Download or read book Neural Networks in QSAR and Drug Design written by James Devillers and published by Academic Press. This book was released on 1996-08-09 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive and impeccably edited, Neural Networks in QSAR and Drug Design is the first book to present an all-inclusive coverage of the topic. The book provides a practice-oriented introduction to the different neural network paradigms, allowing the reader to easily understand and reproduce the results demonstrated. Numerous examples are detailed, demonstrating a variety of applications to QSAR and drug design. The contributors include some of the most distinguished names in the field, and the book provides an exhaustive bibliography, guiding readers to all the literature related to a particular type of application or neural network paradigm. The extensive index acts as a guide to the book, and makes retrieving information from chapters an easy task. A further research aid is a list of software with indications of availablility and price, as well as the editors scale rating the ease of use and interest/price ratio of each software package. The presentation of new, powerful tools for modeling molecular properties and the inclusion of many important neural network paradigms, coupled with extensive reference aids, makes Neural Networks in QSAR and Drug Design an essential reference source for those on the frontiers of this field. Presents the first coverage of neural networks in QSAR and Drug Design Allows easy understanding and reproduction of the results described within Includes an exhaustive bibliography with more than 200 references Provides a list of applicable software packages with availability and price
Download or read book Artificial Neural Network for Drug Design Delivery and Disposition written by Munish Puri and published by Academic Press. This book was released on 2015-10-15 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Network for Drug Design, Delivery and Disposition provides an in-depth look at the use of artificial neural networks (ANN) in pharmaceutical research. With its ability to learn and self-correct in a highly complex environment, this predictive tool has tremendous potential to help researchers more effectively design, develop, and deliver successful drugs. This book illustrates how to use ANN methodologies and models with the intent to treat diseases like breast cancer, cardiac disease, and more. It contains the latest cutting-edge research, an analysis of the benefits of ANN, and relevant industry examples. As such, this book is an essential resource for academic and industry researchers across the pharmaceutical and biomedical sciences. Written by leading academic and industry scientists who have contributed significantly to the field and are at the forefront of artificial neural network (ANN) research Focuses on ANN in drug design, discovery and delivery, as well as adopted methodologies and their applications to the treatment of various diseases and disorders Chapters cover important topics across the pharmaceutical process, such as ANN in structure-based drug design and the application of ANN in modern drug discovery Presents the future potential of ANN-based strategies in biomedical image analysis and much more
Download or read book Neural Networks in QSAR and Drug Design written by James Devillers and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cheminformatics QSAR and Machine Learning Applications for Novel Drug Development written by Kunal Roy and published by Elsevier. This book was released on 2023-05-23 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book.The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates. Presents chemometrics, cheminformatics and machine learning methods under a single reference Showcases the different structure-based, ligand-based and machine learning tools currently used in drug design Highlights special topics of computational drug design and available tools and databases
Download or read book Adaptive Systems in Drug Design written by Gisbert Schneider and published by CRC Press. This book was released on 2002-10-01 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: A brief history of drug design presented to make clear that there are fashions in this important field and that they change rather rapidly. This is due in part to the fact that the way that a new paradigm is accepted in a drug company often does not depend on its scientific merit alone.
Download or read book Artificial Intelligence in Drug Design written by Alexander Heifetz and published by Humana. This book was released on 2022-11-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.
Download or read book 3D QSAR in Drug Design written by Hugo Kubinyi and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significant progress has been made in the study of three-dimensional quantitative structure-activity relationships (3D QSAR) since the first publication by Richard Cramer in 1988 and the first volume in the series. 3D QSAR in Drug Design. Theory, Methods and Applications, published in 1993. The aim of that early book was to contribute to the understanding and the further application of CoMFA and related approaches and to facilitate the appropriate use of these methods. Since then, hundreds of papers have appeared using the quickly developing techniques of both 3D QSAR and computational sciences to study a broad variety of biological problems. Again the editor(s) felt that the time had come to solicit reviews on published and new viewpoints to document the state of the art of 3D QSAR in its broadest definition and to provide visions of where new techniques will emerge or new appli- tions may be found. The intention is not only to highlight new ideas but also to show the shortcomings, inaccuracies, and abuses of the methods. We hope this book will enable others to separate trivial from visionary approaches and me-too methodology from in- vative techniques. These concerns guided our choice of contributors. To our delight, our call for papers elicited a great many manuscripts.
Download or read book De novo Molecular Design written by Gisbert Schneider and published by Wiley-VCH. This book was released on 2013-12-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules. A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions. With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come. From the content: * Reaction-driven de novo design * Adaptive methods in molecular design * Design of ligands against multitarget profiles * Free energy methods in ligand design * Fragment-based de novo design * Automated design of focused and target family-oriented compound libraries * Molecular de novo design by nature-inspired computing * 3D QSAR approaches to de novo drug design * Bioisosteres in de novo design * De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers and many more.
Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Chemoinformatics written by Johann Gasteiger and published by . This book was released on 2003 with total page 1870 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The new discipline of chemoinformatics covers the application of computer-assisted methods to chemical problems such as information storage and retrieval, the prediction of physical, chemical or biological properties of compounds, spectra simulation, structure elucidation, reaction modeling, synthesis planning and drug design. ... this four-volume Handbook contains in-depth contributions from top authors from around the world, with the content organized into chapters dealing with the representation of molecular structures and reactions, data types and databases/data sources, search methods, methods for data analysis as well as applications"--Back cover.
