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Research: CANCER Folding Project #12497

Project #12497 overview

Project Summary AI Beta

This project uses computer simulations to figure out how well drugs bind to their targets. Users design the simulations, and powerful computers run them. The goal is to make finding new drugs faster and easier.
Automated summary; simplified and may not be fully accurate.

Project team

Manager(s)
Prof. Vincent Voelz
Institution
Temple University

Work unit

Atoms
10,000
Core
0x27
Status
Public
Source material

Official Project Description

These projects are 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. This work, a collaboration between the Voelz and Shirts lab, seeks to test and apply OpenFreeEnergy methods for drug discovery.

Performance data

Hardware Performance for Project 12497

Compare community-sampled Folding@Home output for the GPUs and CPUs processing this project.

Data as of Sunday, 23 August 2026 03:43:29

GPU PPD Averages

Rank
Project 		Model Name
Folding@Home Identifier 		Make
Brand 		GPU
Model 		PPD
Average 		Points WU
Average 		WUs Day
Average 		WU Time
Average
1 Quadro RTX 4000
TU104GL [Quadro RTX 4000]		 Nvidia TU104GL 6,908,266 6,000 1151.38 0 hrs 1 mins
2 GeForce RTX 2060
TU106 [Geforce RTX 2060]		 Nvidia TU106 5,382,354 6,000 897.06 0 hrs 2 mins
3 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 Super]		 Nvidia TU106 5,375,442 6,000 895.91 0 hrs 2 mins
4 Intel Arc B580 Graphics
Battlemage G21 [Intel Arc B580 Graphics]		 Intel Battlemage G21 5,006,215 6,000 834.37 0 hrs 2 mins
5 Quadro T400 Mobile
TU117GLM [Quadro T400 Mobile]		 Nvidia TU117GLM 1,839,862 6,000 306.64 0 hrs 5 mins