RESEARCH: FORCE-FIELD-PROTEIN-DYNAMICS
FOLDING PROJECT #18237 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 147,745
Core: 0x24
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project tests different computer models used to simulate how proteins move. They use a well-studied protein called lysozyme to see which model is most accurate. The goal is to improve these simulations so scientists can better understand how proteins work.

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 18239- Amber99SB-star-ILDN with TIP4PD water 18240- Amber99SB-disp with TIP4PD-1.6 water.

RELATED TERMS GLOSSARY AI BETA

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

Force fields

A collective model describing how to calculate the forces acting on atoms in a molecular dynamics simulation.

Technical: Biotechnology
Molecular Dynamics / Simulations

Force fields are mathematical models used in computer simulations to represent the interactions between atoms. They are essential for accurately simulating the behavior of molecules and understanding their properties.


Molecular dynamics

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

Technical: Biotechnology, Pharmacology
Computational Science / Simulation

Molecular dynamics simulations use computer algorithms to model the behavior of molecules. By calculating the forces between atoms, these simulations can predict how molecules will move and interact, providing insights into chemical reactions, protein folding, and other biological processes.


Newton's laws of motion

A set of three fundamental principles that govern the motion of objects.

Scientific: Science
Physics / Classical Mechanics

Newton's laws of motion describe how objects move and interact with forces. These laws are essential for understanding the behavior of everything from planets to projectiles.


Femtoseconds

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

Technical: Science, Technology
Time Measurement / Physical Units

Femtoseconds are incredibly short units of time, used to measure the fastest events in physics and chemistry. They are often employed in studying ultrafast processes like light absorption and chemical reactions.


T4 Lysozyme

A well-studied bacteriolytic enzyme.

Scientific: Biotechnology, Medicine
Biochemistry / Proteins

T4 Lysozyme is a type of protein that breaks down bacterial cell walls. It is widely used as a model system in biochemistry and molecular biology research due to its simplicity and well-characterized structure.


Folding@home

A distributed computing project that uses volunteer computer resources to perform simulations of protein folding.

