RESEARCH: IL-2-FORCE-FIELD-BENCHMARKING
FOLDING PROJECT #18283 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 29,665
Core: 0x27
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project compares computer simulations of human interleukin-2 (IL-2) with real lab results to see which simulation methods are most accurate. IL-2 is a protein that controls how our immune system works, and understanding how it interacts with other proteins could help us develop 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 cytokine that regulates T-cell activity.

Scientific: Biotechnology
Immunology / Cytokines

Interleukin-2 (IL-2) is a crucial signaling molecule produced by immune cells. It plays a vital role in stimulating the growth and activity of T-cells, which are essential for fighting infections and diseases. IL-2 can either promote or inhibit immune responses depending on the specific receptors it binds to.


nuclear magnetic resonance

A technique used to determine the structure and dynamics of molecules.

Scientific: Pharmaceutical Research
Biochemistry / Spectroscopy

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical technique used to study the structure, dynamics, and interactions of molecules. It works by applying a magnetic field and radio waves to a sample, causing the atomic nuclei to resonate at specific frequencies. These resonance frequencies provide information about the chemical environment and bonding patterns within the molecule.


cytokine

A type of signaling molecule produced by immune cells.

Scientific: Biotechnology
Immunology / Signaling Molecules

Cytokines are small proteins that act as messengers between cells in the immune system. They play a crucial role in regulating immune responses, such as inflammation, cell growth, and differentiation. Examples of cytokines include interferons, interleukins, and chemokines.


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 type of lymphocyte, a specialized white blood cell involved in the adaptive immune system. They recognize and destroy infected or cancerous cells by releasing toxic substances or signaling other immune cells to attack. Different types of T-cells have specific functions, such as helper T-cells, which activate other immune cells, and cytotoxic T-cells, which directly kill target cells.


receptor

A protein that binds to a specific molecule.

Scientific: Pharmaceutical Research
Biochemistry / Protein Structure

Receptors are specialized proteins found on the surface or inside cells. They play a vital role in cell signaling by binding to specific molecules, called ligands. This binding triggers a cascade of events within the cell, leading to changes in gene expression, metabolism, or other cellular functions.


force field

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

Scientific: Biotechnology
Computational Chemistry / Molecular Dynamics

A force field is a computational model used in molecular dynamics simulations to describe the interactions between atoms and molecules. It consists of a set of mathematical equations that define the potential energy of a system based on the distances between atoms. Force fields are essential for simulating the behavior of molecules at the atomic level.


molecular dynamics

A computational method used to simulate the movement of atoms and molecules over time.

Scientific: Biotechnology
Computational Chemistry / Simulation Methods

Molecular dynamics (MD) is a powerful computational technique used to simulate the motion of atoms and molecules over time. By solving Newton's equations of motion for a system of interacting particles, MD simulations provide insights into the dynamic behavior of molecules, such as protein folding, ligand binding, and chemical reactions.


simulation

A computer-based representation of a real-world system.

