We are now offering free access to our logP algorithm for scientists who simply require predictions of this property, without the additional capabilities and information provided by the commercial ACD/LogP version (view a comparison of our freeware and full-featured versions). You can enjoy the high quality results of our versatile fragment-based algorithm and get a feel for the accuracy provided by our models. Our logP prediction capabilities were first introduced in 1995, and are continually fine-tuned and enhanced. Calculated values are based on an experimental data set of over 18,000 reliable logP measurements, and ACD/LogP is used worldwide by chemists in various arms of chemical research, including some of the world's largest pharmaceutical companies (GlaxoSmithKline and Pfizer, to name just a few).
Definition of logP—the octanol-water partition coefficient, P, is a measure of the differential solubility of a neutral substance between these immiscible liquids and thereby, a descriptor of hydrophobicity (or the lipophilicity) of a neutral substance. It is typically used in its logarithmic form, logP.
Applications of this hydrophobicity descriptor are wide and varied. Some examples of the how the property is used include the following:
If you are working with compounds that have ionizable groups, it is essential to have a clear understanding of the limitations of logP. LogP does not account for modifications in the hydrophobicity of ionizable compounds at varying pH. The appropriate descriptor for these compounds is the distribution coefficient, D (also typically used in its logarithmic form, logD). This anomaly is illustrated well with Aspirin:
It is evident from these plots that the value of logP for aspirin is only relevant below pH 3. LogD is therefore the appropriate descriptor in the physiologically relevant pH range of 4–8 for an orally available drug. This reasoning is equally relevant for applications of logP outside the realm of drug discovery, though the pH ranges of interest will vary.
The value extractable from logP Predictions—the logP value of a substance is most relevant for neutral substances and is also useful as a general reference point to help us compare overall hydrophobicity trends of compounds. When working with ionizable compounds, however, the limitations of this descriptor mean that logD (the pH-dependant lipophilicity descriptor) should be used.