RESEARCH: CANCER
FOLDING PROJECT #18227 PROFILE
PROJECT TEAM
Manager(s): Justin MillerInstitution: University of Pennsylvania
WORK UNIT INFO
Atoms: 383,200Core: 0x23
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project uses computer simulations to study how the protein Phosphoglycerate kinase (PGK) works. PGK is important for energy production in cells and problems with it can cause health issues. By simulating PGK, researchers hope to understand its structure and function better. They are also testing different simulation methods to see which ones are most accurate.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
In this project we simulate the protein Phosphoglycerate kinase (PGK), a vital component in cell metabolism (specifically glycolysis, the processing of sugar into ATP for the cell).
PGK catalyzes the conversion of 1,3 bisphosphoglycerate to 3-phosphoglycerate generating one molecule of ATP in the process.
While the biochemical activity of PGK has been long understoon, how this process is achieved from a structural perspective is less well known. PGK deficiencies lead to hemolytic anemia and myopathy, over-expression has been linked to a variety of cancers, and PGK can metabolize a variety of different drugs.
We hope that simulations of PGK will lead to a better understanding of how PGK completes these essential catalytic activities. In our prior projects we have looked at the impact of ligands on PGK conformations.
As our experimental collaborators have several biophysical measurements of PGK, we also believe this gives us an excellent opportunity to assess how force fields, one of the fundamental processes of our computer simulations, affect the accuracy of our simulations.
In project 18224, we looked at a commonly used force field, charmm36 performed.
In 18227 and 18228, we look at how the force fields amber03 and amber14sb perform.
We believe these findings will aid not only this project, but all simulation projects going forward.
RELATED TERMS GLOSSARY AI BETA
Phosphoglycerate kinase
Enzyme catalyzing a key step in glycolysis.
Phosphoglycerate kinase (PGK) is an enzyme essential for cellular energy production. It plays a crucial role in glycolysis, the process of breaking down sugar to generate ATP (the cell's energy currency). PGK catalyzes a specific reaction converting 1,3-bisphosphoglycerate to 3-phosphoglycerate, releasing energy used to form ATP.
Glycolysis
Metabolic pathway converting glucose to pyruvate.
Glycolysis is a fundamental metabolic pathway that breaks down glucose into pyruvate. This process occurs in the cytoplasm of cells and is essential for energy production. During glycolysis, glucose is sequentially converted through several enzymatic reactions, ultimately generating ATP (the cell's energy currency) and pyruvate.
ATP
Adenosine triphosphate
ATP (Adenosine Triphosphate) is the primary energy currency of cells. It stores and releases energy in a readily usable form for cellular processes such as muscle contraction, protein synthesis, and nerve impulse transmission.
Hemolytic anemia
Anemia caused by red blood cell destruction.
Hemolytic anemia is a type of anemia characterized by the premature destruction of red blood cells. This can lead to fatigue, weakness, pale skin, and shortness of breath. Causes include genetic disorders, autoimmune diseases, infections, and certain medications.
Myopathy
Disease affecting muscle function.
Myopathy is a general term for any disease that affects muscle function. This can lead to weakness, pain, stiffness, and difficulty moving. Causes include genetic disorders, infections, autoimmune diseases, and certain medications.
Cancer
Uncontrolled cell growth.
Cancer is a group of diseases characterized by uncontrolled cell growth and spread. This can damage surrounding tissues and organs. Causes include genetic mutations, environmental factors, and lifestyle choices.
Force field
Model of molecular interactions.
