Abstract

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds’ databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.

Highlights

  • The Emergence of Virtual ScreeningVirtual screening (VS) has become a popular technique [1] since it was expected to reduce the synthesis and biological screening cost and shorten the life cycles of the discovery phases

  • 2D similarity search did not lead to novel chemotypes, pharmacophore model generation allowed us to identify two novel chemotypes with sub micromolar activities

  • The first round library generation relied on 2D similarity search applying a diverse set of known PDE5 inhibitors (27), and a 5 M commercial library was used as the targeted chemical space (Figure 10) [69]

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Summary

Introduction

Virtual screening (VS) has become a popular technique [1] since it was expected to reduce the synthesis and biological screening cost and shorten the life cycles of the discovery phases. Over the past two decades, huge compound repositories were built exploiting historical collections as well as compound libraries. The chemoinformatics methods have developed rapidly and the computational power increased, allowing fast or real time calculations. Deeper knowledge has been developed about the small molecule–protein interactions using state-of-the-art X-ray crystallography, docking, and conditions of the Creative Commons. The above approaches vary in computational requirements and hit diversity/novelty [5].

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