Research section Research projects and references

Research: LOGP-PREDICTION-SIMULATIONS Folding Project #12470

Project #12470 overview

Project Summary AI Beta

This project is testing a new computer simulation method to predict how well drugs dissolve in the body. They're checking if different simulation settings affect the results.
Automated summary; simplified and may not be fully accurate.

Project team

Manager(s)
Prof. Vincent Voelz
Institution
Temple University

Work unit

Atoms
16,500
Core
0xa8
Status
Public
Source material

Official Project Description

A key challenge in computational drug discovery is developing and testing methods to predict experimental partition coefficients for the relative solubility of organic molecules in aqueous vs.

non-polar media.

The logarithm of the partition coeffient, logP, is an important predictor of lipophilicity, which dictates the bioavailability of drugs.

This CPU project is testing expanded-ensemble (EE) simulations as a method for the calculation of logP and seeing if forcefield selection effects these calculations..

Performance data

Hardware Performance for Project 12470

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

Data as of Sunday, 02 August 2026 22:08:57

CPU PPD Averages Beta

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 7 5800X3D 8-CORE 16 30,916 494,656 AMD
2 RYZEN 7 5700X 8-CORE 16 28,282 452,512 AMD
3 RYZEN 7 5700X3D 8-CORE 16 26,059 416,944 AMD
4 RYZEN 9 5950X 16-CORE 32 10,747 343,904 AMD
5 RYZEN 7 3700X 8-CORE 16 15,190 243,040 AMD
6 13TH GEN CORE I7-13700 24 10,076 241,824 Intel
7 11TH GEN CORE I7-11700F @ 2.50GHZ 16 6,033 96,528 Intel