The computer-aided drug design is an important tool in modern medicinal chemistry. Molecular lipophilicity, usually quantified as log P, is an important molecular characteristic in medicinal chemistry and also in rationalized drug design. The log P coefficient is well-known as one of the principal parameters for the estimation of lipophilicity of chemical compounds and determines their pharmacokinetic properties. This parameter has been measured using known experimental methods, but recently huge progress in determination of log P using computational chemistry methods is observed. The number of methodological publications about lipophilicity predictions has gradually increased over the last ten years, but the number of programs available for an on-line prediction of this important parameter remains limited. This paper presents some of log P prediction methods and very popular programs connected to this topic. The prediction of log P is highly important for the pharmaceutical industry since it limits time-consuming experiments to measure log P required to optimize pharmacodynamic and pharmacokinetic properties of hits and leads. Development of the methods reviewed in this paper concerning log P prediction seems to be a significant tendency in the modern pharmaceutical industry.

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