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Author: Klaus Gundertofte
Publisher: Springer Science & Business Media
ISBN: 1461541417
Category : Science
Languages : en
Pages : 490
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Book Description
Much of chemistry, molecular biology, and drug design, are centered around the relationships between chemical structure and measured properties of compounds and polymers, such as viscosity, acidity, solubility, toxicity, enzyme binding, and membrane penetration. For any set of compounds, these relationships are by necessity complicated, particularly when the properties are of biological nature. To investigate and utilize such complicated relationships, henceforth abbreviated SAR for structure-activity relationships, and QSAR for quantitative SAR, we need a description of the variation in chemical structure of relevant compounds and biological targets, good measures of the biological properties, and, of course, an ability to synthesize compounds of interest. In addition, we need reasonable ways to construct and express the relationships, i. e. , mathematical or other models, as well as ways to select the compounds to be investigated so that the resulting QSAR indeed is informative and useful for the stated purposes. In the present context, these purposes typically are the conceptual understanding of the SAR, and the ability to propose new compounds with improved property profiles. Here we discuss the two latter parts of the SARlQSAR problem, i. e. , reasonable ways to model the relationships, and how to select compounds to make the models as "good" as possible. The second is often called the problem of statistical experimental design, which in the present context we call statistical molecular design, SMD. 1.
Author: Klaus Gundertofte
Publisher: Springer Science & Business Media
ISBN: 1461541417
Category : Science
Languages : en
Pages : 490
Get Book Here
Book Description
Much of chemistry, molecular biology, and drug design, are centered around the relationships between chemical structure and measured properties of compounds and polymers, such as viscosity, acidity, solubility, toxicity, enzyme binding, and membrane penetration. For any set of compounds, these relationships are by necessity complicated, particularly when the properties are of biological nature. To investigate and utilize such complicated relationships, henceforth abbreviated SAR for structure-activity relationships, and QSAR for quantitative SAR, we need a description of the variation in chemical structure of relevant compounds and biological targets, good measures of the biological properties, and, of course, an ability to synthesize compounds of interest. In addition, we need reasonable ways to construct and express the relationships, i. e. , mathematical or other models, as well as ways to select the compounds to be investigated so that the resulting QSAR indeed is informative and useful for the stated purposes. In the present context, these purposes typically are the conceptual understanding of the SAR, and the ability to propose new compounds with improved property profiles. Here we discuss the two latter parts of the SARlQSAR problem, i. e. , reasonable ways to model the relationships, and how to select compounds to make the models as "good" as possible. The second is often called the problem of statistical experimental design, which in the present context we call statistical molecular design, SMD. 1.
Author: Klaus Gundertofte
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 528
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Book Description
The book covers highly important topics in the challenging process from lead finding to drug candidates. Focus is upon the potential usefulness of methods for design of lead discovery libraries, lead optimisation, computational chemistry methods for the calculation of energetics of protein-ligand interaction, and computer simulations of biological activities. Important topics include new developments in chemometrics and rational molecular design as well as different aspects of structure representation, knowledge-based approaches to structure identification, and information handling.
Author: Christoph Sotriffer
Publisher: John Wiley & Sons
ISBN: 3527633340
Category : Medical
Languages : en
Pages : 774
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Book Description
Drug discovery is all about finding small molecules that interact in a desired way with larger molecules, namely proteins and other macromolecules in the human body. If the three-dimensional structures of both the small and large molecule are known, their interaction can be tested by computer simulation with a reasonable degree of accuracy. Alternatively, if active ligands are already available, molecular similarity searches can be used to find new molecules. This virtual screening can even be applied to compounds that have yet to be synthesized, as opposed to "real" screening that requires cost- and labor-intensive laboratory testing with previously synthesized drug compounds. Unique in its focus on the end user, this is a real "how to" book that does not presuppose prior experience in virtual screening or a background in computational chemistry. It is both a desktop reference and practical guide to virtual screening applications in drug discovery, offering a comprehensive and up-to-date overview. Clearly divided into four major sections, the first provides a detailed description of the methods required for and applied in virtual screening, while the second discusses the most important challenges in order to improve the impact and success of this technique. The third and fourth, practical parts contain practical guidelines and several case studies covering the most important scenarios for new drug discovery, accompanied by general guidelines for the entire workflow of virtual screening studies. Throughout the text, medicinal chemists from academia, as well as from large and small pharmaceutical companies report on their experience and pass on priceless practical advice on how to make best use of these powerful methods.
