RESEARCH: FORCE-FIELD-PROTEIN-SIMULATION
FOLDING PROJECT #18243 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 117,230
Core: 0x26
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

The project relates to testing different computer models used to simulate how molecules move. These models are like physics rules for atoms and are important for understanding how proteins fold and work. Scientists are using a protein called lysozyme as a test case because it's well-studied and has many known shapes. This research aims to improve the accuracy of these simulations, which can help us learn more about diseases and develop new drugs.

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

OFFICAL PROJECT DESCRIPTION

Force fields aren't only a thing in far off galaxies, but are also an integral part of molecular dynamics simulations.

Principally, molecular dynamics simulations are evaluating Newton's laws of motion iteratively.

Each atom in the simulation is given a position, velocity, and has some forces acting upon it.

We then take a short step forward in time (often 2-4 femtoseconds), update the positions of each atom based on the last known position, velocity, and acceleration, before re-evaluating the forces acting upon each atom.

Repeating this millions to trillions of times (or more), gives us a physics-based movie of atoms moving which we use to give insight into the behavior of our favorite proteins. One of the fundamental steps of this process is calculating the forces on each atom.

The collective model describing how to calculate these forces is called a force field.

Through the years, many force fields have been derived and refined, each one focusing on improving certain forces or behaviors of the simulation.

While tests are usually performed when force fields are redeveloped, it is difficult to achieve robust sampling (e.g.

many observations of rare events).

Here, we are continuing our efforts to catalog the performance and accuracy of these force fields.

In this project series, we use the well studied protein, T4 Lysozyme, as our test model.

Lysozyme is an antibacterial protein which destroys bacterial cell walls.

Lysozyme is an ideal system to use for evaluating force fields as many biophysical measurements have been performed on the system and several rare conformations (folds) of the protein have been observed.

We expect that our findings in this project series, along with the similar project series 18227-18230 and 18250-18255, will provide a strong benchmark to improve the accuracy in simulations, both on Folding@home as well as in the broader scientific community, to come. We are testing the following force field/water combinations in this project series.

If you are particularly excited about additional force field/water combinations, please reach out. 18235- Amber03 with TIP3P water 18236- Amber14sb with TIP3P water 18237- Amber19sb with OPC water 18238- Charmm36m with TIP3P water 18240- Amber99SB-disp with TIP4PD-1.6 water 18242-Amber99SB-star-ILDN with TIP4PD water 18243- Amber19sb with OPC3 water 18244-Amber19sb with OPC3-pol water.

RELATED TERMS GLOSSARY AI BETA

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

Force fields

A model describing how to calculate forces on atoms in a simulation.

Technical: Biotechnology
Molecular Dynamics / Simulations

Force fields are mathematical models used in molecular dynamics simulations to calculate the forces acting between atoms. They are essential for accurately simulating the behavior of molecules and understanding their properties.


Molecular dynamics

A computational method for simulating the movement of atoms and molecules over time.

Technical: Biotechnology
Biotechnology / Simulations

Molecular dynamics simulations are computer programs that use physical laws to simulate how atoms and molecules interact. This allows scientists to study the behavior of molecules in different environments and conditions.


Newton's laws of motion

The fundamental principles governing the motion of objects.

Scientific: Biotechnology
Physics / Classical Mechanics

Newton's laws of motion describe how objects move and interact with forces. They are the foundation of classical mechanics and are essential for understanding many phenomena in physics, including molecular dynamics.


Femtoseconds

A unit of time equal to 10^-15 seconds.

Technical: Biotechnology
Physics / Time Measurement

Femtoseconds are incredibly short units of time, often used in physics and chemistry to measure the speed of events at the atomic level. In molecular dynamics simulations, femtoseconds represent the small time steps taken to update the positions of atoms.


Proteins

Large, complex molecules essential for many biological processes.

Scientific: Biotechnology
Biology / Biomolecules

Proteins are the workhorses of cells, carrying out a vast array of functions. They are involved in everything from building and repairing tissues to catalyzing chemical reactions.


T4 Lysozyme

A well-studied enzyme with antibacterial properties.

Scientific: Biotechnology
Biology / Proteins

T4 Lysozyme is a protein that breaks down the cell walls of bacteria. It is used extensively in research to study protein structure and function.


Conformations

Different shapes or arrangements that a molecule can adopt.

Scientific: Biotechnology
Chemistry / Protein Structure

Conformations refer to the different ways that a molecule, such as a protein, can fold and arrange its atoms. These different conformations can affect the molecule's function.


Folding@home

A distributed computing project that simulates protein folding.

