Concepts and Experimental Protocols of Modelling and Informatics in Drug Design Books

Click Get Book Button To Download or read online Concepts and Experimental Protocols of Modelling and Informatics in Drug Design books, Available in PDF, ePub, Tuebl and Kindle. This site is like a library, Use search box in the widget to get ebook that you want.

Concepts and Experimental Protocols of Modelling and Informatics in Drug Design


Concepts and Experimental Protocols of Modelling and Informatics in Drug Design
  • Author : Om Silakari
  • Publisher : Academic Press
  • Release : 2020-11-05
  • ISBN : 9780128205471
  • Language : En, Es, Fr & De
GET BOOK

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

Quantitative Molecular Pharmacology and Informatics in Drug Discovery


Quantitative Molecular Pharmacology and Informatics in Drug Discovery
  • Author : Michael Lutz
  • Publisher : John Wiley & Sons
  • Release : 2000-01-10
  • ISBN : 0471988618
  • Language : En, Es, Fr & De
GET BOOK

Quantitative Molecular Pharmacology and Informatics in Drug Discovery Michael Lutz, Section Head, Cheminformatics Group and Terry Kenakin, Principal Research Scientist, Glaxo Wellcome Research and Development, Research Triangle Park, NC, USA Quantitative Molecular Pharmacology and Informatics in Drug Discovery combines pharmacology, genetics and statistics to provide a complete guide to the modern drug discovery process. The book discusses the pharmacology of drug testing and provides a detailed description of the statistical methods used to analyze the resulting data. Application of genetic and genomic tools for identification of biological targets is reviewed in the context of drug discovery projects. Covering both the theoretical principles upon which the techniques are based and the practicalities of drug discovery, this informative guide. * outlines in step-by-step detail the advantages and disadvantages of each technology and approach and links these to the type of chemical target being sought after in the drug discovery process; and, * provides excellent demonstrations of how to use powerful pharmacological and statistical tools to optimize high-throughput screening assays. Written by two internationally known and well-regarded experts, this book is an essential reference for research and development scientists working in the pharmaceutical and biotechnology industries. It will also be useful for postgraduates studying pharmacology and applied statistics.

Chemoinformatics Approaches to Virtual Screening


Chemoinformatics Approaches to Virtual Screening
  • Author : Alexandre Varnek
  • Publisher : Royal Society of Chemistry
  • Release : 2008
  • ISBN : 9780854041442
  • Language : En, Es, Fr & De
GET BOOK

Chemoinformatics is broadly a scientific discipline encompassing the design, creation, organization, management, retrieval, analysis, dissemination, visualization and use of chemical information. It is distinct from other computational molecular modeling approaches in that it uses unique representations of chemical structures in the form of multiple chemical descriptors; has its own metrics for defining similarity and diversity of chemical compound libraries; and applies a wide array of statistical, data mining and machine learning techniques to very large collections of chemical compounds in order to establish robust relationships between chemical structure and its physical or biological properties. Chemoinformatics addresses a broad range of problems in chemistry and biology; however, the most commonly known applications of chemoinformatics approaches have been arguably in the area of drug discovery where chemoinformatics tools have played a central role in the analysis and interpretation of structure-property data collected by the means of modern high throughput screening. Early stages in modern drug discovery often involved screening small molecules for their effects on a selected protein target or a model of a biological pathway. In the past fifteen years, innovative technologies that enable rapid synthesis and high throughput screening of large libraries of compounds have been adopted in almost all major pharmaceutical and biotech companies. As a result, there has been a huge increase in the number of compounds available on a routine basis to quickly screen for novel drug candidates against new targets/pathways. In contrast, such technologies have rarely become available to the academic research community, thus limiting its ability to conduct large scale chemical genetics or chemical genomics research. However, the landscape of publicly available experimental data collection methods for chemoinformatics has changed dramatically in very recent years. The term "virtual screening" is commonly associated with methodologies that rely on the explicit knowledge of three-dimensional structure of the target protein to identify potential bioactive compounds. Traditional docking protocols and scoring functions rely on explicitly defined three dimensional coordinates and standard definitions of atom types of both receptors and ligands. Albeit reasonably accurate in many cases, conventional structure based virtual screening approaches are relatively computationally inefficient, which has precluded them from screening really large compound collections. Significant progress has been achieved over many years of research in developing many structure based virtual screening approaches. This book is the first monograph that summarizes innovative applications of efficient chemoinformatics approaches towards the goal of screening large chemical libraries. The focus on virtual screening expands chemoinformatics beyond its traditional boundaries as a synthetic and data-analytical area of research towards its recognition as a predictive and decision support scientific discipline. The approaches discussed by the contributors to the monograph rely on chemoinformatics concepts such as: -representation of molecules using multiple descriptors of chemical structures -advanced chemical similarity calculations in multidimensional descriptor spaces -the use of advanced machine learning and data mining approaches for building quantitative and predictive structure activity models -the use of chemoinformatics methodologies for the analysis of drug-likeness and property prediction -the emerging trend on combining chemoinformatics and bioinformatics concepts in structure based drug discovery The chapters of the book are organized in a logical flow that a typical chemoinformatics project would follow - from structure representation and comparison to data analysis and model building to applications of structure-property relationship models for hit identification and chemical library design. It opens with the overview of modern methods of compounds library design, followed by a chapter devoted to molecular similarity analysis. Four sections describe virtual screening based on the using of molecular fragments, 2D pharmacophores and 3D pharmacophores. Application of fuzzy pharmacophores for libraries design is the subject of the next chapter followed by a chapter dealing with QSAR studies based on local molecular parameters. Probabilistic approaches based on 2D descriptors in assessment of biological activities are also described with an overview of the modern methods and software for ADME prediction. The book ends with a chapter describing the new approach of coding the receptor binding sites and their respective ligands in multidimensional chemical descriptor space that affords an interesting and efficient alternative to traditional docking and screening techniques. Ligand-based approaches, which are in the focus of this work, are more computationally efficient compared to structure-based virtual screening and there are very few books related to modern developments in this field. The focus on extending the experiences accumulated in traditional areas of chemoinformatics research such as Quantitative Structure Activity Relationships (QSAR) or chemical similarity searching towards virtual screening make the theme of this monograph essential reading for researchers in the area of computer-aided drug discovery. However, due to its generic data-analytical focus there will be a growing application of chemoinformatics approaches in multiple areas of chemical and biological research such as synthesis planning, nanotechnology, proteomics, physical and analytical chemistry and chemical genomics.

