In Silico Tools and In Vitro HTS Approaches to Determine Lipophilicity During the Drug Discovery Process

Abstract

Advances in rational drug design and combinatorial chemistry increased drastically the number of newly promising active compounds. As inappropriate pharmacokinetics (PK) was recognized as one of the major factors leading to the withdrawal of new chemical entities (NCEs) from drug development [1,2], efficient in silico and in vitro models were developed to replace in vivo studies for absorption, distribution, metabolism, excretion (ADME) and toxicity (T) in the early phases of drug research [3]. The large number of approaches offering suitable estimates of ADMET properties in the early stages of drug discovery has been extensively reviewed [4][5][6][7][8][9][10][11]. These approaches used largely (Q)SAR models based on physicochemical parameters such as solubility, ionization and lipophilicity. Thus these fundamental physicochemical properties have to be estimated early in drug discovery programs to filter out unsuitable compounds and to rank validated hits in order to select the most promising compounds according to their pharmacodynamic and pharmacokinetic profiles. As the paradigms of hit-like [12,13], lead-like [13][14][15][16] or drug-like properties [17][18][19][20][21][22][23][24] are governing the research, considerable efforts are still carried out to develop efficient virtual and experimental filters to reduce large chemical databases to smaller collections of compounds with suitable PK properties for an in vivo high therapeutic potency [25].Among the physicochemical properties involved in ADMET profiling, lipophilicity has a place of choice as the major contributor to solubility, membrane permeation and protein binding [26,27], metabolism and the ability to reach and to bind the targeted receptors [28]. This predominant position is well illustrated by numerous papers devoted to this topic (for recent reviews, see [6,11,29,30]). To overcome the limitations of the time-consuming traditional methods such as the shake-flask, potentiometry (for ionizable compounds) and cyclic voltammetry (for ions only), a number of in silico and experimental high-throughput techniques Hit and Lead Profiling. Edited by Bernard Faller and Laszlo Urban j91 emerged. The scope of this chapter is to review these HTS methods for log P and log D determination in the 1-octanol/water system and in other solvent/water systems useful in the early stages of drug discovery. 5.2Virtual Filtering: In Silico Prediction of log P and log D Among the large number of existing lipophilicity parameters [31], the descriptor frequently estimated by in silico methods is the partition coefficient of a solute between 1-octanol and water, expressed as log P oct [32]. However, lipophilicity determination in different solvent systems, such as alkane/water system, proved its utility in (Q)SAR studies and therefore some predictive methods also emerged in this field. Many publically available databases include numerous experimental values collected through the literature; the quality of the experimental data represents the cornerstone of most of the models ...

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“…Physicochemical Assays log P, pK a , and Aqueous Solubility Measurements. The pK a and octanol-water partition coefficient were measured by potentiometric methods 62 with a Sirius GLpKa instrument. Aqueous solubility was determined with the DMSO-buffer dilution turbidimetric method 63 according to a reported procedure.…”

High‐throughput log P determination by MEEKC coupled with UV and MS detections

“…However, they are associated with well-described limitations such as problems with complex molecular fragments [5][6][7] or poor descriptions of intramolecular effects associated with the 3-D molecular structure [4,8]. Therefore, it remains necessary to determine these values experimentally [9,10].…”