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Author: Antoine Daina Publisher: John Wiley & Sons ISBN: 3527348395 Category : Medical Languages : en Pages : 357
Book Description
Open Access Databases and Datasets for Drug Discovery Timely resource discussing the future of data-driven drug discovery and the growing number of open-source databases With an overview of 90 freely accessible databases and datasets on all aspects of drug design, development, and discovery, Open Access Databases and Datasets for Drug Discovery is a comprehensive guide to the vast amount of “free data” available to today’s pharmaceutical researchers. The applicability of open-source data for drug discovery and development is analyzed, and their usefulness in comparison with commercially available tools is evaluated. The most relevant databases for small molecules, drugs and druglike substances, ligand design, protein 3D structures (both experimental and calculated), and human drug targets are described in depth, including practical examples of how to access and work with the data. The first part is focused on databases for small molecules, followed by databases for macromolecular targets and diseases. The final part shows how to integrate various open-source tools into the academic and industrial drug discovery and development process. Contributed to and edited by experts with long-time experience in the field, Open Access Databases and Datasets for Drug Discovery includes information on: An extensive listing of open access databases and datasets for computer-aided drug design PubChem as a chemical database for drug discovery, DrugBank Online, and bioisosteric replacement for drug discovery supported by the SwissBioisostere database The Protein Data Bank (PDB) and macromolecular structure data supporting computer-aided drug design, and the SWISS-MODEL repository of 3D protein structures and models PDB-REDO in computational aided drug design (CADD), and using Pharos/TCRD for discovering druggable targets Unmatched in scope and thoroughly reviewing small and large open data sources relevant for rational drug design, Open Access Databases and Datasets for Drug Discovery is an essential reference for medicinal and pharmaceutical chemists, and any scientists involved in the drug discovery and drug development.
Author: Antoine Daina Publisher: John Wiley & Sons ISBN: 3527348395 Category : Medical Languages : en Pages : 357
Book Description
Open Access Databases and Datasets for Drug Discovery Timely resource discussing the future of data-driven drug discovery and the growing number of open-source databases With an overview of 90 freely accessible databases and datasets on all aspects of drug design, development, and discovery, Open Access Databases and Datasets for Drug Discovery is a comprehensive guide to the vast amount of “free data” available to today’s pharmaceutical researchers. The applicability of open-source data for drug discovery and development is analyzed, and their usefulness in comparison with commercially available tools is evaluated. The most relevant databases for small molecules, drugs and druglike substances, ligand design, protein 3D structures (both experimental and calculated), and human drug targets are described in depth, including practical examples of how to access and work with the data. The first part is focused on databases for small molecules, followed by databases for macromolecular targets and diseases. The final part shows how to integrate various open-source tools into the academic and industrial drug discovery and development process. Contributed to and edited by experts with long-time experience in the field, Open Access Databases and Datasets for Drug Discovery includes information on: An extensive listing of open access databases and datasets for computer-aided drug design PubChem as a chemical database for drug discovery, DrugBank Online, and bioisosteric replacement for drug discovery supported by the SwissBioisostere database The Protein Data Bank (PDB) and macromolecular structure data supporting computer-aided drug design, and the SWISS-MODEL repository of 3D protein structures and models PDB-REDO in computational aided drug design (CADD), and using Pharos/TCRD for discovering druggable targets Unmatched in scope and thoroughly reviewing small and large open data sources relevant for rational drug design, Open Access Databases and Datasets for Drug Discovery is an essential reference for medicinal and pharmaceutical chemists, and any scientists involved in the drug discovery and drug development.
Author: Bin Yu Publisher: Elsevier ISBN: 0443239339 Category : Business & Economics Languages : en Pages : 1243
Book Description
Drug Discovery Stories: From Bench to Bedside presents a collection of cases on the development of highly successful pharmaceuticals. It delves into the realm of drug discovery, exploring the structural biology and biological functions of the sought-after targets. The book covers the identification of promising compounds, their transformation from hits to leads through meticulous optimization, and the elucidation of how key compounds interact with the target (in essence, providing invaluable insights for drug design). Additionally, it covers essential information such as the pivotal biological and PK data of lead compounds, any noteworthy clinical results, and a comprehensive overview of other candidate compounds. The field of drug discovery and development has experienced rapid evolution, with numerous new drugs receiving approval each year. While several books have been published on this subject, there is a pressing need for a new book series that accurately reflects the current advancements in drug discovery. This book aims to not only cater to the drug discovery community but also engage other communities involved in chemical biology, synthetic chemistry, and pharmacology. - Analyzes the drug discovery stories of different blockbuster drugs - Includes the newly approved drugs - Covers key aspects related to the drug development of the drugs
Author: John Schneekloth Publisher: John Wiley & Sons ISBN: 3527351000 Category : Medical Languages : en Pages : 418
Book Description
Discover a new paradigm in drug discovery that greatly expands the space of addressable drug targets and potential novel drugs Existing paradigms for drug discovery have focused largely on enzymes and other proteins as drug targets. In recent years, however, different varieties of ribonucleic acids have emerged as a viable focus for target-based drug discovery, with the potential to revolutionize the strategy and approach for this essential step in the drug development process. RNA as a Drug Target: The Next Frontier for Medicinal Chemistry offers a practice-oriented introduction to developing drug-like small molecules that selectively modulate both coding and non-coding RNAs. Beginning with a description and characterization of existing druggable RNAs, the book discusses how to approach different RNA targets for drug discovery. The result is a crucial resource for targeting RNAs and creating the next generation of life-saving pharmaceuticals. RNA as a Drug Target readers will also find: A complete “toolbox” for working with RNA, from structure determination to screening and lead generation techniques A wide range of addressable targets and mechanisms, including splicing modulation, riboswitches, targeted degradation, and more Authoritative discussion of the potential of RNA-targeted small molecule therapeutics for drugging the epitranscriptome RNA as a Drug Target provides an expert introduction to a new frontier in pharmaceutical research for medicinal chemists, biochemists, molecular biologists, and members of the pharmaceutical industry.
