Molecular modeling ADME prediction

This perspective has examined the approaches to molecular modeling and drug design and emphasized their limitations. The reader should be aware, however, that these tools are daily used on many problems of therapeutic interest with increasing success. This is clearly witnessed by publications of such studies in almost every issue of current major journals. For specific application areas, such as RNA (490, 491), DNA (492-496), membrane (497-507), or peptidomimetic modeling (382, 508-513), the reader is referred to the literature. The prediction of molecular properties, such as log P and correlation between substructures and metabolism, has led to a dramatic increase in efforts to correlate adsorption, distribution (514), metabolism (515-617), and elimination (ADME) with chemical... 

Ceiius Molecular modeling package providing computer models for predicting ADME and toxic properties of compounds http //accelrys.com/products/ceiius2/... 

Elizabeth Barrett Browning after hearing a discussion of toxicity prediction, How can I kill thee, let me count the ways . A recent article by Stouch et al. [74] presents a thoughtful analysis of the validation effort for four such ADME/Tox models. Oprea et al. [75, 76[ have compared drugs leads with compounds in development and in the marketplace and shown that compounds increase in molecular weight and logP as they progress to the bedside. In silico approaches certainly have their place in the pharmaceutical industry as one more tool to increase the probability of success [77]. 

Hou, T.J., Wang, J.M., Zhang, W., Xu, X.J. ADME evaluation in drug discovery. 6. Can oral bioavailability in humans be effectively predicted by simple molecular property-based rules J. Chem. Inf. Model. 2007, 47, 460-3. 

Whereas hard filters can be considered to be knowledge-driven, soft filters are the result of a data-driven approach. A quantitative structure-activity or structure-property relationship (QSAR/QSPR) is established to predict a property from a set of molecular descriptors. Examples are the above-mentioned in-silico prediction tools for frequent hitters [27] and drug-likeness [41,42] additional models for ADM E properties are described below. 

VolSurfwas initially validated on oral absorption [16, 17] and blood-brain-barrier permeation [18] models (see belovi ). VolSurf has continued to be developed to improve in silico predictions for ADME properties, although its use has also been extended to receptor-based evaluation of binding affinity [19, 20], While other soft-ivare tools for ADME modeling are available (see, e.g., [21]), the MIF-based collection of sofhvare and models available from Molecular Discovery (MD) is both extensive and ivell validated by the private sector. Three programs from MD, VolSurf, MetaSite and Almond, are particularly suited for rapid evaluation of large compound sets [22] in connection ivith ADME/Tox related properties ... 

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