point 521,101 40,000 13.03 1 hrs 51 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:30:45
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 12TH GEN CORE I5-12400F 12 Intel