Covering computational tools in drug design using techniques from chemoinformatics, molecular modelling and computational
chemistry, this book explores these methodologies and applications of in silico medicinal chemistry. The first part of the
book covers molecular representation methods in computing in terms of chemical structure, together with guides on common structure
file formats. The second part examines commonly used classes of molecular descriptors. The third part provides a guide to
statistical learning methods using chemical structure data, covering topics such as similarity searching, clustering and diversity
selection, virtual library design, ligand docking and de novo design. The final part of the book summarises the application
of methods to the different stages of drug discovery, from target ID, through hit finding and hit-to-lead, to lead optimisation.
This book is a practical introduction to the subject for researchers new to the fields of chemoinformatics, molecular modelling
and computational chemistry.