Drug computational prediction

Blood-brain barrier permeation of 7, among other drugs, was predicted from its three-dimensional molecular structure by a computational method (0OJMC2204). The combination of molecular topological methods using 137 quinolones, including 7 provided an excellent tool for the design of new... 

Ekins S, Andreyev S, Ryabov A, Kirilov E, Rakhmatulin EA, Bugrim A, et al. Computational prediction of human drug metabolism. Exp Opin Drug Metab Toxicol 2005 1 303-24. 

In the context of drug discovery, computational methods do not add value unless they can achieve practical results. Results must be produced quickly enough so that they can influence decision making in chemical synthesis. Most importantly, computational methods must be accurate enough to maintain the trust of the medicinal chemist. Without this trust, computational predictions will rarely be tested in the laboratory, which will then prevent the generation of critical data useful for improving the original predictions. 

The challenge for the drug discovery organization is how to handle the resource issues for multiple screening data feedback. Often a combination of experimental screens and computational prediction approaches will be used. Rapid data feedback to the medicinal chemist is essential, whether the data is experimental or computational. Data delayed is data with greatly reduced value. 

Aqueous solubility is probably the single most important biopharmaceutical property that pharmaceutical scientists are concerned with. It has been the subject of computational prediction for several years.20 23 The overall accuracy of the predicted values can be expected to be in the vicinity of 0.5 to 1.0 log units (a factor of 3 to 10) at best. Although a decision on acceptance or rejection of a particular compound cannot be made only on the basis of predicted parameters, these predictions may be helpful to direct chemical libraries with improved drug-like properties.24... 

Computational Prediction of Drug-Likeness 29 Table 2.1 Machine learning algorithms used for the prediction of ADME properties. 

Hou, T., Wang, J Zhang, W Wang, W. and Xu, X. (2006) Recent advances in computational prediction of drug absorption and permeability in drug discovery. Current Medicinal Chemistry, 13, 2653-2667. 

Snyder, R.D. and Smith, M.D. (2005) Computational prediction of genotoxicity room for improvement. Drug Discov. Today, 10 (16), 1119-1124. 

Actisomide was included in a set of drugs for computational predictions of human drug clearance using different allometry methods (08MI1, 09JPS2472) and for computational predictions of volume of distribution using linear and nonlinear models (09JMC4488). 

Rao S, Aoyama R, Schrag M et al. (2000) A refined 3-dimensional QSAR of cytochrome P450 2C9 Computational predictions of drug interactions. J Med Chem 43 2789-2796... 

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