Download or read book Application of Neural Networks in the First Principles Calculations and Computer aided Drug Design written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: (Uncorrected OCR) Abstract of thesis entitled APPLICATION OF NEURAL NETWORKS IN THE FIRST PRINCIPLES CALCULATIONS AND COMPUTER-AIDED DRUG DESIGN submitted by Li Hong HU for the degree of Doctor of Philosophy at The University of Hong Kong in September 2004 Neural networks has been widely used in many fields such as engineering, computer science, finance, medicine, etc. Two further novel applications of neural networks have been developed: (1) combining neural networks and first principles quantum mechanical methods; and (2) utilizing a neural networks approach to determine the quantitative structure-activity relationship (QSAR) of drug leads. The new method, combined first principles calculation and neural networks correction approach (DFT-NEURON), corrects the systematic deviations of first principles calculation. Against the known experimental data, neural networks are calibrated to yield the much reduced root mean square (RMS) deviations. As the first application, the DFT-NEURON method has been applied to correct the density-functional theory (DFT) calculated thermochemistry properties of small-and medium-sized organic molecules. The accuracy of the calculated heat of formation has been successfully improved and the RMS deviation has been reduced from 21.4 to 3.1 kcal-mol-1 for B3LYP/6-311+G(d, p) basis set and from 12.0 to 3.3 kcal-mol-1 for B3LYP/6-311+G(3d/,2p). Similarly the RMS deviation of the Gibbs free energy has been reduced from 22.3 to 3.0 kcal-mol-1 for B3LYP/6-311+G(d, p) calculation. With a new set of physical descriptors, we have employed neural networks to determine the QSAR of aldose reductase inhibitors (ARIs). The established QSAR was subsequently used to predict new potent candidates for ARI. The predicted candidates were further screened via computer docking. Finally the surviving potential ARIs were tested for their bindings to the active site via quantum mechanics/molecular mechanics (QM/MM) calculation.
Download or read book Advanced Computer Assisted Techniques in Drug Discovery written by Han van de Waterbeemd and published by John Wiley & Sons. This book was released on 2008-09-26 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of powerful computers has revolutionized molecular design and drug discovery. Thoroughly researched and well-structured, this comprehensive handbook covers highly effective and efficient techniques in 3D-QSAR and advanced statistical analysis. The emphasis is on showing users how to apply these methods and avoid costly and time-consuming methodical errors. Topics covered include * combination of statistical methods and molecular modeling tools * rational use of databases * advanced statistical techniques * neural networks and expert systems in molecular design This book addresses the practitioner in industry and research, as well as the novice wishing to become acquainted with modern tools in medicinal chemistry.
Download or read book GeNeDis 2018 written by Panayiotis Vlamos and published by Springer Nature. This book was released on 2020-05-28 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 3rd World Congress on Genetics, Geriatrics, and Neurodegenerative Disease Research (GeNeDis 2018), focuses on recent advances in genetics, geriatrics, and neurodegeneration, ranging from basic science to clinical and pharmaceutical developments. It also provides an international forum for the latest scientific discoveries, medical practices, and care initiatives. Advanced information technologies are discussed, including the basic research, implementation of medico-social policies, and the European and global issues in the funding of long-term care for elderly people.
Download or read book Drug Design using Machine Learning written by Inamuddin and published by John Wiley & Sons. This book was released on 2022-11-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: DRUG DESIGN USING MACHINE LEARNING The use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field. The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. This excellent overview Provides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugs; Details the use of molecular recognition for drug development through various mathematical models; Highlights classical as well as machine learning-based approaches to study target-drug interactions in the field of drug discovery; Explores computer-aided technics for prediction of drug effectiveness and toxicity. Audience The book will be useful for information technology professionals, pharmaceutical industry workers, engineers, university researchers, medical practitioners, and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements.
Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.
Download or read book Genetic Algorithms in Molecular Modeling written by James Devillers and published by Academic Press. This book was released on 1996-06-07 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms in Molecular Modeling is the first book available on the use of genetic algorithms in molecular design. This volume marks the beginning of an ew series of books, Principles in Qsar and Drug Design, which will be an indispensible reference for students and professionals involved in medicinal chemistry, pharmacology, (eco)toxicology, and agrochemistry. Each comprehensive chapter is written by a distinguished researcher in the field. Through its up to the minute content, extensive bibliography, and essential information on software availability, this book leads the reader from the theoretical aspects to the practical applications. It enables the uninitiated reader to apply genetic algorithms for modeling the biological activities and properties of chemicals, and provides the trained scientist with the most up to date information on the topic. Extremely topical and timely Sets the foundations for the development of computer-aided tools for solving numerous problems in QSAR and drug design Written to be accessible without prior direct experience in genetic algorithms
Download or read book Drug like Properties Concepts Structure Design and Methods written by Li Di and published by Elsevier. This book was released on 2010-07-26 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of the thousands of novel compounds that a drug discovery project team invents and that bind to the therapeutic target, typically only a fraction of these have sufficient ADME/Tox properties to become a drug product. Understanding ADME/Tox is critical for all drug researchers, owing to its increasing importance in advancing high quality candidates to clinical studies and the processes of drug discovery. If the properties are weak, the candidate will have a high risk of failure or be less desirable as a drug product. This book is a tool and resource for scientists engaged in, or preparing for, the selection and optimization process. The authors describe how properties affect in vivo pharmacological activity and impact in vitro assays. Individual drug-like properties are discussed from a practical point of view, such as solubility, permeability and metabolic stability, with regard to fundamental understanding, applications of property data in drug discovery and examples of structural modifications that have achieved improved property performance. The authors also review various methods for the screening (high throughput), diagnosis (medium throughput) and in-depth (low throughput) analysis of drug properties. Serves as an essential working handbook aimed at scientists and students in medicinal chemistry Provides practical, step-by-step guidance on property fundamentals, effects, structure-property relationships, and structure modification strategies Discusses improvements in pharmacokinetics from a practical chemist's standpoint
