Abstract

Since its introduction in 2003, the Shape Signatures method has been successfully applied in a number of drug design projects. Because it uses a ray-tracing approach to directly measure molecular shape and properties (as opposed to relying on chemical structure), it excels at scaffold hopping, and is extraordinarily easy to use. Despite its advantages, a significant drawback of the method has hampered its application to certain classes of problems; namely, when the chemical structures considered are large and contain heterogeneous ring-systems, the method produces descriptors that tend to merely measure the overall size of the molecule, and begin to lose selective power. To remedy this, the approach has been reformulated to automatically decompose compounds into fragments using ring systems as anchors, and to likewise partition the ray-trace in accordance with the fragment assignments. Subsequently, descriptors are generated that are fragment-based, and query and target molecules are compared by mapping query fragments onto target fragments in all ways consistent with the underlying chemical connectivity. This has proven to greatly extend the selective power of the method, while maintaining the ease of use and scaffold-hopping capabilities that characterized the original implementation. In this work, we provide a full conceptual description of the next generation Shape Signatures, and we underline the advantages of the method by discussing its practical applications to ligand-based virtual screening. The new approach can also be applied in receptor-based mode, where protein-binding sites (partitioned into subsites) can be matched against the new fragment-based Shape Signatures descriptors of library compounds.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-013-9698-7) contains supplementary material, which is available to authorized users.

Highlights

  • Molecular shape remains the fundamental determinant in our understanding of the mechanisms of bioactivity [1]

  • We focus on the Androgen Receptor (AR), an important drug target in Prostate Cancer (PCa) therapy [24], and one with which we have significant prior computational experience [25]

  • We tested the ability of fragment-based Shape Signatures to provide virtual screening hits with high potential to identify chemical classes of AR binders

Read more

Summary

Introduction

Molecular shape remains the fundamental determinant in our understanding of the mechanisms of bioactivity [1]. Shape is a preeminent consideration, and given the rapid increase in the size of available chemical libraries, it remains a challenge to efficiently screen large compound databases to identify compounds likely to evince shape similar to a query molecule, or to match the complementary volume of a protein receptor. Another argument that draws increasing attention is the practical issue of securing intellectual property rights for potential therapeutics. Methods that rely on the development of structural queries presume a high level of chemical expertise, and may be difficult for the non-computational specialist to apply

Objectives
Methods
Results
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call