Biophysical and Computational Tools in Drug Discovery

1. Auflage 2021
ISBN: 978-3-030-85283-2
Verlag: Springer International Publishing

Buch, Englisch, 402 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 622 g

Reihe: Topics in Medicinal Chemistry

This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals frompharmaceutical industry interested in drug design and discovery.

Zielgruppe

Research

Autoren/Hrsg.

Saxena, Anil Kumar

Fachgebiete

• Naturwissenschaften Chemie Chemie Allgemein Pharmazeutische Chemie, Medizinische Chemie
• Naturwissenschaften Chemie Physikalische Chemie
• Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik
• Naturwissenschaften Biowissenschaften Biowissenschaften

Inhaltsverzeichnis

Kinetic profiling of fragments by TR-FRET.- Role of Structural biology in drug discovery with emphasis on X-ray crystallography.- A computational search for peptide vaccines using novel mathematical descriptors of sequences of emerging pathogens.- Solution NMR methods in Drug Discovery for the series.- Applications of Mass Spectrometry in Herbal Drug Research.- Generative machine learning for drug discovery.- Structure and ligand based virtual screening in drug discovery.- Quantum Chemical and Quantum Dynamics Techniques for Drug Discovery Including Bioinorganic Compounds.

Über Autor(innen)

Dr. Anil K. Saxena, Emeritus Scientist, Ex-Chief Scientist Central Drug Research Institute, Lucknow, India, is actively involved in the fields of Medicinal Chemistry & Computer Aided Drug Design (CADD). With 50+ years of research experience, several publications in journals and books, and 70 patents, he is the recipient of numerous awards, including the Alexander von Humboldt Fellowship, INSA Young Scientist Medal , Themis Chemicals UDCT Diamond Jubilee Distinguished Fellowship, Ranbaxy Research Award in Pharmaceutical Sciences, an Honorary Medal for outstanding contributions to Medicinal Chemistry and International Scientific collaboration Moscow, Russia, 2004, and Prof. P.K. Bose Memorial Award (Indian Chemical Society, 2009). Dr. Saxena is a Fellow of the Royal Society of Chemistry, UK, and is also series editor of “Topics in Medicinal Chemistry” published by Springer. He is the Editorial Board Member of different journals like Medicinal Chemistry Research, SAR and QSAR in Environmental Research, Current Topics in Medicinal Chemistry and online International journal ARKIVOC, and he is also member of several committees including the American Chemical Society.