The Impact of Lipophilicity in Drug Discovery: Rapid Measurements by Means of Reversed-Phase HPLC

Abstract

Lipophilicity constitutes a vital physicochemical property in drug design as it is connected with pharmacodynamic and pharmacokinetic properties as well as toxicological aspects of candidate drugs. Traditional partitioning experiments to determine n-octanol-water coefficients are laborious and time-consuming, while they cannot be reliably performed for highly lipophilic or compounds undergoing degradation. Alternatively, lipophilicity of candidate drugs can be accurately and reproducibly determined using reversed-phase liquid chromatography. In this chapter, the details of protocols for lipophilicity assessment using reversed-phase HPLC, under conditions which provide the best simulation of n-octanol-water partition coefficients, are described.

Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds

“…Interestingly, when comparing these values with the variation of ⟨ D 2 ( c j )⟩, tests on virus lines, such as Moloney murine sarcoma virus and Woolly monkey sarcoma virus, had higher means (between 140 and 205). Since the ALOGP coefficient is a measure widely used in drug discovery to assess the degree of absorption, distribution in the body, penetration across biological membranes, metabolism, and excretion, this range identified in our results is an important space for the prediction of antisarcoma drugs. , Likewise, the range of PSA evidenced in viral line assays may be a better space for this coefficient if it is desired to predict new compounds in these experimental conditions. This may be interesting when defining the validation of a certain antisarcoma compound.…”

Is there enough focus on lipophilicity in drug discovery?

“…In practice, the calculated log P (clog P) is often used instead of the measured log P as an assessment of lipophilicity, with measured partition coefficients obtained on key compounds through a project's progression. Since clog P values used for screening virtual libraries are often inaccurate, this can lead to imprecise results that cause promising compounds to be abandoned and/or flawed compounds to move forward [3,4]. Comparisons made between marketed oral drugs and compounds in earlier stages of development indicate that log P values beyond Lipinksi's rule-of-five criteria (>5) are associated with undesired drug features, such as rapid metabolic turnover, poor aqueous solubility, high plasma protein binding, and tissue accumulation.…”

“…Additionally, log P should be experimentally evaluated for a representative set of compounds in order to predict log P for a given chemical series. This can be accomplished using chromatographic techniques such as reversed-phase high performance liquid chromatography [3,4]. The use of confidence in log P prediction would allow higher resolution and discrimination with regard to selection of reliable and non-reliable predictions, thus increasing design efficiency.…”

Lipophilicity Determination of Antifungal Isoxazolo[3,4-b]pyridin-3(1H)-ones and Their N1-Substituted Derivatives with Chromatographic and Computational Methods

“…It determines not only the transport of molecules through biological membranes but also their ability to undergo complexation with blood proteins and binding to receptors [1]. Knowledge of lipophilicity helps us understanding pharmacokinetic properties, including absorption, distribution, metabolism, and excretion (ADME) processes, as well as toxicity [2,3].…”

“…Minimum, maximum, and mean value of log P -s calculated by different software, Table S3: Retention data for the investigated pyrido- and quinolino-isoxazolones obtained from the Soczewiński–Wachtmeister method with statistical parameters; Table S4. Antifungal activity toward references Candida species [1,2,3]; Table S5. Cross-validation—analysis of variance summary for the TLC C 8 QSRR model; Table S6.…”