RESEARCH: IL-2-MOLECULAR-DYNAMICS
FOLDING PROJECT #18282 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 32,721
Core: 0x27
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project studies how different computer models simulate the human protein IL-2, which helps regulate our immune system. By comparing these simulations to real-world data, researchers hope to better understand how IL-2 works and design new versions that could be used as medicines.

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: Pharmaceuticals
Biotechnology / Immunology

Interleukin-2 (IL-2) is a signaling molecule crucial for the immune system. It stimulates the growth and activity of T cells, which are essential for fighting infections and diseases. Research focuses on understanding IL-2's role in immune responses and developing therapies that harness its power.


cytokine

A type of signaling protein produced by cells.

Scientific: Pharmaceuticals
Biotechnology / Immunology

Cytokines are small proteins that act as messengers between cells, particularly in the immune system. They regulate various immune responses, such as inflammation, cell growth, and differentiation. Cytokines play a vital role in fighting infections and maintaining immune homeostasis.


T-cell

A type of white blood cell involved in immune responses.

Scientific: Pharmaceuticals
Biotechnology / Immunology

T cells are a crucial part of the adaptive immune system. They recognize and destroy infected or abnormal cells, regulate other immune cells, and provide long-lasting immunity against specific pathogens. There are different types of T cells, each with specialized functions.


receptor

A protein that binds to a specific molecule, triggering a cellular response.

Scientific: Pharmaceuticals
Biotechnology / Molecular Biology

Receptors are proteins found on the surface of cells that bind to specific molecules, such as hormones, neurotransmitters, or drugs. This binding triggers a cascade of events inside the cell, leading to a specific response. Receptors play a vital role in cell communication and signal transduction.


NMR spectroscopy

Nuclear Magnetic Resonance Spectroscopy

Scientific: Pharmaceuticals
Biotechnology / Structural Biology

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 determine the spatial arrangement and interactions within a molecule.


force field

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

Scientific: Pharmaceuticals
Biotechnology / Computational Biology

Force fields are essential tools in computational biology and drug discovery. They allow scientists to simulate molecular behavior and predict how molecules will interact with each other. By refining force fields, researchers can improve the accuracy of their simulations.


simulation

A computer-based model of a real-world process.

Scientific: Pharmaceuticals
Biotechnology / Computational Biology

Simulations are powerful tools used in various fields, including biotechnology and drug discovery. They allow researchers to study complex systems and predict their behavior under different conditions. By running simulations, scientists can gain insights into biological processes and test hypotheses.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:30:34
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 3,310,987 18,400 179.94 0 hrs 8 mins
2 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 Super]
Nvidia TU106 2,312,332 32,862 70.36 0 hrs 20 mins
3 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,223,441 18,400 120.84 0 hrs 12 mins
4 Intel Arc B580 Graphics
Battlemage G21 [Intel Arc B580 Graphics]
Intel Battlemage G21 2,168,334 23,259 93.23 0 hrs 15 mins
5 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 1,970,362 18,400 107.08 0 hrs 13 mins
6 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,920,246 27,852 68.94 0 hrs 21 mins
7 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,776,454 18,400 96.55 0 hrs 15 mins
8 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,759,658 130,404 13.49 1 hrs 47 mins
9 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 1,722,671 117,961 14.60 1 hrs 39 mins
10 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,707,947 129,566 13.18 1 hrs 49 mins
11 P102-100
GP102 [P102-100]
Nvidia GP102 1,678,676 18,400 91.23 0 hrs 16 mins
12 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,663,592 18,400 90.41 0 hrs 16 mins
13 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,571,081 117,957 13.32 1 hrs 48 mins
14 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,297,495 86,156 15.06 1 hrs 36 mins
15 P104-100
GP104 [P104-100]
Nvidia GP104 1,217,417 18,400 66.16 0 hrs 22 mins
16 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,214,067 18,400 65.98 0 hrs 22 mins
17 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,194,401 22,328 53.49 0 hrs 27 mins
18 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,170,329 18,400 63.60 0 hrs 23 mins
19 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 994,032 18,400 54.02 0 hrs 27 mins
20 RX 5600 OEM/5600XT/5700(XT)
Navi 10 [RX 5600 OEM/5600XT/5700(XT)]
AMD Navi 10 985,859 18,400 53.58 0 hrs 27 mins
21 P106-100
GP106 [P106-100]
Nvidia GP106 977,465 18,400 53.12 0 hrs 27 mins
22 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 892,915 18,400 48.53 0 hrs 30 mins
23 GeForce RTX 3050 6GB
GA107 [GeForce RTX 3050 6GB]
Nvidia GA107 842,909 18,400 45.81 0 hrs 31 mins
24 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 832,387 101,131 8.23 2 hrs 55 mins
25 CMP 30HX
TU116 [CMP 30HX]
Nvidia TU116 830,185 18,400 45.12 0 hrs 32 mins
26 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 705,817 18,400 38.36 0 hrs 38 mins
27 Radeon Pro W5700
Navi 10 [Radeon Pro W5700]
AMD Navi 10 690,585 18,400 37.53 0 hrs 38 mins
28 GeForce GTX 1650
TU116 [GeForce GTX 1650] 3091
Nvidia TU116 665,346 34,299 19.40 1 hrs 14 mins
29 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 592,145 18,400 32.18 0 hrs 45 mins
30 GeForce RTX 3050 Ti Mobile
GA107BM [GeForce RTX 3050 Ti Mobile]
Nvidia GA107BM 569,439 18,400 30.95 0 hrs 47 mins
31 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 398,233 18,400 21.64 1 hrs 7 mins
32 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 396,201 18,400 21.53 1 hrs 7 mins
33 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 395,964 18,400 21.52 1 hrs 7 mins
34 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 369,832 75,404 4.90 4 hrs 54 mins
35 Radeon PRO W6400
Navi 24 [Radeon PRO W6400]
AMD Navi 24 355,166 18,400 19.30 1 hrs 15 mins
36 RX 5500(M)/Pro 5500M
Navi 14 [RX 5500(M)/Pro 5500M]
AMD Navi 14 335,369 18,400 18.23 1 hrs 19 mins
37 Quadro M5000
GM204GL [Quadro M5000]
Nvidia GM204GL 333,664 18,400 18.13 1 hrs 19 mins
38 Radeon RX 6400/6500XT
Navi 24 [Radeon RX 6400/6500XT]
AMD Navi 24 304,214 64,696 4.70 5 hrs 6 mins
39 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 266,830 28,197 9.46 2 hrs 32 mins
40 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 257,200 68,567 3.75 6 hrs 24 mins
41 GeForce RTX 3050 6GB Laptop GPU
GN20-P0-R-K2 [GeForce RTX 3050 6GB Laptop GPU]
Nvidia GN20-P0-R-K2 222,044 18,400 12.07 1 hrs 59 mins
42 Quadro T400 Mobile
TU117GLM [Quadro T400 Mobile]
Nvidia TU117GLM 214,823 18,400 11.68 2 hrs 3 mins
43 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 114,745 18,400 6.24 3 hrs 51 mins
44 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 94,183 49,892 1.89 12 hrs 43 mins
45 Radeon 760M/780M
Phoenix/Hawk Point [Radeon 760M/780M]
AMD Phoenix/Hawk Point 64,315 18,400 3.50 6 hrs 52 mins
46 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 62,154 29,703 2.09 11 hrs 28 mins
47 GeForce GT 730
GK208B [GeForce GT 730] 692.7
Nvidia GK208B 21,436 18,400 1.17 20 hrs 36 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 03:30:34
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make