ADMET properties toxicity

Hansch and Leo [13] described the impact of Hpophihdty on pharmacodynamic events in detailed chapters on QSAR studies of proteins and enzymes, of antitumor drugs, of central nervous system agents as well as microbial and pesticide QSAR studies. Furthermore, many reviews document the prime importance of log P as descriptors of absorption, distribution, metabolism, excretion and toxicity (ADMET) properties [5-18]. Increased lipophilicity was shown to correlate with poorer aqueous solubility, increased plasma protein binding, increased storage in tissues, and more rapid metabolism and elimination. Lipophilicity is also a highly important descriptor of blood-brain barrier (BBB) permeability [19, 20]. Last, but not least, lipophilicity plays a dominant role in toxicity prediction [21]. 

Pharmacokinetics and toxicity have been identified as important causes of costly late-stage failures in drug development. Hence, physicochemical as well as ADMET properties need to be fine-tuned even in the lead optimization phase. Recently developed in silica approaches will further increase model predictivity in this area to improve compound design and to focus on the most promising compounds only. A recent overview on ADME in silica models is given in Ref [128]. 

Other HTS assay advances include the us-e of microorganisms such as bacteria and yeast, the cloning and expression of mammalian receptors in microorganisms, probing protein-protein inlcraclions. and veiy importantly. DNA and protein arrays. These are loo involved to discuss here, but excellent reviews exi.sl.- - The increasing use of HTS to screen fora molecule s absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties has been covered as well. ... 

This chapter describes some of the approaches and techniques used currently to derive in silico models for the prediction of absorption, distribution, metabolism, elimination/excretion, and toxicity (ADMET) properties. The chapter also discusses some of the fundamental requirements for deriving statistically sound and predictive ADMET relationships as well as some of the pitfalls and problems encountered during these investigations. It is the intention of the authors to make the reader aware of some of the challenges involved in deriving useful in silico ADMET models for drug development. 

Prediction of absorption, distribution, metabolism and excretion/toxicity (ADMET) properties. To deveiop its pharmacoiogical activity, a drug candidate has to penetrate various physioiogical barriers, move to its effector site, be modified by specialised enzymes and finally be removed from the body. In other words, it requires some particular properties of absorption, distribution, metabolism and excretion without being toxic. ADMET properties have been identified... 

The most appropriate and widely used method for extracting information from large data sets is QSAR and its relatives, quantitative structure-property relationships (QSPR) for property modeling, and quantitative structure-toxicity relationships (QSTR) for toxicity modeling. QSAR is a simple, well validated, computationally efficient method of modeling first developed by Hansch and Fujita several decades ago (30). QSAR has proven to be very effective for discovery and optimization of drug leads as well as prediction of physical properties, toxicity, and several other important parameters. QSAR is capable of accounting for some transport and metabolic (ADMET) processes and is suitable for analysis of in vivo data. 

The attraction of lipophilicity in medicinal chemistry is mainly due to Corwin Hansch s work and thus it is traditionally related to pharmacodynamic processes. However, following the evolution of the drug discovery process, lipophilicity is today one of the most relevant properties also in absorption, distribuhon, metabolism, excretion and toxicity (ADMET) prediction, and thus in drug profiling (details are given in Chapter 2). 

Instead, due to the multi-objective nature of drug discovery, other factors, such as absorption, distribution, metabolism, excretion, toxicity (ADMET), selectivity and cost, molecular screening libraries need to be carefully planned and a number of design objectives must be taken into account (8). In recent times, MLD efforts have been exploring the use of multi-objective optimization (MOOP) techniques capable of designing libraries based on a number of properties simultaneously (9). 

Early determination of PK properties (absorption, distribution, metabolism, excretion and toxicity, ADMET) has become a fundamental resource of medicinal chemistry in the LO phase. New technologies have been developed to perform a great number of in vitro and even in silico tests. Currently, the most common early-ADME assays evaluate both physicochemical properties (such as the solubility in an opportune medium, the lipophilicity, and the p K i) and biophysical properties (such as the permeability through cellular monolayers to predict oral absorption and the metabolic stability after treatment with liver or microsomal subcellular fraction that contains oxidative cytochromes). 

Drug Discovery Today 7 25-27 Li AP (2004) In vitro approaches to evaluate ADMET drug properties. Curr Top Med Chem 4 701-706 Li W, Escarpe PA, Eisenberg EJ et al. (1998) Identification of GS 4104 as an orally bioavailable prodrug of the influenza virus neuraminidase inhibitor GS 4071. Antimicrobial Agents and Chemotherapy 42 647-653 Los LE, Welsh DA, Herold EG et al. (1996) Gender differences in toxicokinetics, liver metabolism, and plasma esterase activity observations from a chronic (27-week) toxicity study of enalapril/diltiazem combinations in rats. Drug Metab Dispos 24 28-33... 

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