Concepts And Experimental Protocols Of Modelling And Informatics In Drug Design

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

Molecular modelling is the scientific art of simulating chemicalor biological systems, so that computational methods can beapplied to understand the process concerned. Models usingcomputers are generated using mathematical equations and areevolved based on experimental information that is taken intoconsideration during model building. This book is anintroduction to the field of molecular modelling and drug designin which biological molecules effective in treating diseases arediscovered using in silico methods.

In the literature, several terms are used synonymously to name the topic of this book: chem-, chemi-, or chemo-informatics. A widely recognized de- nition of this discipline is the one by Frank Brown from 1998 (1) who defined chemoinformatics as the combination of “all the information resources that a scientist needs to optimize the properties of a ligand to become a drug. ” In Brown’s definition, two aspects play a fundamentally important role: de- sion support by computational means and drug discovery, which distinguishes it from the term “chemical informatics” that was introduced at least ten years earlier and described as the application of information technology to ch- istry (not with a specific focus on drug discovery). In addition, there is of course “chemometrics,” which is generally understood as the application of statistical methods to chemical data and the derivation of relevant statistical models and descriptors (2). The pharmaceutical focus of many developments and efforts in this area—and the current popularity of gene-to-drug or si- lar paradigms—is further reflected by the recent introduction of such terms as “discovery informatics” (3), which takes into account that gaining kno- edge from chemical data alone is not sufficient to be ultimately successful in drug discovery. Such insights are well in accord with other views that the boundaries between bio- and chemoinformatics are fluid and that these d- ciplines should be closely combined or merged to significantly impact b- technology or pharmaceutical research (4).

Specially designed computer software is revolutionizing procedures for structured or rational drug design and discovery. The Guidebook on Molecular Modeling in Drug Design serves as a manual for the analysis ofmolecular structure and the correlation of these structures with pharmacological reactions. Intended as an introductory guide for advanced students and professionals with an interest in computer-assisted modeling for drug design and discovery, this bookwill also be of interest to medicinal and organic chemists, pharmaceutical researchers, pharmacologists, and biochemists who want to gain further insight into this rapidly advancing field. Molecular modeling is assuming an important role in the understanding of three-dimensional aspects in the specificity of drug-receptor interactions at the molecular level. This research area has become a well-established discipline in pharmaceutical research. It has created unprecedented opportunities in assisting medicinal chemists in the design of new therapeutic agents. Advances made in computer hardware and in theoretical medicinal chemistry have brought high-performance computing and graphics tools within reach of most academic and industrial laboratories, facilitating the development of useful approaches to rational drug design. The Guidebook on Molecular Modeling in Drug Design serves as a manual for the analysis of the molecular structure of biological molecules and drugs and the correlation of these structures with pharmacological actions. Intended as a guide for advanced students and professionals with an interest in computer-assisted modeling for drug design and discovery, this book will also be of interest to medicinal and organic chemists, pharmaceutical researchers, pharmacologists, and biochemists who want to gain further insight into this rapidly advancing field.

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.

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.

Pharmaceutical research draws on increasingly complex techniques to solve the challenges of drug design. Bringing together a number of the latest informatics techniques, this book looks at modelling and bioinformatic strategies; structural genomics and X-ray crystallography; virtual screening; lead optimisation; ADME profiling and vaccine design. A number of relevant case studies, focussing on techniques that have demonstrated their use, will concentrate on G-protein coupled receptors as potential disease targets. Providing details of state-of-the-art research, Drug Design: Cutting Edge Approaches will be invaluable to all drug discovery scientists, including medicinal and combinatorial chemists, molecular modellers, bio- and chemoinformaticians, and pharmacologists, amongst others. University and pharmaceutical company libraries will also benefit from having a copy on their shelves.

Kleine Moleküle für Einsteiger: Dieser für Lehre und Selbststudium gleichermaßen geeignete Band behandelt den computergestützten Entwurf von Wirkstoffen, Enzyminhibitoren, Sonden und Markern für Biomoleküle und führt den Leser bis zum ersten eigenen De-Novo-Design eines funktionellen Moleküls. Gestützt auf lange Erfahrung im Molecular-Modeling-Umfeld erläutern die Autoren, welche Fragen mit den beschriebenen Methoden beantwortet werden können (und welche nicht).