RESEARCH: ALCHEMICAL-BINDING-ENERGY
FOLDING PROJECT #12601 PROFILE
PROJECT TEAM
Manager(s): David L. DotsonInstitution: Chodera Lab
WORK UNIT INFO
Atoms: 50,000Core: 0x26
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Alchemiscale lets users design experiments to study how molecules bind together. These experiments are then run by volunteers' computers through Folding@Home, a project that uses computing power for scientific research.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Relative binding free energy calculations orchestrated via alchemiscale.org.
Networks of alchemical transformations are submitted by alchemiscale users, and transformations that can be performed by Folding@Home are executed via these PROJECTs.
RELATED TERMS GLOSSARY AI BETA
Relative binding free energy
The difference in free energy between a ligand bound to a receptor and the unbound state.
Relative binding free energy calculations help scientists understand how strongly a molecule (ligand) binds to another molecule (receptor). This information is crucial for drug development as it allows researchers to identify molecules that effectively bind to specific targets in the body.
alchemiscale.org
A platform for collaborative drug discovery using alchemical transformations.
Alchemiscale.org is a web-based platform that facilitates the development of new drugs by enabling researchers to share and execute computational experiments involving molecular simulations.
Networks
Interconnected structures of nodes and edges.
In the context of alchemiscale.org, networks represent connections between different computational tasks or molecules involved in drug discovery.
PROJECTs
Project for the execution of alchemical transformations.
PROJECTs are computational tasks submitted to the Folding@Home platform via alchemiscale.org. These projects involve simulating molecular interactions and contribute to the discovery of new drugs.
Folding@Home
A distributed computing platform for scientific research.
Folding@Home is a network of volunteer computers that work together to perform complex simulations. In the context of alchemiscale.org, Folding@Home is used to execute computational projects related to drug discovery.
alchemical transformations
Changes in the structure of molecules that are simulated computationally.
Alchemical transformations involve simulating modifications to molecular structures. This allows researchers to explore how changes in a molecule's properties affect its interactions with other molecules, which is crucial for drug design.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:34:05|
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 4080 SUPER AD103 [GeForce RTX 4080 SUPER] |
Nvidia | AD103 | 34,338,552 | 46,725 | 734.91 | 0 hrs 2 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 32,170,099 | 46,725 | 688.50 | 0 hrs 2 mins |
| 3 | GeForce RTX 5090 GB202 [GeForce RTX 5090] |
Nvidia | GB202 | 24,947,081 | 46,725 | 533.91 | 0 hrs 3 mins |
| 4 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 17,134,634 | 315,007 | 54.39 | 0 hrs 26 mins |
| 5 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 15,128,943 | 307,828 | 49.15 | 0 hrs 29 mins |
| 6 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 11,474,178 | 192,511 | 59.60 | 0 hrs 24 mins |
| 7 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 10,009,505 | 316,178 | 31.66 | 0 hrs 45 mins |
| 8 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 9,893,902 | 222,555 | 44.46 | 0 hrs 32 mins |
| 9 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 7,991,027 | 46,725 | 171.02 | 0 hrs 8 mins |
| 10 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 7,840,997 | 289,160 | 27.12 | 0 hrs 53 mins |
| 11 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 7,113,376 | 46,725 | 152.24 | 0 hrs 9 mins |
| 12 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 6,514,238 | 277,064 | 23.51 | 1 hrs 1 mins |
| 13 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 6,461,547 | 46,725 | 138.29 | 0 hrs 10 mins |