Scientific: Biotechnology
Computational Chemistry / Modeling Techniques

Simulation is the process of creating a computer model that mimics the behavior of a real-world system. Simulations are widely used in various fields, such as science, engineering, and business, to study complex systems, predict outcomes, and optimize processes.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:30:32
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 11,497,846 18,000 638.77 0 hrs 2 mins
2 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 2,951,132 18,000 163.95 0 hrs 9 mins
3 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 Super]
Nvidia TU106 2,478,365 26,816 92.42 0 hrs 16 mins
4 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,021,384 18,000 112.30 0 hrs 13 mins
5 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,898,804 153,621 12.36 1 hrs 57 mins
6 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 1,865,121 18,000 103.62 0 hrs 14 mins
7 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,826,621 21,202 86.15 0 hrs 17 mins
8 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,802,666 113,029 15.95 1 hrs 30 mins
9 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,736,046 123,646 14.04 1 hrs 43 mins
10 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,705,306 18,000 94.74 0 hrs 15 mins
11 Intel Arc B580 Graphics
Battlemage G21 [Intel Arc B580 Graphics]
Intel Battlemage G21 1,470,171 18,000 81.68 0 hrs 18 mins
12 P102-100
GP102 [P102-100]
Nvidia GP102 1,422,536 18,000 79.03 0 hrs 18 mins
13 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,349,140 18,000 74.95 0 hrs 19 mins
14 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,334,589 83,435 16.00 1 hrs 30 mins
15 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 1,268,603 18,000 70.48 0 hrs 20 mins
16 P104-100
GP104 [P104-100]
Nvidia GP104 1,168,009 18,000 64.89 0 hrs 22 mins
17 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,142,951 31,075 36.78 0 hrs 39 mins
18 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 982,216 18,000 54.57 0 hrs 26 mins
19 RX 5600 OEM/5600XT/5700(XT)
Navi 10 [RX 5600 OEM/5600XT/5700(XT)]
AMD Navi 10 977,660 18,000 54.31 0 hrs 27 mins
20 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 969,598 42,004 23.08 1 hrs 2 mins
21 P106-100
GP106 [P106-100]
Nvidia GP106 934,118 18,000 51.90 0 hrs 28 mins
22 GeForce RTX 3050 Ti Mobile
GA107M [GeForce RTX 3050 Ti Mobile]
Nvidia GA107M 901,213 18,000 50.07 0 hrs 29 mins
23 CMP 30HX
TU116 [CMP 30HX]
Nvidia TU116 893,113 18,000 49.62 0 hrs 29 mins
24 GeForce GTX 1650
TU106 [GeForce GTX 1650]
Nvidia TU106 862,361 18,000 47.91 0 hrs 30 mins
25 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 861,355 100,888 8.54 2 hrs 49 mins
26 Radeon Pro W5700
Navi 10 [Radeon Pro W5700]
AMD Navi 10 860,738 18,000 47.82 0 hrs 30 mins
27 GeForce GTX 1650
TU116 [GeForce GTX 1650] 3091
Nvidia TU116 838,226 18,000 46.57 0 hrs 31 mins
28 GeForce RTX 3050 6GB
GA107 [GeForce RTX 3050 6GB]
Nvidia GA107 723,375 18,000 40.19 0 hrs 36 mins
29 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 622,410 61,393 10.14 2 hrs 22 mins
30 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 553,572 18,000 30.75 0 hrs 47 mins
31 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 426,328 18,000 23.68 1 hrs 1 mins
32 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 420,361 78,094 5.38 4 hrs 28 mins
33 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 419,955 18,000 23.33 1 hrs 2 mins
34 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 389,860 18,000 21.66 1 hrs 6 mins
35 RX 5500(M)/Pro 5500M
Navi 14 [RX 5500(M)/Pro 5500M]
AMD Navi 14 366,203 18,000 20.34 1 hrs 11 mins
36 Radeon PRO W6400
Navi 24 [Radeon PRO W6400]
AMD Navi 24 348,361 18,000 19.35 1 hrs 14 mins
37 Quadro M5000
GM204GL [Quadro M5000]
Nvidia GM204GL 346,586 18,000 19.25 1 hrs 15 mins
38 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 272,541 68,766 3.96 6 hrs 3 mins
39 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 256,056 37,038 6.91 3 hrs 28 mins
40 Quadro K5200
GK110 [Quadro K5200]
Nvidia GK110 241,562 18,000 13.42 1 hrs 47 mins
41 GeForce GTX Titan X
GM200 [GeForce GTX Titan X] 6144
Nvidia GM200 206,194 63,919 3.23 7 hrs 26 mins
42 Quadro T400 Mobile
TU117GLM [Quadro T400 Mobile]
Nvidia TU117GLM 205,054 18,000 11.39 2 hrs 6 mins
43 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 102,823 50,004 2.06 11 hrs 40 mins
44 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 79,917 32,929 2.43 9 hrs 53 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 03:30:32
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make