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Author: Javier Luque
Publisher: Royal Society of Chemistry
Published: 2012
Total Pages: 443
ISBN-13: 1849733538
DOWNLOAD EBOOKThis title covers a wide range of topics relevant to the development of drugs. It provides a comprehensive description of the major methodological strategies available for rational drug discovery.
Author: Anil Kumar Saxena
Publisher: Springer Nature
Published: 2021-10-18
Total Pages: 405
ISBN-13: 3030852814
DOWNLOAD EBOOKThis book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals from pharmaceutical industry interested in drug design and discovery.
Author: Rupesh Kumar Gautam
Publisher: Elsevier
Published: 2023-02-15
Total Pages: 364
ISBN-13: 0323993737
DOWNLOAD EBOOKComputational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. - Explains computer use in pharmacology using real-life case studies - Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research - Describes the role of AI in pharmacology and applications of CADD in various diseases
Author: Pietro Cozzini
Publisher: Royal Society of Chemistry
Published: 2012-11-30
Total Pages: 191
ISBN-13: 1849735352
DOWNLOAD EBOOKNuclear receptors (NR) are ligand-induced activated transcription factors that are involved in numerous biological processes. Since the 1990's when the first structures were determined by means of X ray diffraction, the number of NR structures has increased considerably. Moreover several 'omics' projects (genomics, pharmcogenomics and proteomics) have opened up great opportunities for the discovery of new targets, the characterization of abnormal protein patterns, the selection of "tailored" drugs and the evaluation of drug efficacy even with a lack of structural data. Furthermore, structure-based drug design, computational methods for in silico screening and nanobiotechnology- based tools are simplifying this time-consuming and money-intensive research of lead compounds and, possibly, new drugs. Biological interactions such as those that occur between a protein and ligand are concerted events where flexible molecules interact. Thus understanding flexibility of large molecules or biological complexes is of primary importance to help define the right model to approximate the reality for drug discovery, virtual screening, food safety analysis, etc. NRs are known as flexible targets, with many structural similarities, in particular for their Ligand Binding Domain: these similarities could be assumed to share behavioural qualities that belong to this class of compounds. Thus to supply a possible, complete and exhaustive answer to questions about the behaviour of NRs, their interactions with new potential drugs, endocrine disruptors such as animal and human food toxins, food additives or industry residuals, it is mandatory to approach the problem from a different point of view: a molecular modelling approach, steered synthesis, and in vitro and in vivo tests, etc. The aim of this book is to provide a state of the art review on investigations into Nuclear Receptors.
Author: Zoran Mandic
Publisher: IAPC Publishing
Published: 2012
Total Pages: 500
ISBN-13: 9535694200
DOWNLOAD EBOOKAuthor: Yuriy A. Abramov
Publisher: John Wiley & Sons
Published: 2016-05-20
Total Pages: 440
ISBN-13: 1119229197
DOWNLOAD EBOOKThis book is the first to combine computational material science and modeling of molecular solid states for pharmaceutical industry applications. • Provides descriptive and applied state-of-the-art computational approaches and workflows to guide pharmaceutical solid state chemistry experiments and to support/troubleshoot API solid state selection • Includes real industrial case examples related to application of modeling methods in problem solving • Useful as a supplementary reference/text for undergraduate, graduate and postgraduate students in computational chemistry, pharmaceutical and biotech sciences, and materials science
Author: Nathan Brown
Publisher: Royal Society of Chemistry
Published: 2020-11-04
Total Pages: 425
ISBN-13: 1839160543
DOWNLOAD EBOOKFollowing 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: David C. Blakemore
Publisher: Royal Society of Chemistry
Published: 2016
Total Pages: 474
ISBN-13: 1849738033
DOWNLOAD EBOOKThe number of available synthetic methods can be overwhelming. In order to create novel motifs and templates which confer new and potentially valuable drug-like properties, it is important to know which synthetic methodologies will give the best results. Similarly, which methodologies are used to progress potential drug candidates from leads through the development process? What are the current industrial research problems and how can they be resolved in an industrial setting? This book highlights key methods that have real impact in drug discovery and facilitate delivery of drug molecules. Synthetic Methods in Drug Discovery Volume 1 focuses on the hugely important area of transition metal mediated methods used in industry. Current methods of importance such as the Suzuki-Miyaura coupling, Buchwald-Hartwig couplings and CH activation are discussed. In addition, exciting emerging areas such as decarboxylative coupling, and the uses of iron and nickel in coupling reactions are also covered. This book provides both academic and industrial perspectives on some key reactions giving the reader an excellent overview of the techniques used in modern synthesis. Reaction types are conveniently framed in the context of their value to industry and the challenges and limitations of methodologies are discussed with relevant illustrative examples. Edited and authored by leading scientists from both academia and industry, this book will be a valuable reference for all chemists involved in drug discovery as well as postgraduate students in medicinal chemistry.
Author: Zunnan Huang
Publisher: Frontiers Media SA
Published: 2021-03-15
Total Pages: 135
ISBN-13: 2889666018
DOWNLOAD EBOOKAuthor: Emily A. Peterson
Publisher: Royal Society of Chemistry
Published: 2015-06-11
Total Pages: 339
ISBN-13: 1782622659
DOWNLOAD EBOOKThe incorporation of Green Chemistry is a relatively new phenomenon in the drug discovery discipline, since the scale that chemists operate on in drug discovery is smaller than those of process and manufacturing chemistry. The necessary metrics are more difficult to obtain in drug discovery due to the diversity of reactions conducted. However, pharmaceutical companies are realizing that incorporation of green chemistry techniques at earlier stages of drug development can speed the development of a drug candidate. Written by experts who have pioneered green chemistry efforts within their own institutions, this book provides a practical guide for both academic and industrial labs wanting to know where to start with introducing greener approaches for greatest return on investment. The Editors have taken a comprehensive approach to the topic, covering the entire drug discovery process from molecule conception, through synthesis, formulation and toxicology with specific examples and case studies where green chemistry strategies have been implemented. Emerging techniques for performing greener drug discovery chemistry are addressed as well as cutting-edge topics like biologics discovery and continuous processing. Moreover, important surrounding issues such as intellectual property are included. This book serves as a practical guide for both academic and industrial chemists who work across the breadth of the drug discovery discipline. Ultimately, readers will learn how to incorporate green chemistry strategies into their everyday workflow without slowing down their science.
