Exploring computational tools in drug design using techniques from chemoinformatics, molecular modelling and computational chemistry; this book is a practical introduction for researchers new to the fields. It is ideal for aimed academics, postgraduates and industry practitioners in medicinal chemistry, chemoinformatics, molecular modelling, computational chemistry, and in silico medicinal chemistry.
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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. The fourth part of the book covers topics such as similarity searching, clustering and diversity selection, virtual library design, ligand docking and de novo design in the drug discovery setting. 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.
Nathan Brown leads the In Silico Medicinal Chemistry group at The Institute of Cancer Research, London, supporting academic drug design by application of chemoinformatics, computational chemistry and molecular modelling, and developing new methodologies.
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Hardcover. Condition: new. Hardcover. 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. Exploring the methodologies and applications ofcomputational tools in drug design, this book is a practical introduction to chemoinformatics, molecular modelling and computational chemistry for researchers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781782621638
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