RESEARCH: IL-2-FORCE-FIELD-BENCHMARKING
FOLDING PROJECT #18279 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 43,881
Core: 0x27
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project compares computer simulations of human interleukin-2 (IL-2), a molecule that controls immune cells, to real-world data. IL-2 can either boost or weaken the immune system, and scientists are trying to understand how it works so they can design better treatments.

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

OFFICAL PROJECT DESCRIPTION

As part of our ongoing effort to benchmark the most popular force field and water combinations, this project series focuses on human interleukin-2 (IL-2).

Our aim is to compare the results of these simulations to experimental nuclear magnetic resonance (NMR) spectroscopy data. Human interleukin-2 (IL-2) is an important signaling molecule, or cytokine, for the regulation of T-cell activity.

IL-2 can act as a promotor or inhibitor in immune cells depending on which of its receptors are bound.

There have been efforts to modify IL-2’s receptor binding sites to bias its activity towards either promoting or inhibiting immune cells.

However, the dynamics underlying IL-2 receptor recognition and binding are still not fully understood.

In addition to quantifying force field accuracy, a better understanding of these dynamics will help design IL-2 variants with more specific activity, thus improving its potential as a therapeutic.
p18278- amber03 with tip3p water 18279 - amber19sb with opc water p18280- amber99sb-disp with aadisp water p18281- charmm36m with tip3p water p18282- amber99sb-star-ILDN with tip4p water p18283- amber99sb-star-ILDN with tip4pd water.

RELATED TERMS GLOSSARY AI BETA

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

interleukin-2

A signaling molecule that regulates T cell activity.

Scientific: Biotechnology
Immunology / Cytokines

Interleukin-2 (IL-2) is a crucial protein involved in the immune system. It helps control how T cells, a type of white blood cell, behave. IL-2 can either stimulate or suppress T cell activity depending on the receptors it binds to. Researchers are exploring ways to modify IL-2 to make it more specific in its actions, potentially leading to better treatments for diseases.


cytokine

A type of protein that regulates immune responses.

Scientific: Biotechnology
Immunology / Signaling Molecules

Cytokines are small proteins that act as messengers in the immune system. They help cells communicate with each other and coordinate immune responses to infections or injuries. There are many different types of cytokines, each with specific functions. For example, some cytokines promote inflammation, while others suppress it.


T-cell

A type of white blood cell that plays a key role in the immune response.

Scientific: Biotechnology
Immunology / Lymphocytes

T cells are a crucial part of the adaptive immune system. They recognize and destroy infected or cancerous cells. There are different types of T cells, each with specific functions. For example, helper T cells coordinate the immune response, while cytotoxic T cells directly kill infected cells.


receptor

A protein that binds to a specific molecule (ligand) and triggers a cellular response.

Scientific: Biotechnology
Biology / Cellular Signaling

Receptors are proteins found on the surface of cells. They act like antennas, receiving signals from outside the cell. When a receptor binds to its specific ligand, it initiates a series of events inside the cell, leading to a particular response. For example, hormone receptors trigger changes in gene expression, while neurotransmitter receptors control nerve impulses.


NMR spectroscopy

Nuclear Magnetic Resonance Spectroscopy

Scientific: Biotechnology
Biochemistry / Structural Analysis

NMR spectroscopy is a powerful technique used to study the structure and dynamics of molecules. It relies on the magnetic properties of atomic nuclei to provide information about the arrangement of atoms within a molecule. NMR spectroscopy is widely used in biochemistry, drug discovery, and materials science.


force field

A set of mathematical equations that describes the interactions between atoms in a molecule.

Scientific: Biotechnology
Computational Chemistry / Molecular Simulations

Force fields are essential tools for molecular simulations. They provide a simplified model of how atoms interact with each other. By using force fields, scientists can simulate the behavior of molecules over time and study their properties. For example, force fields can be used to predict the shape of a protein or the binding affinity of a drug molecule.


simulations

Computer-based models that mimic the behavior of molecules.