Technical: Biotechnology
Biotechnology / Distributed Computing

Folding@home is a volunteer computing project that uses the processing power of donated computers to simulate protein folding. This helps researchers understand how proteins fold and function.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:30:55
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 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 9,317,263 331,349 28.12 0 hrs 51 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 8,742,279 205,545 42.53 0 hrs 34 mins
3 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 7,918,554 426,430 18.57 1 hrs 18 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 7,866,800 346,237 22.72 1 hrs 3 mins
5 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 7,052,373 50,149 140.63 0 hrs 10 mins
6 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,303,052 272,199 23.16 1 hrs 2 mins
7 RTX A4500
GA102GL [RTX A4500]
Nvidia GA102GL 5,836,787 39,000 149.66 0 hrs 10 mins
8 Radeon RX 9070(XT)
Navi 48 [Radeon RX 9070(XT)]
AMD Navi 48 5,686,522 68,525 82.98 0 hrs 17 mins
9 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 5,527,524 130,919 42.22 0 hrs 34 mins
10 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 5,261,041 212,559 24.75 0 hrs 58 mins
11 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 5,216,616 39,000 133.76 0 hrs 11 mins
12 Radeon RX 6800(XT)/6900XT
Navi 21 [Radeon RX 6800(XT)/6900XT]
AMD Navi 21 5,110,393 284,362 17.97 1 hrs 20 mins
13 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 4,956,493 49,187 100.77 0 hrs 14 mins
14 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 4,443,079 294,298 15.10 1 hrs 35 mins
15 RTX A4000
GA104GL [RTX A4000]
Nvidia GA104GL 4,100,487 39,000 105.14 0 hrs 14 mins
16 Radeon RX 7700XT/7800XT
Navi 32 [Radeon RX 7700XT/7800XT]
AMD Navi 32 4,094,440 39,000 104.99 0 hrs 14 mins
17 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,975,902 225,334 17.64 1 hrs 22 mins
18 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,709,934 39,000 95.13 0 hrs 15 mins
19 Tesla V100 PCIe 16GB
GV100GL [Tesla V100 PCIe 16GB] M 14028
Nvidia GV100GL 3,641,642 39,000 93.38 0 hrs 15 mins
20 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 3,556,965 257,824 13.80 1 hrs 44 mins
21 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,446,266 52,456 65.70 0 hrs 22 mins
22 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 3,332,015 39,000 85.44 0 hrs 17 mins
23 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,291,384 264,093 12.46 1 hrs 56 mins
24 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,278,524 55,516 59.06 0 hrs 24 mins
25 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,242,660 39,000 83.15 0 hrs 17 mins
26 GeForce RTX 3070 Mobile / Max-Q
GA104M [GeForce RTX 3070 Mobile / Max-Q]
Nvidia GA104M 3,116,944 39,000 79.92 0 hrs 18 mins
27 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,827,635 125,098 22.60 1 hrs 4 mins
28 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,796,793 39,000 71.71 0 hrs 20 mins
29 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,775,494 39,000 71.17 0 hrs 20 mins
30 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,700,479 228,259 11.83 2 hrs 2 mins
31 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 2,643,037 248,078 10.65 2 hrs 15 mins
32 Quadro P6000
GP102GL [Quadro P6000]
Nvidia GP102GL 2,599,193 39,000 66.65 0 hrs 22 mins
33 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,573,352 213,393 12.06 1 hrs 59 mins
34 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 2,573,040 39,000 65.98 0 hrs 22 mins
35 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 2,510,765 234,794 10.69 2 hrs 15 mins
36 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,505,717 263,582 9.51 2 hrs 31 mins
37 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 2,468,795 39,000 63.30 0 hrs 23 mins
38 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 2,458,777 39,000 63.05 0 hrs 23 mins
39 TITAN X
GP102 [TITAN X] 6144
Nvidia GP102 2,351,364 238,579 9.86 2 hrs 26 mins
40 Radeon RX 6700(XT)/6800M
Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]
AMD Navi 22 XT-XL 2,217,816 39,000 56.87 0 hrs 25 mins
41 GeForce RTX 2070 Mobile / Max-Q Refresh
TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh]
Nvidia TU106M 2,214,675 230,990 9.59 2 hrs 30 mins
42 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,154,953 160,626 13.42 1 hrs 47 mins
43 GeForce RTX 2070 Mobile
TU106BM [GeForce RTX 2070 Mobile]
Nvidia TU106BM 2,132,723 229,032 9.31 2 hrs 35 mins
44 Radeon RX 6650XT
Navi 23 [Radeon RX 6650XT]
AMD Navi 23 2,044,606 224,803 9.10 2 hrs 38 mins
45 TITAN RTX
TU102 [TITAN RTX] 16310
Nvidia TU102 1,982,257 39,000 50.83 0 hrs 28 mins
46 Quadro P5000
GP104GL [Quadro P5000]
Nvidia GP104GL 1,657,042 39,000 42.49 0 hrs 34 mins
