Innovative and forward-looking, this volume focuses on recent achievements in this rapidly progressing field and looks at future potential for development. The first part provides a basic understanding of the factors governing protein-ligand interactions, followed by a comparison of key experimental methods (calorimetry, surface plasmon resonance, NMR) used in generating interaction data. The second half of the book is devoted to insilico methods of modeling and predicting molecular recognition and binding, ranging from first principles-based to approximate ones. Here, as elsewhere in the book, emphasis is placed on novel approaches and recent improvements to established methods. The final part looks at unresolved challenges, and the strategies to address them. With the content relevant for all drug classes and therapeutic fields, this is an inspiring and often-consulted guide to the complexity of protein-ligand interaction modeling and analysis for both novices and experts.
About the Author
Holger Gohlke is Professor of Pharmaceutical and Medicinal Chemistry at the Heinrich-Heine-University, Dusseldorf, Germany. He obtained his diploma in chemistry from the Technical University of Darmstadt and his PhD from Philipps-University, Marburg, working with Gerhard Klebe, where he developed the DrugScore and AFMoC approaches. He then did postdoctoral research at The Scripps Research Institute, La Jolla, USA, working with David Case on developing and evaluating computational biophysical methods to predict protein-protein interactions. After appointments as Assistant Professor at Goethe University Frankfurt and Professor at Christian-Albrechts-University, Kiel, he moved to Dusseldorf in 2009. He was awarded the 'Innovationspreis in Medizinischer und Pharmazeutischer Chemie' from the Gesellschaft Deutscher Chemiker and the Deutsche Pharmazeutische Gesellschaft, and the Hansch Award of the Cheminformatics and QSAR Society. His current research focuses on the understanding, prediction, and modulation of interactions involving biological macromolecules from a theoretical perspective. His group applies and develops techniques grounded in bioinformatics, computational biology, and computational biophysics.
