In Silico Lead Discovery

Chemical Libraries for Virtual Screening

Author(s): David Lagorce, Olivier Sperandio, Maria A. Miteva and Bruno O. Villoutreix

Pp: 1-19 (19)

Doi: 10.2174/978160805142711101010001


The number of new drug approvals per year has been decreasing over the past decade for numerous reasons including an increase in regulatory requirements and lack of sufficient knowledge on the pathophysiological processes being targeted. Also, many compounds fail in development because they lack efficacy and safety. One strategy, among many, to circumvent this high attrition rate is through improving the quality of the compound collections as libraries have usually grown in size with little or inadequate attention about the quality. There are many different ways to prepare a compound collection, the process can involve increasing diversity but it can also imply the creation of focused collection dedicated to a specific disease-type and/or target. In parallel, ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) properties have to be considered and the parameters assessed tuned according to the project, stage of the project and disease type. In this chapter, in silico methods facilitating the creation of a generic target-independent compound collections are explored and several in silico ADMET prediction tools are discussed. Key concepts are described to build a compound collection appropriate for hit finding. Overall, this procedure involves several steps: database cleaning, compound filtering step using drug-likeness or lead-likeness criteria, removal of undesirables chemical structures, and structural and chemical quality control. Because for in silico screening studies the collection has to be in 3D, a paragraph exposes some recently developed methods for 3D structure generations, and a list of commercial and free standalone packages as well as online tools is provided.

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