A force field is a mathematical model used in computer simulations to represent the interactions between atoms and molecules. It describes how atoms attract and repel each other based on their distance and electronic properties. Force fields are essential for simulating the behavior of complex biological systems.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:31:15|
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 | 42,215,121 | 101,000 | 417.97 | 0 hrs 3 mins |
| 2 | GeForce RTX 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 28,622,787 | 101,000 | 283.39 | 0 hrs 5 mins |
| 3 | GeForce RTX 5080 GB203 [GeForce RTX 5080] |
Nvidia | GB203 | 22,340,936 | 104,613 | 213.56 | 0 hrs 7 mins |
| 4 | GeForce RTX 4080 SUPER AD103 [GeForce RTX 4080 SUPER] |
Nvidia | AD103 | 21,518,333 | 110,702 | 194.38 | 0 hrs 7 mins |
| 5 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 21,317,349 | 133,589 | 159.57 | 0 hrs 9 mins |
| 6 | GeForce RTX 5070 Ti GB203 [GeForce RTX 5070 Ti] |
Nvidia | GB203 | 19,154,959 | 101,000 | 189.65 | 0 hrs 8 mins |
| 7 | GeForce RTX 4090 Laptop GPU AD103M / GN21-X11 [GeForce RTX 4090 Laptop GPU] |
Nvidia | AD103M / GN21-X11 | 14,215,317 | 101,000 | 140.75 | 0 hrs 10 mins |
| 8 | GeForce RTX 4070 Ti SUPER AD103 [GeForce RTX 4070 Ti SUPER] |
Nvidia | AD103 | 13,478,652 | 259,032 | 52.03 | 0 hrs 28 mins |
| 9 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 13,477,314 | 797,257 | 16.90 | 1 hrs 25 mins |
| 10 | GeForce RTX 5070 GB205 [GeForce RTX 5070] |
Nvidia | GB205 | 12,507,860 | 101,000 | 123.84 | 0 hrs 12 mins |
| 11 | GeForce RTX 4070 SUPER AD104 [GeForce RTX 4070 SUPER] |
Nvidia | AD104 | 11,018,866 | 251,079 | 43.89 | 0 hrs 33 mins |
| 12 | RTX 5000 Ada Generation Laptop GPU AD103GLM [RTX 5000 Ada Generation Laptop GPU] |
Nvidia | AD103GLM | 10,625,529 | 736,658 | 14.42 | 1 hrs 40 mins |
| 13 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 8,956,066 | 632,089 | 14.17 | 1 hrs 42 mins |
| 14 | GeForce RTX 5060 Ti GB206 [GeForce RTX 5060 Ti] |
Nvidia | GB206 | 8,841,135 | 101,000 | 87.54 | 0 hrs 16 mins |
| 15 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 8,498,310 | 466,334 | 18.22 | 1 hrs 19 mins |
| 16 | GeForce RTX 4070 AD104 [GeForce RTX 4070] |
Nvidia | AD104 | 8,303,473 | 253,808 | 32.72 | 0 hrs 44 mins |
| 17 | Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE] |
AMD | Navi 31 | 7,466,761 | 477,166 | 15.65 | 1 hrs 32 mins |
| 18 | GeForce RTX 4070 Max-Q / Mobile AD106M [GeForce RTX 4070 Max-Q / Mobile] |
Nvidia | AD106M | 7,278,360 | 101,000 | 72.06 | 0 hrs 20 mins |
| 19 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 6,876,473 | 607,550 | 11.32 | 2 hrs 7 mins |
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| 20 | GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti] |
Nvidia | AD106 | 6,545,685 | 602,884 | 10.86 | 2 hrs 13 mins |
| 21 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 6,405,016 | 600,313 | 10.67 | 2 hrs 15 mins |
| 22 | TITAN RTX TU102 [TITAN RTX] 16310 |
Nvidia | TU102 | 6,398,400 | 101,000 | 63.35 | 0 hrs 23 mins |
| 23 | TITAN V GV100 [TITAN V] M 12288 |
Nvidia | GV100 | 5,786,899 | 101,000 | 57.30 | 0 hrs 25 mins |
| 24 | GeForce RTX 5080 Max-Q / Mobile GB203M / GN22-X9 [GeForce RTX 5080 Max-Q / Mobile] |
Nvidia | GB203M / GN22-X9 | 5,581,243 | 101,000 | 55.26 | 0 hrs 26 mins |
| 25 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 5,319,670 | 551,602 | 9.64 | 2 hrs 29 mins |
| 26 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,230,769 | 101,000 | 51.79 | 0 hrs 28 mins |
| 27 | Radeon RX 9070(XT) Navi 48 [Radeon RX 9070(XT)] |
AMD | Navi 48 | 5,080,687 | 137,513 | 36.95 | 0 hrs 39 mins |
| 28 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,043,521 | 101,000 | 49.94 | 0 hrs 29 mins |
| 29 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,667,488 | 512,761 | 9.10 | 2 hrs 38 mins |
| 30 | Radeon RX 6800(XT)/6900XT Navi 21 [Radeon RX 6800(XT)/6900XT] |