Author: Adriano D. Andricopulo Publisher: Frontiers Media SA ISBN: 2889457443 Category : Languages : en Pages : 415
Book Description
Chemoinformatics is paramount to current drug discovery. Structure- and ligand-based drug design strategies have been used to uncover hidden patterns in large amounts of data, and to disclose the molecular aspects underlying ligand-receptor interactions. This Research Topic aims to share with a broad audience the most recent trends in the use of chemoinformatics in drug design. To that end, experts in all areas of drug discovery have made their knowledge available through a series of articles that report state-of-the-art approaches. Readers are provided with outstanding contributions focusing on a wide variety of topics which will be of great value to those interested in the many different and exciting facets of drug design.
Author: Nathan Brown Publisher: Royal Society of Chemistry ISBN: 1839160543 Category : Computers Languages : en Pages : 425
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: Tripathi, Rati Kailash Prasad Publisher: IGI Global ISBN: Category : Medical Languages : en Pages : 337
Book Description
The world of pharmaceutical research is moving at lightning speed, and the age-old approach to drug discovery faces many challenges. It's a fascinating time to be on the cutting edge of medical innovation, but it's certainly not without its obstacles. The process of developing new drugs is often time-consuming, expensive, and fraught with uncertainty. Researchers are constantly seeking ways to streamline this process, reduce costs, and increase the success rate of bringing new drugs to market. One promising solution lies in the convergence of pharmacy science and engineering, particularly in computational drug discovery. Converging Pharmacy Science and Engineering in Computational Drug Discovery presents a comprehensive solution to these challenges by exploring the transformative synergy between pharmacy science and engineering. This book demonstrates how researchers can expedite the identification and development of novel therapeutic compounds by harnessing the power of computational approaches, such as sophisticated algorithms and modeling techniques. Through interdisciplinary collaboration, pharmacy scientists and engineers can revolutionize drug discovery, paving the way for more efficient and effective treatments. This book is an invaluable resource for pharmaceutical scientists, researchers, and engineers seeking to enhance their understanding of computational drug discovery. This book inspires future innovations by showcasing cutting-edge methodologies and innovative research at the intersection of pharmacy science and engineering. It contributes to the ongoing evolution of pharmaceutical research. It offers practical insights and solutions that will shape the future of drug discovery, making it essential reading for anyone involved in the pharmaceutical industry.
Author: De-Shuang Huang Publisher: Springer Nature ISBN: 9819947499 Category : Technology & Engineering Languages : en Pages : 835
Book Description
This three-volume set of LNCS 14086, LNCS 14087 and LNCS 14088 constitutes - in conjunction with the double-volume set LNAI 14089-14090- the refereed proceedings of the 19th International Conference on Intelligent Computing, ICIC 2023, held in Zhengzhou, China, in August 2023. The 337 full papers of the three proceedings volumes were carefully reviewed and selected from 828 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Author: Pooja A. Chawla Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3111207595 Category : Science Languages : en Pages : 543
Book Description
Computational methods and understanding computational models are important in modern drug discovery. The book focuses on computational approaches that can improve the development of in silico methodologies. It includes lead hit methods, docking algorithms, computational chiral compounds, structure-based drug design, GROMACS and NAMD, structural genomics, toxicity prediction, enzyme inhibitors and peptidomimetic therapeutics
Author: Anil K. Philip Publisher: Academic Press ISBN: 0323903738 Category : Computers Languages : en Pages : 644
Book Description
A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. This book will be useful to academic and industrial researchers interested in drug delivery, chemical biology, computational chemistry, medicinal chemistry and bioinformatics. The massive time and costs investments in drug research and development necessitate application of more innovative techniques and smart strategies. - Focuses on the use of Artificial Intelligence in drug delivery strategies and future impacts - Provides insights into how artificial intelligence can be effectively used for the development of advanced drug delivery systems - Written by experts in the field of advanced drug delivery systems and digital health
Author: Antoine Daina
Author: Antoine Daina
Author: Bin Yu
Author: John Schneekloth
Author: Adriano D. Andricopulo
Author: Nathan Brown
Author: Tripathi, Rati Kailash Prasad
Author: De-Shuang Huang
Author: Pooja A. Chawla
Author: Fei Ye
Author: Anil K. Philip