Research section Research projects and references

Research: ALZHEIMERS Folding Project #18264

Project #18264 overview

Project Summary AI Beta

Alzheimer's disease involves harmful protein clumps called tau tangles. Researchers are using computer simulations to understand how tau behaves and find the best models to represent it. This could help develop new treatments for Alzheimer's and other diseases caused by misbehaving proteins.
Automated summary; simplified and may not be fully accurate.

Project team

Manager(s)
Justin Miller
Institution
University of Pennsylvania

Work unit

Atoms
919,221
Core
0x27
Status
Public
Source material

Official 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 accompanying 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 p18264 - amber99sb-star-ILDN with tip3p water.

Performance data

Hardware Performance for Project 18264

Compare community-sampled Folding@Home output for the GPUs and CPUs processing this project.

Data as of Sunday, 23 August 2026 03:26:32

GPU PPD Averages

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 48,910,973 398,257 122.81 0 hrs 12 mins
2 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 26,740,522 1,148,942 23.27 1 hrs 2 mins
3 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 25,139,872 398,257 63.12 0 hrs 23 mins
4 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 19,515,102 398,257 49.00 0 hrs 29 mins
5 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 17,018,333 2,157,640 7.89 3 hrs 3 mins
6 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 16,645,477 1,088,200 15.30 1 hrs 34 mins
7 RTX PRO 4000 Blackwell
GB203GL [RTX PRO 4000 Blackwell]
Unknown GB203GL 12,416,495 398,257 31.18 0 hrs 46 mins
8 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 12,177,650 431,062 28.25 0 hrs 51 mins
9 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 10,659,894 398,257 26.77 0 hrs 54 mins
10 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 10,585,988 398,257 26.58 0 hrs 54 mins
11 Radeon RX 6800(XT)/6900XT
Navi 21 [Radeon RX 6800(XT)/6900XT]
AMD Navi 21 10,355,843 398,257 26.00 0 hrs 55 mins
12 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 10,121,885 398,257 25.42 0 hrs 57 mins
13 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 8,674,446 398,257 21.78 1 hrs 6 mins
14 GeForce RTX 5060
GB206 [GeForce RTX 5060]
Nvidia GB206 5,396,622 398,257 13.55 1 hrs 46 mins
15 GeForce RTX 4060 Ti 16GB
AD106 [GeForce RTX 4060 Ti 16GB]
Nvidia AD106 5,038,130 398,257 12.65 1 hrs 54 mins
16 GeForce RTX 5060 Ti
GB206 [GeForce RTX 5060 Ti]
Nvidia GB206 3,837,310 398,257 9.64 2 hrs 29 mins
17 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 3,556,999 398,257 8.93 2 hrs 41 mins
18 Radeon RX 6700(XT)/6800M
Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]
AMD Navi 22 XT-XL 3,212,156 398,257 8.07 2 hrs 59 mins
19 Radeon RX 6400/6500XT
Navi 24 [Radeon RX 6400/6500XT]
AMD Navi 24 378,562 607,594 0.62 38 hrs 31 mins