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.

The molecular modeling perspective in drug design. (N. Calude Cohen). Molecular graphics and modeling: tools of the trade. (Roderick E. Hubbard). Molecular modeling of small molecules. (Tamara Gund). Computer assisted new lead design. (Akiko Itai, Miho Yamada Mizutani, Yoshihiko Nishibata, and Nubuo Tomioka). Experimental techniques and data banks. (John P. Priestle and C. Gregory Paris). Computer-assisted drug discovery. (Peter Gund, Gerald Maggiora, and James P. Snyder). Modeling drug-receptor interactions. (Konrad F. Koehler, Shashidhar N. Rao, and James P. Snyder). Glossary of terminology. (J. P. Tollenaere).

Molecular modeling techniques have been widely used in drug discovery fields for rational drug design and compound screening. Now these techniques are used to model or mimic the behavior of molecules, and help us study formulation at the molecular level. Computational pharmaceutics enables us to understand the mechanism of drug delivery, and to develop new drug delivery systems. The book discusses the modeling of different drug delivery systems, including cyclodextrins, solid dispersions, polymorphism prediction, dendrimer-based delivery systems, surfactant-based micelle, polymeric drug delivery systems, liposome, protein/peptide formulations, non-viral gene delivery systems, drug-protein binding, silica nanoparticles, carbon nanotube-based drug delivery systems, diamond nanoparticles and layered double hydroxides (LDHs) drug delivery systems. Although there are a number of existing books about rational drug design with molecular modeling techniques, these techniques still look mysterious and daunting for pharmaceutical scientists. This book fills the gap between pharmaceutics and molecular modeling, and presents a systematic and overall introduction to computational pharmaceutics. It covers all introductory, advanced and specialist levels. It provides a totally different perspective to pharmaceutical scientists, and will greatly facilitate the development of pharmaceutics. It also helps computational chemists to look for the important questions in the drug delivery field. This book is included in the Advances in Pharmaceutical Technology book series.

Concepts and Experimental Protocols of Modelling and Informatics in Drug Design discusses each experimental protocol utilized in the field of bioinformatics, focusing especially on computer modeling for drug development. It helps the user in understanding the field of computer-aided molecular modeling (CAMM) by presenting solved exercises and examples. The book discusses topics such as fundamentals of molecular modeling, QSAR model generation, protein databases and how to use them to select and analyze protein structure, and pharmacophore modeling for drug targets. Additionally, it discusses data retrieval system, molecular surfaces, and freeware and online servers. The book is a valuable source for graduate students and researchers on bioinformatics, molecular modeling, biotechnology and several members of biomedical field who need to understand more about computer-aided molecular modeling. - Presents exercises with solutions to aid readers in validating their own protocol - Brings a thorough interpretation of results of each exercise to help readers compare them to their own study - Explains each parameter utilized in the algorithms to help readers understand and manipulate various features of molecules and target protein to design their study

This book provides a myriad of fresh ideas and energetic approaches to the newer aspects of everyday drug modelling. With contributions from some of the best young talents of today, Molecular Modelling and Drug Design encourages a break from old traditions and probes the unexplored avenues of the modelling tool. The contributors' views act as a gauge to future trends in computer-aided drug design-an area that continues to expand and play an ever more significant role in drug discovery.

The process of drug discovery and development is a complex multistage logistics project spanned over 10-15 years with an average budget exceeding 1 billion USD. Starting with target identification and synthesizing anywhere between 10k to 15k synthetic compounds to potentially obtain the final drug that reaches the market involves a complicated maze with multiple inter- and intra-operative fields. Topics described in this book emphasize the progresses in computational applications, pharmacokinetics advances, and molecular modeling developments. In addition the book also contains special topics describing target deorphaning in Mycobacterium tuberculosis, therapy treatment of some rare diseases, and developments in the pediatric drug discovery process.

This book provides up-to-date information on bioinformatics tools for the discovery and development of new drug molecules. It discusses a range of computational applications, including three-dimensional modeling of protein structures, protein-ligand docking, and molecular dynamics simulation of protein-ligand complexes for identifying desirable drug candidates. It also explores computational approaches for identifying potential drug targets and for pharmacophore modeling. Moreover, it presents structure- and ligand-based drug design tools to optimize known drugs and guide the design of new molecules. The book also describes methods for identifying small-molecule binding pockets in proteins, and summarizes the databases used to explore the essential properties of drugs, drug-like small molecules and their targets. In addition, the book highlights various tools to predict the absorption, distribution, metabolism, excretion (ADME) and toxicity (T) of potential drug candidates. Lastly, it reviews in silico tools that can facilitate vaccine design and discusses their limitations.