Author: Hans-Joachim Böhm
Publisher: John Wiley & Sons
ISBN: 3527613099
Category : Science
Languages : de
Pages : 325
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Book Description
Recent progress in high-throughput screening, combinatorial chemistry and molecular biology has radically changed the approach to drug discovery in the pharmaceutical industry. New challenges in synthesis result in new analytical methods. At present, typically 100,000 to one million molecules have to be tested within a short period and, therefore, highly effective screening methods are necessary for today's researchers - preparing and characterizing one compound after another belongs to the past. Intelligent, computer-based search agents are needed and "virtual screening" provides solutions to many problems. Such screening comprises innovative computational techniques designed to turn raw data into valuable chemical information and to assist in extracting the relevant molecular features. This handbook is unique in bringing together the various efforts in the field of virtual screening to provide the necessary methodological framework for more effective research. Leading experts give a thorough introduction to the state of the art along with a critical assessment of both successful applications and drawbacks. The information collated here will be indispensable for experienced scientists, as well as novices, working in medicinal chemistry and related disciplines.
Author: Richard S. Larson
Publisher:
ISBN: 9781617799655
Category : Bioinformatics
Languages : en
Pages : 374
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Book Description
Recent advances in drug discovery have been rapid. The second edition of Bioinformatics and Drug Discovery has been completely updated to include topics that range from new technologies in target identification, genomic analysis, cheminformatics, protein analysis, and network or pathway analysis. Each chapter provides an extended introduction that describes the theory and application of the technology. In the second part of each chapter, detailed procedures related to the use of these technologies and software have been incorporated. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Bioinformatics and Drug Discovery, Second Edition seeks to aid scientists in the further study of the rapidly expanding field of drug discovery.
Author: F. Hirata
Publisher: Springer Science & Business Media
ISBN: 1402025904
Category : Science
Languages : en
Pages : 366
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Book Description
Molecular Theory of Solvation presents the recent progress in the statistical mechanics of molecular liquids applied to the most intriguing problems in chemistry today, including chemical reactions, conformational stability of biomolecules, ion hydration, and electrode-solution interface. The continuum model of "solvation" has played a dominant role in describing chemical processes in solution during the last century. This book discards and replaces it completely with molecular theory taking proper account of chemical specificity of solvent. The main machinery employed here is the reference-interaction-site-model (RISM) theory, which is combined with other tools in theoretical chemistry and physics: the ab initio and density functional theories in quantum chemistry, the generalized Langevin theory, and the molecular simulation techniques. This book will be of benefit to graduate students and industrial scientists who are struggling to find a better way of accounting and/or predicting "solvation" properties.
Author:
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 4576
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Book Description
Author: Nathan Brown
Publisher: Royal Society of Chemistry
ISBN: 1839160543
Category : Computers
Languages : en
Pages : 425
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Book Description
Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.
Author: Alexandre Varnek
Publisher: Royal Society of Chemistry
ISBN: 0854041443
Category : Computers
Languages : en
Pages : 356
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Book Description
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.
Author: Pandi Veerapandian
Publisher: Routledge
ISBN: 1351413066
Category : Medical
Languages : en
Pages : 665
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Book Description
Introducing the most recent advances in crystallography, nuclear magnetic resonance, molecular modeling techniques, and computational combinatorial chemistry, this unique, interdisciplinary reference explains the application of three-dimensional structural information in the design of pharmaceutical drugs. Furnishing authoritative analyses by world-renowned experts, Structure-Based Drug Design discusses protein structure-based design in optimizing HIV protease inhibitors and details the biochemical, genetic, and clinical data on HIV-1 reverse transcriptase presents recent results on the high-resolution three-dimensional structure of the catalytic core domain of HIV-1 integrase as a foundation for divergent combination therapy focuses on structure-based design strategies for uncovering receptor antagonists to treat inflammatory diseases demonstrates a systematic approach to the design of inhibitory compounds in cancer treatment reviews current knowledge on the Interleukin-1 (IL-1) system and progress in the development of IL-1 modulators describes the influence of structure-based methods in designing capsid-binding inhibitors for relief of the common cold and much more!
