RESEARCH: ALCHEMICAL-BINDING-FREE-ENERGY
FOLDING PROJECT #12600 PROFILE
PROJECT TEAM
Manager(s): David L. DotsonInstitution: Chodera Lab
WORK UNIT INFO
Atoms: 10,000Core: 0x26
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
People use alchemiscale.org to design experiments that calculate how strongly molecules bind together. These experiments are then run by computers through Folding@Home, a network of volunteers donating their computing power.
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 calculations
A method for predicting the stability of protein-ligand interactions.
Relative binding free energy calculations are a computational technique used to determine the strength of interactions between proteins and other molecules, such as drugs. This information is crucial in drug discovery as it helps identify potential drug candidates that bind effectively to their target proteins.
alchemiscale.org
A web platform for performing alchemical calculations.
Alchemiscale.org is a website that provides tools and resources for scientists to perform alchemical free energy calculations. These calculations are used to predict the binding affinity between molecules, which is essential for drug discovery and development.
Networks of alchemical transformations
A collection of chemical reactions that can be used to modify the properties of molecules.
Networks of alchemical transformations refer to sets of interconnected chemical reactions that can be used to alter the structure and properties of molecules. This concept is applied in computational biology and drug discovery to simulate and predict molecular interactions.
PROJECTs
Platform for distributed computing tasks.
PROJECTs is a platform that utilizes a network of computers to perform computationally intensive tasks. This approach, often employed in scientific research, allows for the efficient processing of large datasets and complex simulations.
Folding@Home
A distributed computing project that uses volunteered computer processing power to simulate protein folding.
Folding@Home is a global initiative that harnesses the power of volunteer computers to simulate the complex process of protein folding. This research contributes to understanding how proteins fold into their specific shapes, which is crucial for various biological functions and drug development.
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 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 2,886,031 | 10,509 | 274.62 | 0 hrs 5 mins |
| 2 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 1,696,220 | 18,755 | 90.44 | 0 hrs 16 mins |
| 3 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 1,056,756 | 2,625 | 402.57 | 0 hrs 4 mins |
| 4 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 956,366 | 2,625 | 364.33 | 0 hrs 4 mins |
| 5 | GeForce MX250 GP108M [GeForce MX250] |
Nvidia | GP108M | 918,470 | 19,379 | 47.40 | 0 hrs 30 mins |
| 6 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 754,675 | 18,865 | 40.00 | 0 hrs 36 mins |
| 7 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 666,569 | 2,625 | 253.93 | 0 hrs 6 mins |
| 8 | Ryzen 7000 Series iGPU Raphael [Ryzen 7000 Series iGPU] |
AMD | Raphael | 426,184 | 15,420 | 27.64 | 0 hrs 52 mins |
| 9 | RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590] |
AMD | Ellesmere XT | 410,669 | 14,143 | 29.04 | 0 hrs 50 mins |
| 10 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 368,386 | 2,625 | 140.34 | 0 hrs 10 mins |
| 11 | Radeon R9 285/380 Tonga PRO [Radeon R9 285/380] |
AMD | Tonga PRO | 332,299 | 14,742 | 22.54 | 1 hrs 4 mins |
| 12 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 274,577 | 2,625 | 104.60 | 0 hrs 14 mins |
| 13 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 255,867 | 2,625 | 97.47 | 0 hrs 15 mins |
| 14 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 162,234 | 4,406 | 36.82 | 0 hrs 39 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 |
|---|