Scientific: Biotechnology
Computational Chemistry / Molecular Dynamics

Simulations are a powerful tool for studying complex systems. In computational chemistry, simulations are used to model the behavior of molecules over time. By running simulations, scientists can gain insights into molecular structure, dynamics, and interactions. For example, simulations can be used to study protein folding, drug binding, or chemical reactions.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 23 June 2026 15:29:43
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 3,859,647 27,300 141.38 0 hrs 10 mins
2 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,756,979 27,300 100.99 0 hrs 14 mins
3 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,341,965 27,300 85.79 0 hrs 17 mins
4 GeForce RTX 2070 Mobile / Max-Q Refresh
TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh]
Nvidia TU106M 2,144,954 27,300 78.57 0 hrs 18 mins
5 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 2,132,988 27,300 78.13 0 hrs 18 mins
6 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 Super]
Nvidia TU106 2,081,022 124,777 16.68 1 hrs 26 mins
7 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 2,055,513 48,235 42.61 0 hrs 34 mins
8 P102-100
GP102 [P102-100]
Nvidia GP102 2,002,991 27,300 73.37 0 hrs 20 mins
9 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,904,946 166,669 11.43 2 hrs 6 mins
10 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,790,917 134,527 13.31 1 hrs 48 mins
11 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,464,939 27,300 53.66 0 hrs 27 mins
12 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,348,198 126,538 10.65 2 hrs 15 mins
13 GeForce RTX 3050 Ti Mobile
GA107M [GeForce RTX 3050 Ti Mobile]
Nvidia GA107M 1,337,786 155,468 8.60 2 hrs 47 mins
14 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,197,692 146,751 8.16 2 hrs 56 mins
15 P104-100
GP104 [P104-100]
Nvidia GP104 1,148,928 27,300 42.09 0 hrs 34 mins
16 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,114,779 32,118 34.71 0 hrs 41 mins
17 RX 5600 OEM/5600XT/5700(XT)
Navi 10 [RX 5600 OEM/5600XT/5700(XT)]
AMD Navi 10 1,052,402 27,300 38.55 0 hrs 37 mins
18 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,030,990 38,924 26.49 0 hrs 54 mins
19 P106-100
GP106 [P106-100]
Nvidia GP106 947,578 27,300 34.71 0 hrs 41 mins
20 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 914,391 27,300 33.49 0 hrs 43 mins
21 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 907,123 27,300 33.23 0 hrs 43 mins
22 CMP 30HX
TU116 [CMP 30HX]
Nvidia TU116 855,378 27,300 31.33 0 hrs 46 mins
23 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 791,442 129,243 6.12 3 hrs 55 mins
24 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 756,713 56,657 13.36 1 hrs 48 mins
25 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 669,669 27,300 24.53 0 hrs 59 mins
26 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 619,857 27,300 22.71 1 hrs 3 mins
27 GeForce GTX Titan X
GM200 [GeForce GTX Titan X] 6144
Nvidia GM200 499,273 103,112 4.84 4 hrs 57 mins
28 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 475,238 27,300 17.41 1 hrs 23 mins
29 Radeon PRO W6400
Navi 24 [Radeon PRO W6400]
AMD Navi 24 392,658 27,300 14.38 1 hrs 40 mins
30 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 392,542 27,300 14.38 1 hrs 40 mins
31 GeForce GTX 1650
TU106 [GeForce GTX 1650]
Nvidia TU106 391,328 27,300 14.33 1 hrs 40 mins
32 RX 5500(M)/Pro 5500M
Navi 14 [RX 5500(M)/Pro 5500M]
AMD Navi 14 387,442 27,300 14.19 1 hrs 41 mins
33 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 375,292 100,652 3.73 6 hrs 26 mins
34 Quadro M5000
GM204GL [Quadro M5000]
Nvidia GM204GL 337,708 27,300 12.37 1 hrs 56 mins
35 Radeon RX 6400/6500XT
Navi 24 [Radeon RX 6400/6500XT]
AMD Navi 24 324,365 96,192 3.37 7 hrs 7 mins
36 Radeon RX 6400 / 6500 XT
Navi 24 [Radeon RX 6400 / 6500 XT]
AMD Navi 24 302,025 27,300 11.06 2 hrs 10 mins
37 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 294,458 27,300 10.79 2 hrs 14 mins
38 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 285,781 52,187 5.48 4 hrs 23 mins
39 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 251,600 88,576 2.84 8 hrs 27 mins
40 Quadro K5200
GK110 [Quadro K5200]
Nvidia GK110 238,678 27,300 8.74 2 hrs 45 mins
41 Quadro T400 Mobile
TU117GLM [Quadro T400 Mobile]
Nvidia TU117GLM 206,402 27,300 7.56 3 hrs 10 mins
42 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 147,359 27,300 5.40 4 hrs 27 mins
43 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 70,235 43,862 1.60 14 hrs 59 mins
44 GeForce GT 710
GK208B [GeForce GT 710] 366
Nvidia GK208B 4,940 27,300 0.18 132 hrs 38 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 23 June 2026 15:29:43
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make