RESEARCH: ALCHEMICAL-BINDING-FREE-ENERGY
FOLDING PROJECT #12602 PROFILE
PROJECT TEAM
Manager(s): David L. DotsonInstitution: Chodera Lab
WORK UNIT INFO
Atoms: 30,000Core: 0x26
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Alchemiscale lets people design experiments to calculate how molecules bind together. These experiments are then run on powerful computers donated by Folding@Home users. Think of it like a crowdsourced lab for studying chemistry!
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
Energy difference between a bound and unbound molecule.
Relative binding free energy describes the stability of a molecule when bound to another molecule. It's calculated by comparing the energy of the bound complex to the energy of the individual molecules when separated. This value is crucial in drug discovery as it helps predict how effectively a drug molecule binds to its target.
alchemiscale.org
A web platform for collaborative drug discovery.
Alchemiscale.org is a platform that allows researchers to share and collaborate on computational drug discovery projects. It provides tools for modeling molecular interactions, simulating protein folding, and analyzing large datasets. This platform fosters open science and accelerates the development of new drugs.
Networks of alchemical transformations
Sets of computational steps used to modify molecular properties.
Networks of alchemical transformations represent a series of computational steps that can be applied to molecules. These transformations allow researchers to explore different chemical modifications and predict their effects on molecular properties, such as binding affinity or stability. This approach is valuable for optimizing drug candidates.
PROJECTs
Project for Execution by Folding@Home.
PROJECTs stands for 'Projects for Execution by Folding@Home.' This refers to computational tasks submitted to the Folding@Home distributed computing platform. These projects often involve complex simulations and analyses that require significant processing power.
Folding@Home
A distributed computing platform for scientific research.
Folding@Home is a platform that harnesses the processing power of volunteers' computers to perform complex simulations. It's primarily used in computational biology to study protein folding and other biological processes. The Folding@Home platform has made significant contributions to drug discovery by enabling researchers to simulate molecular interactions and screen potential drug candidates.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:34:04|
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 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 5,899,188 | 54,351 | 108.54 | 0 hrs 13 mins |
| 2 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 3,146,329 | 62,162 | 50.61 | 0 hrs 28 mins |
| 3 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 2,490,814 | 34,950 | 71.27 | 0 hrs 20 mins |
| 4 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 2,194,603 | 54,898 | 39.98 | 0 hrs 36 mins |
| 5 | TITAN V GV100 [TITAN V] M 12288 |
Nvidia | GV100 | 2,174,858 | 7,315 | 297.31 | 0 hrs 5 mins |
| 6 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,986,354 | 53,242 | 37.31 | 0 hrs 39 mins |
| 7 | RTX A1000 GA107GL [RTX A1000] |
Nvidia | GA107GL | 1,672,198 | 7,315 | 228.60 | 0 hrs 6 mins |
| 8 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,126,239 | 7,315 | 153.96 | 0 hrs 9 mins |
| 9 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 272,841 | 7,315 | 37.30 | 0 hrs 39 mins |
| 10 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 206,117 | 7,315 | 28.18 | 0 hrs 51 mins |
| 11 | GeForce GTX Titan X GM200 [GeForce GTX Titan X] 6144 |
Nvidia | GM200 | 158,918 | 7,315 | 21.72 | 1 hrs 6 mins |
| 12 | Vega Mobile 5000 series APU Cezanne [Vega Mobile 5000 series APU] |
AMD | Cezanne | 113,265 | 20,786 | 5.45 | 4 hrs 24 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:34:04|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
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