47 RTX A2000
GA106 [RTX A2000]
Nvidia GA106 1,638,150 39,000 42.00 0 hrs 34 mins
48 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,570,562 39,000 40.27 0 hrs 36 mins
49 Radeon RX 6600(XT/M)
Navi 23 XT-XL [Radeon RX 6600(XT/M)]
AMD Navi 23 XT-XL 1,564,910 163,672 9.56 2 hrs 31 mins
50 RTX A2000 12GB
GA106 [RTX A2000 12GB]
Nvidia GA106 1,497,238 39,000 38.39 0 hrs 38 mins
51 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,437,893 39,000 36.87 0 hrs 39 mins
52 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,417,071 199,087 7.12 3 hrs 22 mins
53 Geforce RTX 3050
GA106 [Geforce RTX 3050]
Nvidia GA106 1,409,261 39,000 36.13 0 hrs 40 mins
54 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,403,841 177,799 7.90 3 hrs 2 mins
55 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,394,100 39,000 35.75 0 hrs 40 mins
56 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,353,114 194,397 6.96 3 hrs 27 mins
57 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,345,078 107,109 12.56 1 hrs 55 mins
58 P104-100
GP104 [P104-100]
Nvidia GP104 1,311,085 39,000 33.62 0 hrs 43 mins
59 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,299,475 39,000 33.32 0 hrs 43 mins
60 RTX A2000 Mobile
GA107GLM [RTX A2000 Mobile]
Nvidia GA107GLM 1,297,911 39,000 33.28 0 hrs 43 mins
61 GeForce RTX 4060 Max-Q / Mobile
AD107M [GeForce RTX 4060 Max-Q / Mobile]
Nvidia AD107M 1,219,571 114,709 10.63 2 hrs 15 mins
62 GeForce RTX 3050 Mobile
GA107M [GeForce RTX 3050 Mobile]
Nvidia GA107M 1,179,552 39,000 30.24 0 hrs 48 mins
63 RTX A1000
GA107GL [RTX A1000]
Nvidia GA107GL 1,128,268 39,000 28.93 0 hrs 50 mins
64 GeForce RTX 3050 Ti Mobile
GA107M [GeForce RTX 3050 Ti Mobile]
Nvidia GA107M 934,993 39,000 23.97 1 hrs 0 mins
65 GeForce GTX Titan X
GM200 [GeForce GTX Titan X] 6144
Nvidia GM200 928,055 39,000 23.80 1 hrs 1 mins
66 RX 5600 OEM/5600XT/5700(XT)
Navi 10 [RX 5600 OEM/5600XT/5700(XT)]
AMD Navi 10 884,073 39,000 22.67 1 hrs 4 mins
67 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 881,446 39,000 22.60 1 hrs 4 mins
68 P106-100
GP106 [P106-100]
Nvidia GP106 851,518 132,860 6.41 3 hrs 45 mins
69 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 843,409 39,000 21.63 1 hrs 7 mins
70 Quadro P3200 Mobile
GP104GLM [Quadro P3200 Mobile]
Nvidia GP104GLM 788,979 155,950 5.06 4 hrs 45 mins
71 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 758,679 169,536 4.48 5 hrs 22 mins
72 GeForce GTX 1660 Mobile
TU116M [GeForce GTX 1660 Mobile]
Nvidia TU116M 742,210 168,070 4.42 5 hrs 26 mins
73 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 722,038 158,101 4.57 5 hrs 15 mins
74 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 678,432 155,137 4.37 5 hrs 29 mins
75 Quadro P2200
GP106GL [Quadro P2200]
Nvidia GP106GL 598,422 39,000 15.34 1 hrs 34 mins
76 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 595,758 39,000 15.28 1 hrs 34 mins
77 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 574,405 158,474 3.62 6 hrs 37 mins
78 RX 5500(M)/Pro 5500M
Navi 14 [RX 5500(M)/Pro 5500M]
AMD Navi 14 518,115 39,000 13.29 1 hrs 48 mins
79 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 486,849 39,000 12.48 1 hrs 55 mins
80 Quadro P2000
GP106GL [Quadro P2000] [MED-XN71] 3935
Nvidia GP106GL 475,383 39,000 12.19 1 hrs 58 mins
81 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 459,585 73,621 6.24 3 hrs 51 mins
82 GeForce GTX 1650
TU116 [GeForce GTX 1650] 3091
Nvidia TU116 443,956 115,717 3.84 6 hrs 15 mins
83 GeForce GTX 1650
TU106 [GeForce GTX 1650]
Nvidia TU106 408,828 39,000 10.48 2 hrs 17 mins
84 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 394,903 39,000 10.13 2 hrs 22 mins
85 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 355,853 89,343 3.98 6 hrs 2 mins
86 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 355,589 76,830 4.63 5 hrs 11 mins
87 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 251,721 40,554 6.21 3 hrs 52 mins
88 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 218,701 39,000 5.61 4 hrs 17 mins
89 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 190,168 39,000 4.88 4 hrs 55 mins
90 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 189,717 102,460 1.85 12 hrs 58 mins
91 GeForce GTX 760
GK104 [GeForce GTX 760] 2258
Nvidia GK104 124,068 39,000 3.18 7 hrs 33 mins
92 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 118,325 42,926 2.76 8 hrs 42 mins
93 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 99,212 58,559 1.69 14 hrs 10 mins
94 GeForce MX250
GP108M [GeForce MX250]
Nvidia GP108M 64,464 84,159 0.77 31 hrs 20 mins
95 GeForce MX350
GP107M [GeForce MX350]
Nvidia GP107M 53,850 39,000 1.38 17 hrs 23 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:30:55
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 CORE I5-7400 CPU @ 3.00GHZ 4 Intel
2 12TH GEN CORE I5-12400F 12 Intel