| 14 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 6,431,394 | 271,169 | 23.72 | 1 hrs 1 mins |
| 15 | TITAN V GV100 [TITAN V] M 12288 |
Nvidia | GV100 | 6,173,690 | 46,725 | 132.13 | 0 hrs 11 mins |
| 16 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 5,416,197 | 256,908 | 21.08 | 1 hrs 8 mins |
| 17 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 5,319,324 | 82,502 | 64.48 | 0 hrs 22 mins |
| 18 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 5,104,148 | 240,817 | 21.20 | 1 hrs 8 mins |
| 19 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 3,946,695 | 46,725 | 84.47 | 0 hrs 17 mins |
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| 20 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 3,875,795 | 118,853 | 32.61 | 0 hrs 44 mins |
| 21 | GeForce RTX 3060 GA104 [GeForce RTX 3060] |
Nvidia | GA104 | 3,855,395 | 46,725 | 82.51 | 0 hrs 17 mins |
| 22 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 3,773,769 | 171,186 | 22.04 | 1 hrs 5 mins |
| 23 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 3,693,588 | 226,904 | 16.28 | 1 hrs 28 mins |
| 24 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 3,398,952 | 220,595 | 15.41 | 1 hrs 33 mins |
| 25 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 Super] |
Nvidia | TU106 | 2,870,967 | 46,725 | 61.44 | 0 hrs 23 mins |
| 26 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 2,861,215 | 46,725 | 61.24 | 0 hrs 24 mins |
| 27 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 2,806,804 | 207,256 | 13.54 | 1 hrs 46 mins |
| 28 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 2,751,634 | 46,725 | 58.89 | 0 hrs 24 mins |
| 29 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 2,743,636 | 46,725 | 58.72 | 0 hrs 25 mins |
| 30 | RTX A1000 GA107GL [RTX A1000] |
Nvidia | GA107GL | 2,721,071 | 46,725 | 58.24 | 0 hrs 25 mins |
| 31 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 2,639,890 | 46,725 | 56.50 | 0 hrs 25 mins |
| 32 | RTX A2000 12GB GA106 [RTX A2000 12GB] |
Nvidia | GA106 | 2,235,250 | 46,725 | 47.84 | 0 hrs 30 mins |
| 33 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,220,653 | 46,725 | 47.53 | 0 hrs 30 mins |
| 34 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 2,059,269 | 46,725 | 44.07 | 0 hrs 33 mins |
| 35 | GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile] |
Nvidia | TU116M | 1,633,113 | 172,334 | 9.48 | 2 hrs 32 mins |
| 36 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 1,584,482 | 170,264 | 9.31 | 2 hrs 35 mins |
| 37 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 1,460,708 | 163,632 | 8.93 | 2 hrs 41 mins |
| 38 | GeForce GTX 1070 Mobile GP104BM [GeForce GTX 1070 Mobile] 6463 |
Nvidia | GP104BM | 1,178,105 | 46,725 | 25.21 | 0 hrs 57 mins |
| 39 | RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590] |
AMD | Ellesmere XT | 821,178 | 137,451 | 5.97 | 4 hrs 1 mins |
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| 40 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 808,375 | 100,987 | 8.00 | 2 hrs 60 mins |
| 41 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 807,230 | 46,725 | 17.28 | 1 hrs 23 mins |
| 42 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 664,066 | 46,725 | 14.21 | 1 hrs 41 mins |
| 43 | GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti] |
Nvidia | AD106 | 614,191 | 27,851 | 22.05 | 1 hrs 5 mins |
| 44 | Radeon R9 285/380 Tonga PRO [Radeon R9 285/380] |
AMD | Tonga PRO | 457,686 | 114,591 | 3.99 | 6 hrs 1 mins |
| 45 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 324,176 | 46,725 | 6.94 | 3 hrs 28 mins |
| 46 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 242,793 | 46,725 | 5.20 | 4 hrs 37 mins |
| 47 | Ryzen 7000 Series iGPU Raphael [Ryzen 7000 Series iGPU] |
AMD | Raphael | 74,962 | 62,420 | 1.20 | 19 hrs 59 mins |
| 48 | FirePro W2100 Oland GL [FirePro W2100] |
AMD | Oland GL | 28,337 | 46,725 | 0.61 | 39 hrs 34 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:34:05|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|