Biomarkers in Drug Development


Biomarkers in Drug Development
  • Author : Michael R. Bleavins
  • Publisher : John Wiley & Sons
  • Release : 2011-09-20
  • ISBN : 9781118210420
  • Language : En, Es, Fr & De
GET BOOK

Discover how biomarkers can boost the success rate of drugdevelopment efforts As pharmaceutical companies struggle to improve the success rateand cost-effectiveness of the drug development process, biomarkershave emerged as a valuable tool. This book synthesizes and reviewsthe latest efforts to identify, develop, and integrate biomarkersas a key strategy in translational medicine and the drugdevelopment process. Filled with case studies, the bookdemonstrates how biomarkers can improve drug development timelines,lower costs, facilitate better compound selection, reducelate-stage attrition, and open the door to personalizedmedicine. Biomarkers in Drug Development is divided into eightparts: Part One offers an overview of biomarkers and their role in drugdevelopment. Part Two highlights important technologies to help researchersidentify new biomarkers. Part Three examines the characterization and validation processfor both drugs and diagnostics, and provides practical advice onappropriate statistical methods to ensure that biomarkers fulfilltheir intended purpose. Parts Four through Six examine the application of biomarkers indiscovery, preclinical safety assessment, clinical trials, andtranslational medicine. Part Seven focuses on lessons learned and the practical aspectsof implementing biomarkers in drug development programs. Part Eight explores future trends and issues, including dataintegration, personalized medicine, and ethical concerns. Each of the thirty-eight chapters was contributed by one or moreleading experts, including scientists from biotechnology andpharmaceutical firms, academia, and the U.S. Food and DrugAdministration. Their contributions offer pharmaceutical andclinical researchers the most up-to-date understanding of thestrategies used for and applications of biomarkers in drugdevelopment.

Chemoinformatics in Drug Discovery


Chemoinformatics in Drug Discovery
  • Author : Tudor I. Oprea
  • Publisher : John Wiley & Sons
  • Release : 2006-03-06
  • ISBN : 9783527604203
  • Language : En, Es, Fr & De
GET BOOK

This handbook provides the first-ever inside view of today's integrated approach to rational drug design. Chemoinformatics experts from large pharmaceutical companies, as well as from chemoinformatics service providers and from academia demonstrate what can be achieved today by harnessing the power of computational methods for the drug discovery process. With the user rather than the developer of chemoinformatics software in mind, this book describes the successful application of computational tools to real-life problems and presents solution strategies to commonly encountered problems. It shows how almost every step of the drug discovery pipeline can be optimized and accelerated by using chemoinformatics tools -- from the management of compound databases to targeted combinatorial synthesis, virtual screening and efficient hit-to-lead transition. An invaluable resource for drug developers and medicinal chemists in academia and industry.