RESEARCH: DRUG-SOLUBILITY-PREDICTION
FOLDING PROJECT #18497 PROFILE

PROJECT TEAM

Manager(s): Prof. Vincent Voelz
Institution: Temple University

WORK UNIT INFO

Atoms: 18,193
Core: 0xa8
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project tests using computer simulations to predict how well drugs dissolve in water versus oil. The project looks at different simulation methods and how they affect the results.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL 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..

RELATED TERMS GLOSSARY AI BETA

Note: Glossary items are a high level summary and may not be 100% accurate.

partition coefficient

A measure of a substance's solubility in two immiscible solvents.

Technical: Biotechnology
Drug Discovery / Pharmacology

The partition coefficient describes how readily a molecule dissolves in water compared to oil. It's a crucial factor in determining drug effectiveness as it influences how well a medication can pass through cell membranes and reach its target.


logP

Logarithm of the octanol-water partition coefficient

Acronym: Biotechnology
Drug Discovery / Pharmacology

logP is a simplified way to represent the partition coefficient. It's a numerical value that indicates how much more soluble a drug is in fat (octanol) compared to water. Higher logP values suggest better solubility in fats, which can influence how easily a drug crosses cell membranes.


lipophilicity

The tendency of a molecule to dissolve in fats and oils.

Technical: Biotechnology
Drug Discovery / Pharmacology

Lipophilicity is a key property that affects how well drugs can move through the body. Drugs with high lipophilicity are more likely to dissolve in cell membranes, allowing them to enter cells and exert their effects.


bioavailability

The fraction of a drug that reaches the systemic circulation.

Technical: Biotechnology
Drug Discovery / Pharmacology

Bioavailability refers to how much of a drug actually enters the bloodstream and becomes available to act on its target. Several factors can influence bioavailability, including lipophilicity, metabolism, and absorption.


forcefield

A set of mathematical equations that describe the interactions between atoms in a molecule.

Technical: Biotechnology
Drug Discovery / Computational Chemistry

Forcefields are essential for computer simulations of molecules. They allow scientists to predict how molecules will behave and interact with each other. Different forcefields have varying levels of accuracy and are suited for different types of calculations.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:27:59
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 03:27:59
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 7 9700X 8-CORE 16 86,902 1,390,432 AMD
2 CORE ULTRA 7 265K 20 68,325 1,366,500 Intel
3 RYZEN 9 9950X 16-CORE 32 34,929 1,117,728 AMD
4 RYZEN 7 7700X 8-CORE 16 58,420 934,720 AMD
5 RYZEN 5 5500 12 68,358 820,296 AMD
6 RYZEN 9 7950X3D 16-CORE 32 23,450 750,400 AMD
7 RYZEN 9 7900X 12-CORE 24 30,227 725,448 AMD
8 RYZEN 7 7800X3D 8-CORE 16 39,074 625,184 AMD
9 RYZEN 9 5950X 16-CORE 32 18,860 603,520 AMD
10 RYZEN 9 7900 12-CORE 24 24,283 582,792 AMD
11 RYZEN 7 5800X3D 8-CORE 16 36,033 576,528 AMD
12 RYZEN 7 5800X 8-CORE 16 32,283 516,528 AMD
13 RYZEN 7 7700 8-CORE 16 32,088 513,408 AMD
14 12TH GEN CORE I7-12700F 20 24,259 485,180 Intel
15 RYZEN THREADRIPPER 3960X 24-CORE 48 9,733 467,184 AMD
16 RYZEN 7 5700X3D 8-CORE 16 28,870 461,920 AMD
17 RYZEN 7 5700X 8-CORE 16 25,726 411,616 AMD
18 13TH GEN CORE I5-13600K 14 26,252 367,528 Intel
19 RYZEN 9 3900X 12-CORE 24 15,100 362,400 AMD
20 12TH GEN CORE I9-12900K 24 13,469 323,256 Intel
21 RYZEN 9 3950X 16-CORE 32 9,133 292,256 AMD
22 RYZEN THREADRIPPER 2950X 16-CORE 32 8,802 281,664 AMD
23 RYZEN 5 5600G 12 23,189 278,268 AMD
24 RYZEN 5 5600 6-CORE 12 23,078 276,936 AMD
25 CORE I9-14900KS 16 15,290 244,640 Intel
26 XEON CPU E5-2683 V4 @ 2.10GHZ 32 7,410 237,120 Intel
27 XEON CPU X5660 @ 2.80GHZ 24 9,850 236,400 Intel
28 CORE I7-10700K CPU @ 3.80GHZ 16 14,561 232,976 Intel
29 RYZEN 5 5600X 6-CORE 12 18,839 226,068 AMD
30 RYZEN 7 3700X 8-CORE 16 13,740 219,840 AMD
31 11TH GEN CORE I7-11800H @ 2.30GHZ 16 12,588 201,408 Intel
32 RYZEN 9 3900XT 12-CORE 24 7,254 174,096 AMD
33 CORE I5-10400 CPU @ 2.90GHZ 12 14,226 170,712 Intel
34 RYZEN 7 5800H 16 10,613 169,808 AMD
35 CORE I7-5820K CPU @ 3.30GHZ 12 11,761 141,132 Intel
36 APPLE M1 8 15,586 124,688 Apple
37 11TH GEN CORE I7-11700F @ 2.50GHZ 16 7,165 114,640 Intel
38 RYZEN 5 5500U 12 8,396 100,752 AMD
39 RYZEN 5 3400G 8 7,879 63,032 AMD
40 12TH GEN CORE I5-12600KF 16 1,747 27,952 Intel
41 RYZEN 9 7950X 16-CORE 32 AMD
42 RYZEN 5 7600 6-CORE 12 AMD
43 XEON CPU E5-2680 V2 @ 2.80GHZ 40 Intel
44 RYZEN 9 5900X 12-CORE 24 AMD
45 XEON W-2145 CPU @ 3.70GHZ 16 Intel
46 13TH GEN CORE I7-13700 24 Intel
47 13TH GEN CORE I9-13900KF 32 Intel
48 RYZEN THREADRIPPER PRO 7955WX 16-CORES 32 AMD