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 Skel Gen 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.
Tabela de Conteúdo
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 (Para Surf and Para Fit)
The XED Forcefield and Spark
Molecular Interaction Fingerprints
Skel Gen
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
Sobre o autor
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 Bio Medical 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.
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