Download or read book QSPR QSAR Approaches for Complex Molecular Systems written by Sulev Sild and published by . This book was released on 2001 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Modelling of Molecular Descriptors in QSAR QSPR written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2012-09-13 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook and ready reference presents a combination of statistical, information-theoretic, and data analysis methods to meet the challenge of designing empirical models involving molecular descriptors within bioinformatics. The topics range from investigating information processing in chemical and biological networks to studying statistical and information-theoretic techniques for analyzing chemical structures to employing data analysis and machine learning techniques for QSAR/QSPR. The high-profile international author and editor team ensures excellent coverage of the topic, making this a must-have for everyone working in chemoinformatics and structure-oriented drug design.
Download or read book QSPR QSAR Analysis Using SMILES and Quasi SMILES written by Alla P. Toropova and published by Springer Nature. This book was released on 2023-06-10 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume overviews recently presented approaches for carrying out QSPR/QSAR analysis by using a simplifying molecular input-line entry system (SMILES) to represent the molecular structure. In contrast to traditional SMILES, quasi-SMILES is a sequence of special symbols-codes that reflect molecular features and codes of experimental conditions. SMILES and quasi-SMILES serve as a basis to develop QSPR/QSAR as well Nano-QSPR/QSAR via the Monte Carlo calculation that provides the so-called optimal descriptors for QSPR/QSAR models. The book presents a reliable technology for developing Nano-QSPR/QSAR while it also includes the description of the algorithms of the Monte Carlo optimization. It discusses the theory and practice of the technique of variational authodecoders (VAEs) based on SMILES and analyses in detail the index of ideality of correlation (IIC) and the correlation intensity index (CII) which are new criteria for the predictive potential of the model. The mathematical apparatus used is simple so that students of relevant specializations can easily follow. This volume is a valuable contribution to the field and will be of great interest to developers of models of physicochemical properties and biological activity, chemical technologists, and toxicologists involved in the area of drug design.
Download or read book A Primer on QSAR QSPR Modeling written by Kunal Roy and published by Springer. This book was released on 2015-04-11 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and pharmacy. With this in mind, the authors have carefully compiled this brief in order to provide a thorough and painless introduction to the fundamental concepts of QSAR/QSPR modelling. The brief is aimed at novice readers.
Download or read book Computational Approaches in Cheminformatics and Bioinformatics written by Rajarshi Guha and published by John Wiley & Sons. This book was released on 2012-01-04 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: A breakthrough guide employing knowledge that unites cheminformatics and bioinformatics as innovation for the future Bridging the gap between cheminformatics and bioinformatics for the first time, Computational Approaches in Cheminformatics and Bioinformatics provides insight on how to blend these two sciences for progressive research benefits. It describes the development and evolution of these fields, how chemical information may be used for biological relations and vice versa, the implications of these new connections, and foreseeable developments in the future. Using algorithms and domains as workflow tools, this revolutionary text drives bioinformaticians to consider chemical structure, and similarly, encourages cheminformaticians to consider large biological systems such as protein targets and networks. Computational Approaches in Cheminformatics and Bioinformatics covers: Data sources available for modelling and prediction purposes Developments of conventional Quantitative Structure-Activity Relationships (QSAR) Computational tools for manipulating chemical and biological data Novel ways of probing the interactions between small molecules and proteins Also including insight from public (NIH), academic, and industrial sources (Novartis, Pfizer), this book offers expert knowledge to aid scientists through industry and academic study. The invaluable applications for drug discovery, cellular and molecular biology, enzymology, and metabolism make Computational Approaches in Cheminformatics and Bioinformatics the essential guidebook for evolving drug discovery research and alleviating the issue of chemical control and manipulation of various systems.
Download or read book Fragmentation Toward Accurate Calculations on Complex Molecular Systems written by Mark S. Gordon and published by John Wiley & Sons. This book was released on 2017-10-23 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fragmentation: Toward Accurate Calculations on Complex Molecular Systems introduces the reader to the broad array of fragmentation and embedding methods that are currently available or under development to facilitate accurate calculations on large, complex systems such as proteins, polymers, liquids and nanoparticles. These methods work by subdividing a system into subunits, called fragments or subsystems or domains. Calculations are performed on each fragment and then the results are combined to predict properties for the whole system. Topics covered include: Fragmentation methods Embedding methods Explicitly correlated local electron correlation methods Fragment molecular orbital method Methods for treating large molecules This book is aimed at academic researchers who are interested in computational chemistry, computational biology, computational materials science and related fields, as well as graduate students in these fields.
Download or read book Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment written by Kunal Roy and published by Academic Press. This book was released on 2015-03-03 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles. This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR. Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment. Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods. Includes numerous practical examples related to QSAR methods and applications Follows the Organization for Economic Co-operation and Development principles for QSAR model development Discusses related techniques such as structure-based design and the combination of structure- and ligand-based design tools
Download or read book Quantum Modeling of Complex Molecular Systems written by Jean-Louis Rivail and published by Springer. This book was released on 2015-10-13 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This multi-author contributed volume includes methodological advances and original applications to actual chemical or biochemical phenomena which were not possible before the increased sophistication of modern computers. The chapters contain detailed reviews of the developments of various computational techniques, used to study complex molecular systems such as molecular liquids and solutions (particularly aqueous solutions), liquid-gas, solid-gas interphase and biomacromolecular systems. Quantum modeling of complex molecular systems is a useful resource for graduate students and fledgling researchers and is also an excellent companion for research professionals engaged in computational chemistry, material science, nanotechnology, physics, drug design, and molecular biochemistry.