AMD | Navi 21 | 4,076,887 | 405,703 | 10.05 | 2 hrs 23 mins |
| 31 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,070,418 | 523,999 | 7.77 | 3 hrs 5 mins |
| 32 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 Super] |
Nvidia | TU104 | 3,979,025 | 101,000 | 39.40 | 0 hrs 37 mins |
| 33 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 3,776,188 | 288,284 | 13.10 | 1 hrs 50 mins |
| 34 | Radeon RX 7700XT/7800XT Navi 32 [Radeon RX 7700XT/7800XT] |
AMD | Navi 32 | 3,769,272 | 101,000 | 37.32 | 0 hrs 39 mins |
| 35 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 3,551,306 | 176,859 | 20.08 | 1 hrs 12 mins |
| 36 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,435,122 | 342,529 | 10.03 | 2 hrs 24 mins |
| 37 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 3,310,515 | 444,847 | 7.44 | 3 hrs 13 mins |
| 38 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 3,295,471 | 443,719 | 7.43 | 3 hrs 14 mins |
| 39 | GeForce RTX 4050 Max-Q / Mobile AD107M [GeForce RTX 4050 Max-Q / Mobile] |
Nvidia | AD107M | 3,237,600 | 498,077 | 6.50 | 3 hrs 42 mins |
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|
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| 40 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,128,340 | 491,044 | 6.37 | 3 hrs 46 mins |
| 41 | RTX A4000 GA104GL [RTX A4000] |
Nvidia | GA104GL | 3,064,160 | 101,000 | 30.34 | 0 hrs 47 mins |
| 42 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,965,061 | 484,904 | 6.11 | 3 hrs 55 mins |
| 43 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,774,974 | 758,096 | 3.66 | 6 hrs 33 mins |
| 44 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 2,698,385 | 466,881 | 5.78 | 4 hrs 9 mins |
| 45 | RTX 2000 Ada Generation Laptop GPU AD107GLM [RTX 2000 Ada Generation Laptop GPU] |
Nvidia | AD107GLM | 2,646,214 | 470,034 | 5.63 | 4 hrs 16 mins |
| 46 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,620,948 | 434,760 | 6.03 | 3 hrs 59 mins |
| 47 | GeForce RTX 4060 Max-Q / Mobile AD107M [GeForce RTX 4060 Max-Q / Mobile] |
Nvidia | AD107M | 2,200,152 | 342,547 | 6.42 | 3 hrs 44 mins |
| 48 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,871,014 | 101,000 | 18.52 | 1 hrs 18 mins |
| 49 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 1,855,469 | 159,757 | 11.61 | 2 hrs 4 mins |
| 50 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 1,596,687 | 101,000 | 15.81 | 1 hrs 31 mins |
| 51 | RTX A2000 12GB GA106 [RTX A2000 12GB] |
Nvidia | GA106 | 1,526,538 | 101,000 | 15.11 | 1 hrs 35 mins |
| 52 | Radeon RX 6700(XT)/6800M Navi 22 XT-XL [Radeon RX 6700(XT)/6800M] |
AMD | Navi 22 XT-XL | 1,438,188 | 101,000 | 14.24 | 1 hrs 41 mins |
| 53 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,216,422 | 101,000 | 12.04 | 1 hrs 60 mins |
| 54 | Radeon RX 6600(XT/M) Navi 23 XT-XL [Radeon RX 6600(XT/M)] |
AMD | Navi 23 XT-XL | 1,104,271 | 335,671 | 3.29 | 7 hrs 18 mins |
| 55 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 817,460 | 276,943 | 2.95 | 8 hrs 8 mins |
| 56 | R9 Fury X/NANO Fiji XT [R9 Fury X/NANO] |
AMD | Fiji XT | 649,341 | 101,000 | 6.43 | 3 hrs 44 mins |
| 57 | GeForce GTX 1650 TU106 [GeForce GTX 1650] |
Nvidia | TU106 | 480,630 | 101,000 | 4.76 | 5 hrs 3 mins |
| 58 | RX 5500/5500M/Pro 5500M Navi 14 [RX 5500/5500M/Pro 5500M] |
AMD | Navi 14 | 432,810 | 253,458 | 1.71 | 14 hrs 3 mins |
| 59 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 165,457 | 101,000 | 1.64 | 14 hrs 39 mins |
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| 60 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 124,118 | 101,000 | 1.23 | 19 hrs 32 mins |
| 61 | Vega Mobile APU Lucienne [Vega Mobile APU] |
AMD | Lucienne | 28,373 | 101,000 | 0.28 | 85 hrs 26 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:31:15|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|---|---|---|---|---|
| 1 | RYZEN 5 3600X 6-CORE | 12 | AMD | ||
| 2 | RYZEN 7 5700X 8-CORE | 16 | AMD |