Technical: Biotechnology, Research
Computational Science / Distributed Computing

Folding@home harnesses the power of thousands of computers to simulate the complex process of protein folding. This research helps scientists understand how proteins fold into their functional shapes and develop new drugs and therapies.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:31:05
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 28,296,349 68,000 416.12 0 hrs 3 mins
2 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 20,723,444 465,547 44.51 0 hrs 32 mins
3 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 18,730,815 68,000 275.45 0 hrs 5 mins
4 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 16,332,403 323,171 50.54 0 hrs 28 mins
5 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 15,131,579 524,226 28.86 0 hrs 50 mins
6 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 15,049,990 264,357 56.93 0 hrs 25 mins
7 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 13,219,484 513,615 25.74 0 hrs 56 mins
8 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 11,816,316 193,120 61.19 0 hrs 24 mins
9 GeForce RTX 4070 Ti SUPER
AD103 [GeForce RTX 4070 Ti SUPER]
Nvidia AD103 11,296,049 301,818 37.43 0 hrs 38 mins
10 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 8,859,857 127,016 69.75 0 hrs 21 mins
11 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 8,716,966 252,295 34.55 0 hrs 42 mins
12 RTX 5000 Ada Generation Laptop GPU
AD103GLM [RTX 5000 Ada Generation Laptop GPU]
Nvidia AD103GLM 8,456,745 523,956 16.14 1 hrs 29 mins
13 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 8,003,321 452,740 17.68 1 hrs 21 mins
14 GeForce RTX 3080 12GB
GA102 [GeForce RTX 3080 12GB]
Nvidia GA102 7,144,852 495,732 14.41 1 hrs 40 mins
15 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,956,423 410,902 16.93 1 hrs 25 mins
16 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,498,519 407,433 15.95 1 hrs 30 mins
17 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 6,403,853 165,191 38.77 0 hrs 37 mins
18 GeForce RTX 4060 Ti 16GB
AD106 [GeForce RTX 4060 Ti 16GB]
Nvidia AD106 6,328,309 468,308 13.51 1 hrs 47 mins
19 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 6,028,794 404,057 14.92 1 hrs 37 mins
20 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 5,977,919 267,045 22.39 1 hrs 4 mins
21 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 5,580,967 68,000 82.07 0 hrs 18 mins
22 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 5,464,537 68,000 80.36 0 hrs 18 mins
23 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 5,296,463 173,632 30.50 0 hrs 47 mins
24 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 5,057,364 250,533 20.19 1 hrs 11 mins
25 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,662,699 267,806 17.41 1 hrs 23 mins
26 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 4,656,035 419,229 11.11 2 hrs 10 mins
27 GeForce RTX 4070 Max-Q / Mobile
AD106M [GeForce RTX 4070 Max-Q / Mobile]
Nvidia AD106M 4,371,224 68,000 64.28 0 hrs 22 mins
28 Radeon RX 6800/6800XT/6900XT
Navi 21 [Radeon RX 6800/6800XT/6900XT]
AMD Navi 21 3,874,913 277,441 13.97 1 hrs 43 mins
29 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,720,672 377,744 9.85 2 hrs 26 mins
30 Radeon RX 7700XT/7800XT
Navi 32 [Radeon RX 7700XT/7800XT]
AMD Navi 32 3,718,893 136,723 27.20 0 hrs 53 mins
31 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 3,673,629 126,005 29.15 0 hrs 49 mins
32 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,432,021 287,839 11.92 2 hrs 1 mins
33 GeForce RTX 4060
AD106 [GeForce RTX 4060]
Nvidia AD106 3,289,634 381,594 8.62 2 hrs 47 mins
34 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,251,296 358,334 9.07 2 hrs 39 mins
35 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 2,935,839 293,875 9.99 2 hrs 24 mins
36 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,743,163 275,469 9.96 2 hrs 25 mins
37 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 2,594,707 68,000 38.16 0 hrs 38 mins
38 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 2,552,464 68,000 37.54 0 hrs 38 mins
39 GeForce RTX 4060 Max-Q / Mobile
AD107M [GeForce RTX 4060 Max-Q / Mobile]
Nvidia AD107M 2,548,823 351,116 7.26 3 hrs 18 mins
40 Radeon RX 6800(XT)/6900XT
Navi 21 [Radeon RX 6800(XT)/6900XT]
AMD Navi 21 2,522,837 250,477 10.07 2 hrs 23 mins
41 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,451,102 326,773 7.50 3 hrs 12 mins
42 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,415,780 345,313 7.00 3 hrs 26 mins
43 Radeon RX 6700/6700XT/6800M
Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M]
AMD Navi 22 XT-XL 2,302,449 114,685 20.08 1 hrs 12 mins
44 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,199,626 230,914 9.53 2 hrs 31 mins
45 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,188,994 130,450 16.78 1 hrs 26 mins
46 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 2,188,414 306,721 7.13 3 hrs 22 mins
47 Radeon RX 6700(XT)/6800M
Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]
AMD Navi 22 XT-XL 2,089,840 68,000 30.73 0 hrs 47 mins
48 GeForce RTX 2070 Mobile / Max-Q Refresh
TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh]
Nvidia TU106M 2,033,896 313,554 6.49 3 hrs 42 mins
49 Radeon RX 7700S/7600S
Navi 33 [Radeon RX 7700S/7600S]
AMD Navi 33 1,833,441 68,000 26.96 0 hrs 53 mins
50 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,760,661 215,863 8.16 2 hrs 57 mins
51 Radeon RX 6650XT
Navi 23 [Radeon RX 6650XT]
AMD Navi 23 1,747,339 309,621 5.64 4 hrs 15 mins
52 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,694,521 89,591 18.91 1 hrs 16 mins
53 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,609,371 131,890 12.20 1 hrs 58 mins
54 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,580,554 68,000 23.24 1 hrs 2 mins
55 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,574,991 300,925 5.23 4 hrs 35 mins
56 GeForce RTX 3050 8GB
GA107 [GeForce RTX 3050 8GB]
Nvidia GA107 1,527,362 306,405 4.98 4 hrs 49 mins
57 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,490,466 120,048 12.42 1 hrs 56 mins
58 P104-100
GP104 [P104-100]
Nvidia GP104 1,410,412 68,000 20.74 1 hrs 9 mins
59 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,251,063 248,524 5.03 4 hrs 46 mins
60 Geforce RTX 3050
GA106 [Geforce RTX 3050]
Nvidia GA106 1,202,592 68,000 17.69 1 hrs 21 mins
61 RTX A2000 12GB
GA106 [RTX A2000 12GB]
Nvidia GA106 1,169,881 68,000 17.20 1 hrs 24 mins
62 Radeon Pro W5700
Navi 10 [Radeon Pro W5700]
AMD Navi 10 1,148,112 275,301 4.17 5 hrs 45 mins
63 Radeon RX 6600/6600 XT/6600M
Navi 23 XT-XL [Radeon RX 6600/6600 XT/6600M]
AMD Navi 23 XT-XL 1,114,932 186,180 5.99 4 hrs 0 mins
64 GeForce RTX 3050 Ti Mobile
GA107M [GeForce RTX 3050 Ti Mobile]
Nvidia GA107M 1,023,130 268,895 3.80 6 hrs 18 mins
65 P106-100
GP106 [P106-100]
Nvidia GP106 1,012,080 258,774 3.91 6 hrs 8 mins
66 RX 5600 OEM/5600XT/5700/5700XT
Navi 10 [RX 5600 OEM/5600XT/5700/5700XT]
AMD Navi 10 996,008 200,993 4.96 4 hrs 51 mins
67 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 961,703 68,000 14.14 1 hrs 42 mins
68 GeForce RTX 3050 6GB
GA107 [GeForce RTX 3050 6GB]
Nvidia GA107 930,320 68,000 13.68 1 hrs 45 mins
69 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 883,745 68,000 13.00 1 hrs 51 mins
70 GeForce GTX 1660 Mobile
TU116M [GeForce GTX 1660 Mobile]
Nvidia TU116M 855,055 242,418 3.53 6 hrs 48 mins
71 GeForce GTX 1650
TU116 [GeForce GTX 1650] 3091
Nvidia TU116 742,781 68,000 10.92 2 hrs 12 mins
72 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 734,295 125,267 5.86 4 hrs 6 mins
73 Ryzen 7000 Series iGPU
Raphael [Ryzen 7000 Series iGPU]
AMD Raphael 689,325 73,786 9.34 2 hrs 34 mins
74 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 616,397 68,000 9.06 2 hrs 39 mins
75 RX 5500/5500M/Pro 5500M
Navi 14 [RX 5500/5500M/Pro 5500M]
AMD Navi 14 603,226 219,001 2.75 8 hrs 43 mins
76 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 445,067 79,868 5.57 4 hrs 18 mins
77 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 431,277 68,000 6.34 3 hrs 47 mins
78 GeForce GTX 1650
TU106 [GeForce GTX 1650]
Nvidia TU106 276,320 68,000 4.06 5 hrs 54 mins
79 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 130,290 82,910 1.57 15 hrs 16 mins
80 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 106,695 68,000 1.57 15 hrs 18 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:31:05
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 9 5950X 16-CORE 32 AMD
2 CORE I9-14900K 32 Intel
3 CORE I9-14900KF 24 Intel