Scaffold Hopping in Medicinal Chemistry

This first systematic treatment of the concept and practice of scaffold hopping shows the tricks of the trade and provides invaluable guidance for the reader′s own projects. The first section serves as an introduction to the topic by describing the concept of scaffolds, their discovery, diversity and representation, and their importance for finding new chemical entities. The following part describes the most common tools and methods for scaffold hopping, whether topological, shape–based or structure–based. Methods such as CATS, Feature Trees, Feature Point Pharmacophores (FEPOPS), and SkelGen are discussed among many others. The final part contains three fully documented real–world examples of successful drug development projects by scaffold hopping that illustrate the benefits of the approach for medicinal chemistry. While most of the case studies are taken from medicinal chemistry, chemical and structural biologists will also benefit greatly from the insights presented here.

PART I: SCAFFOLDS: IDENTIFICATION, REPRESENTATION DIVERSITY AND NAVIGATION Identifying and Representing Scaffolds Markush Structures and Chemical Patents Scaffold Diversity in Medicinal Chemistry Space Scaffold Mining of Publicly Available Compound Data Exploring Virtual Scaffold Spaces PART II: SCAFFOLD HOPPING METHODS Similarity–Based Scaffold Hopping Using 2D Fingerprints CATS for Scaffold–Hopping in Medicinal Chemistry Reduced Graphs Feature Trees Feature Point Pharmacophores (FEPOPS) Three–Dimensional Scaffold Replacement Methods Spherical Harmonic Molecular Surfaces (ParaSurf and ParaFit) The XED Forcefield and Spark Molecular Interaction Fingerprints SkelGen PART III: CASE STUDIES Case Study 1: Scaffold Hopping for T–Type Calcium Channel and Glycine Transporter Type 1 Inhibitors Case Study 2: Bioisosteric Replacements for the Neurokinin 1 Receptor (NK1R) Case Study 3: Fragment Hopping to Design Highly Potent and Selective Neuronal Nitric Oxide Synthase Inhibitors

Nathan Brown is the Head of the In Silico Medicinal Chemistry group in the Cancer Therapeutics Unit at The Institute of Cancer Research in London (UK). At the ICR, Dr. Brown and his group support the entire drug discovery portfolio together with developing new computational methodologies to enhance the drug design work. Nathan Brown conducted his doctoral research in Sheffield with Professor Peter Willett focusing on evolutionary algorithms and graph theory. After a two–year Marie Curie Fellowship in Amsterdam in collaboration with Professor Johann Gasteiger in Erlangen, he joined the Novartis Institutes for BioMedical Research in Basel for a three–year Presidential Fellowship in Basel working with Professors Peter Willett and Karl–Heinz Altmann. His work has led to the pioneering work on multiobjective de novo design in addition to a variety of discoveries and method development in scaffold hopping, bioisosteric identifi cation and replacement, molecular descriptors and statistical modeling. Nathan continues to pursue his research in all aspects of in silico medicinal chemistry.