Reprint

Molecular Modeling in Drug Design

Edited by
March 2019
220 pages
  • ISBN978-3-03897-614-1 (Paperback)
  • ISBN978-3-03897-615-8 (PDF)

This book is a reprint of the Special Issue Molecular Modeling in Drug Design that was published in

Chemistry & Materials Science
Medicine & Pharmacology
Summary

Since the first attempts at structure-based drug design about four decades ago, molecular modelling techniques for drug design have developed enormously, along with the increasing computational power and structural and biological information of active compounds and potential target molecules. Nowadays, molecular modeling can be considered to be an integral component of the modern drug discovery and development toolbox. Nevertheless, there are still many methodological challenges to be overcome in the application of molecular modeling approaches to drug discovery. The eight original research and five review articles collected in this book provide a snapshot of the state-of-the-art of molecular modeling in drug design, illustrating recent advances and critically discussing important challenges. The topics covered include virtual screening and pharmacophore modelling, chemoinformatic applications of artificial intelligence and machine learning, molecular dynamics simulation and enhanced sampling to investigate contributions of molecular flexibility to drug–receptor interactions, the modeling of drug–receptor solvation, hydrogen bonding and polarization, and drug design against protein–protein interfaces and membrane protein receptors.

Format
  • Paperback
License
© 2019 by the authors; CC BY-NC-ND licence
Keywords
hyperlipidemia; squalene synthase (SQS); molecular modeling; drug discovery; Traditional Chinese Medicine; molecular dynamics simulation; biophenols; natural compounds; amyloid fibrils; Alzheimer’s disease; ligand–protofiber interactions; adhesion; FimH; rational drug design; molecular dynamics; molecular docking; ligand binding; EphA2-ephrin A1; PPI inhibition; interaction energy; in silico screening; adenosine; boron cluster; adenosine receptors; AR ligands; aggregation; promiscuous mechanism; human ecto-5′-nucleotidase; virtual screening; enzymatic assays; turbidimetry; dynamic light scattering; docking; solvent effect; binding affinity; scoring function; molecular dynamics; target-focused pharmacophore modeling; density-based clustering; structure-based drug design; AutoGrid; grid maps; probe energies; method development; steered molecular dynamics; all-atom molecular dynamics simulation; resultant dipole moment; mechanical stability; protein-peptide interactions; molecular dynamics; proteins; molecular recognition; protein protein interactions; artificial intelligence; deep learning; neural networks; property prediction; quantitative structure-activity relationship (QSAR); quantitative structure-property prediction (QSPR); de novo design; adenosine receptor; metadynamics; extracellular loops; allosterism; molecular dynamics; cosolvent molecular dynamics; drug design; fragment screening; docking; n/a