Screen in-silico

New scientific approaches, e.g. combinatorial chemistry, high-throughput screening, in silico models, pharmaco-genomics and pharmaco-proteomics offered new possibilities. 

Virtual screening (in silico screening, 3D database search) of known compounds... 

Rational designs to save resources Prediction-based screening (in-silico or combination of in-silico and experimental techniques) Molecular Recognition Reduce the number of crystallization solvents, find all predicted polymorphs 5-10 solvents chosen to interact with specific functional groups HBD/HBA propensity Solvent class (H-bonding functionahty)... 

In addition to traditional wet screening, in silico virtual screening has also been used to identify new ligands or ligand fragments [22, 23]. 

The term virtual screening or in silico screening" is defined as the selection of compounds by evaluating their desirability in a computational model. The desirability comprises high potency, selectivity, appropriate pharmacokinetic properties, and favorable toxicology. 

If structural information of the protein target is available, e.g., a crystal structure, in silico screening of huge virtual compound libraries can be conducted by the use of docking simulations. Based on identified primary hits, structural variations of the ligand can be evaluated by computational modeling of the ligand-protein complex. 

Schuffenhauer A, Zimmermann J, Stoop R,van derVyver JJ, Lecchini S, Jacoby E. An ontology for pharmaceutical ligands and its application for in silico screening and library design. J Chem Inf Comput Sci 2002 42 947-55. 

Langer T, Eder M, Hoffmann RD, Chiba P and Ecker GF. Lead identification for modulators of multidrug resistance based on in silico screening with a phar-macophoric feature model. Arch Pharm (Weinheim) 2004 337 317-27. 

The abundance of crystallographic information on the 3D structure of protein kinases, including knowledge of receptor-ligand complexes, has seen protein kinases feature consistently in datasets employed to both develop and evaluate methods for receptor-based screening. Indeed, the vast majority of literature surrounding protein kinases and receptor-based in silico... 

In silico property prediction is needed more than ever to cope with the screening overload. Improved prediction technologies are continuing to emerge [13,14]. However, reliably measured physicochemical properties to use as training sets for new target applications have not kept pace with the in silico methodologies. 

Although the pressure to screen large numbers of compounds quickly has led to the rapid development of in silico and in vitro assays, the sheer number and complexity of the processes involved in determining the disposition of any particular compound means that in vivo studies are still required to provide assurance that the important processes are modeled with sufficient accuracy [4-6], and indeed, that the potential contribution of processes for which there are no good in vitro models (e.g., biliary secretion) are adequately assessed. 

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