LogP

Overview

This module calculates the value of the octanol-water partition coefficient – LogP. Reliability of predictions is quantitatively estimated via the calculation of the Reliability Index value.

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Features

• Calculate the octanol-water partition coefficient for a wide range of neutral compounds under standard conditions, at 25°C
• Calculations are provided with 95% confidence intervals, or reliability Index (RI)
• Review bioconcentration factor (BCF) and the adsorption coefficient (Koc)
• Evaluate Rule-of-5 compliance
• Train the model with experimental values to improve predictions for proprietary chemical space

Interface

ACD/LogP Classic

File:acdlogp classic.png

1. LogP prediction obtained using ACD/LogP Classic calculation algorithm.
2. LogP calculation protocol. Lists the increments of all functional groups and carbon atoms, as well as the contirbutions of interaction through aliphatic, aromatic and vinylic systems.
3. The protocol is interactive. Click on any entry to highlight the respective atom, group, or interaction onto the molecule.
4. If the compound is found in LogP DB, all available experimental data for that compound are displayed along with literature references.

ACD/LogP GALAS

File:acdlogp galas.png

1. Lipophilic parts of the molecule are highlighted in green, hydrophilic groups in red, and the intensity of the color indicates the predicted degree of lipophilicity or hydrophilicity of an atom or a substructure.
2. LogP prediction obtained using GALAS modeling methodology.
3. Reliability index (RI):
   RI < 0.3 – Not Reliable,
   RI in range 0.3-0.5 – Borderline Reliability,
   RI in range 0.5-0.75 – Moderate Reliability,
   RI >= 0.75 – High Reliability
4. Up to 5 most similar drug-like structures with experimental parameters

Consensus LogP

File:logp consensus.png

1. ...
2. Up to 5 most similar drug-like structures with experimental parameters

Technical information

LogP module provides the estimate of the value of the octanol-water partitioning coefficient for neutral species. Reliability of each prediction is quantitatively estimated via the calculation of the Reliability Index value. In addition a color-coded representation of the predicted property distribution is provided indicating lipophilic and hydrophilic parts of the compound structure.

Training set size: 11,387
Internal validation set size: 4,890
Main sources of experimental data:

• Reference books:
  • The Merck Index. An Encyclopedia of Chemicals, Drugs, and Biologicals, O'Neil, M.J., Smith, A., Heckelman, P.E., Budavari, S., Eds. 13th Edition, Merck & Co., Inc., Whitehouse Station, NJ, 2001
  • Therapeutic Drugs, Dolery, C., Ed. 2nd Edition, Churchill Livingstone, New York, NY, 1999
  • Clarke's Isolation and Identification of Drugs, Moffat, A.C., Jackson, J.V., Moss, M.S., Widdop, B., Eds. 2nd Edition, The Pharmaceutical Press, London, 1986
• Various articles from peer-reviewed scientific journals*
• Other public data sources (online databases, handbooks, etc.)

* - Articles reporting LogP models by other authors were the predominant type among analyzed literature, meaning that each publication contained larger collections of experimental data (usually in the order of tens or hundreds compounds) compiled from corresponding original experimental articles.

Internal Validation

Table 1. ACD/LogP (AB/LogP v2.0) model performance statistics for the various fractions of the internal validation set.

Subset	Coverage of the entire internal validation set (N=4,890)	R2	RMSE
RI > 0.3 N = 4,872	99.6%	0.94	0.46
RI > 0.5 N = 4,772	97.6%	0.95	0.44
RI > 0.75 N = 3,345	68.7%	0.96	0.36