Download or read book Chemoinformatics and Advanced Machine Learning Perspectives Complex Computational Methods and Collaborative Techniques written by Lodhi, Huma and published by IGI Global. This book was released on 2010-07-31 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.
Download or read book Prediction of Properties of Low and High Molecular Weight Compounds written by Carlo Giuseppe Bertinetto and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-Property/Activity Relationships (QSPR/QSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors. The capabilities of this methodology are investigated by applying it to different predictive problems: the melting point of ionic liquids, the glass transition temperature of polymers and the toxicity of organic molecules. The results show that the graphical molecular representation was able to effectively model each case, providing accurate predictions using practically no background knowledge. The proposed structure-based RNN approach, it is argued, can provide a simple and general prediction method with great potential in molecular design, toxicology and evaluation of other complex properties.
Download or read book QSPR QSAR Studies by Molecular Descriptors written by Mircea V. Diudea and published by Nova Biomedical Books. This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The central problem in QSPR (Quantitative Structure-Property Relationship) I QSAR (Quantitative Structure-Activity Relationship) is to convert chemical structures into molecular descriptors that are relevant to a certain physico-chemical property or biological activity. Although various physico-chemical properties may be subjected to QSPR/QSAR studies, the major application field of these models is drug discovery. Classically, drug discovery mainly relied on chance and massive screening of large libraries of synthesised or natural compounds. By contrast, computer-aided drug design, GADD, is an approach to rational drug design made possible by the recent advances in computational chemistry (in its various fields, such as molecular graphics, quantum chemistry, molecular mechanics, molecular dynamics, library searching, prediction of physicochemical and biological properties) and, of course, in computer science. Many physico-chemical properties can be satisfactorily correlated with the topostructural or topochemical features. Topological indices are among the simplest and efficient descriptors for QSPR/QSAR. In principle, these are mathematical objects, without a precise physical meaning. However, they may express the topological shape or may correlate with the molecular volume or surface area, as is shown in the pages of this book.
Download or read book Molecular Descriptors in QSAR QSPR written by Mati Karelson and published by Wiley-Interscience. This book was released on 2000-02-24 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular descriptors are mathematical values that describe the structure or shape of molecules, helping predict the activity and properties of molecules in complex experiments. This book describes the equations known as QSAR (quantitative structure-activity relationships) and QSPR (quantitative structure-property relationships), showing how they can be used productively in a wide range of industries.
Download or read book Quantitative Structure Activity Relationships in Drug Design Predictive Toxicology and Risk Assessment written by Roy, Kunal and published by IGI Global. This book was released on 2015-02-28 with total page 727 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative structure-activity relationships (QSARs) represent predictive models derived from the application of statistical tools correlating biological activity or other properties of chemicals with descriptors representative of molecular structure and/or property. Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment discusses recent advancements in the field of QSARs with special reference to their application in drug development, predictive toxicology, and chemical risk analysis. Focusing on emerging research in the field, this book is an ideal reference source for industry professionals, students, and academicians in the fields of medicinal chemistry and toxicology.
Download or read book Chemoinformatics Approaches to Virtual Screening written by Alexandre Varnek and published by Royal Society of Chemistry. This book was released on 2008 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Recent Advances in QSAR Studies written by Tomasz Puzyn and published by Springer Science & Business Media. This book was released on 2010-01-19 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an interdisciplinary overview on the most recent advances in QSAR studies. The first part consists of a comprehensive review of QSAR methodology. The second part highlights the interdisciplinary aspects and new areas of QSAR modelling.
Download or read book QSAR written by Hugo Kubinyi and published by John Wiley & Sons. This book was released on 2008-07-11 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding the new remedy for a certain disease: an inspired goal. QSAR, an invaluable tool in drug design, aids scientists to attain this aim. This book is a long-awaited comprehensive text to QSAR and related approaches. It provides a practice-oriented introduction to the theory, methods and analyses for QSAR relationships, including modelling-based and 3D approaches. Hugo Kubinyi is a leading expert in QSAR. Readers will benefit from the author's 20 years of practical experience, from his careful calculations and recalculations of thousands of QSAR equations. Among the topics covered are: - physiocochemical parameters - quantitative models - statistical methods - Hansch analysis - Free Wilson analysis - 3D-QSAR approaches The book can readily be used as a textbook due to its high didactic value and numerous examples (over 200 equations and 1100 references).
Download or read book Molecular Electrostatic Potentials written by J.S. Murray and published by Elsevier. This book was released on 1996-11-22 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 25 years, the molecular electrostatic potential has become firmly established as an effective guide to molecular interactions. With the recent advances in computational technology, it is currently being applied to a variety of important chemical and biological systems. Its range of applicability has expanded from primarily a focus on sites for electrophilic and nucleophilic attack to now include solvent effects, studies of zeolite, molecular cluster and crystal behavior, and the correlation and prediction of a wide range of macroscopic properties. Moreover, the increasing prominence of density functional theory has raised the molecular electrostatic potential to a new stature on a more fundamental conceptual level. It is rigorously defined in terms of the electron density, and has very interesting topological characteristics since it explicitly reflects opposing contributions from the nuclei and the electrons. This volume opens with a survey chapter by one of the original pioneers of the use of the electrostatic potential in studies of chemical reactivity, Jacopo Tomasi. Though the flow of the succeeding chapters is not stringently defined, the overall trend is that the emphasis changes gradually from methodology to applications. Chapters discussing more theoretical topics are placed near the end. Readers will find the wide variety of topics provided by an international group of authors both convincing and useful.
