In Silico Drug Discovery and Design: Theory, Methods, Challenges, and Applications provides a comprehensive, unified, and in-depth overview of the current methodological strategies in computer-aided drug discovery and design. Its main aims are to introduce the theoretical framework and algorithms, discuss the range of validity, strengths and limita
In Silico Drug Design: Repurposing Techniques and Methodologies explores the application of computational tools that can be utilized for this approach. The book covers theoretical background and methodologies of chem-bioinformatic techniques and network modeling and discusses the various applied strategies to systematically retrieve, integrate and analyze datasets from diverse sources. Other topics include in silico drug design methods, computational workflows for drug repurposing, and network-based in silico screening for drug efficacy. With contributions from experts in the field and the inclusion of practical case studies, this book gives scientists, researchers and R&D professionals in the pharmaceutical industry valuable insights into drug design. Discusses the theoretical background and methodologies of useful techniques of cheminformatics and bioinformatics that can be applied for drug repurposing Offers case studies relating to the in silico modeling of FDA-approved drugs for the discovery of antifungal, anticancer, antiplatelet agents, and for drug therapies against diseases Covers tools and databases that can be utilized to facilitate in silico methods for drug repurposing
|Author||: Darryl Leon,Scott Markel|
|Publisher||: CRC Press|
|Release Date||: 2006-06-13|
|ISBN 10||: 1420015737|
|Pages||: 504 pages|
The pharmaceutical industry relies on numerous well-designed experiments involving high-throughput techniques and in silico approaches to analyze potential drug targets. These in silico methods are often predictive, yielding faster and less expensive analyses than traditional in vivo or in vitro procedures. In Silico Technologies in Drug Target Identification and Validation addresses the challenge of testing a growing number of new potential targets and reviews currently available in silico approaches for identifying and validating these targets. The book emphasizes computational tools, public and commercial databases, mathematical methods, and software for interpreting complex experimental data. The book describes how these tools are used to visualize a target structure, identify binding sites, and predict behavior. World-renowned researchers cover many topics not typically found in most informatics books, including functional annotation, siRNA design, pathways, text mining, ontologies, systems biology, database management, data pipelining, and pharmacogenomics. Covering issues that range from prescreening target selection to genetic modeling and valuable data integration, In Silico Technologies in Drug Target Identification and Validation is a self-contained and practical guide to the various computational tools that can accelerate the identification and validation stages of drug target discovery and determine the biological functionality of potential targets more effectively. Daniel E. Levy, editor of the Drug Discovery Series, is the founder of DEL BioPharma, a consulting service for drug discovery programs. He also maintains a blog that explores organic chemistry.
Infectious diseases caused by viruses, parasites, bacteria, and fungi are the number one cause of death worldwide. Although new technologies have improved diagnosis of infectious diseases, the efficacy of all known current anti-infective agents is threatened by the spread of drug-resistant forms of the pathogens. Hence, there remains an urgent need to develop anti-infective agents that target drug-resistant pathogens. In Silico Models for Drug Discovery presents a comprehensive look at the role in silico models play in understanding infectious diseases and in developing novel therapeutics to treat them. Written by leading experts in the field, chapters cover topics such as techniques to derive novel antimicrobial targets, methods of interpreting polypharmacology-based drug target networks, and molecular dynamics techniques used to compute binding energies of drugs to their target proteins, to name a few. Written in the successful Methods in Molecular BiologyTM series or in review article format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and easily accessible, In Silico Models for Drug Discovery seeks to serve both professionals and novices involved in the study and treatment of infectious diseases.
Computer-aided drug design and in silico screening have contributed to the discovery of several compounds that have either reached the market or entered clinical trials. In silico Lead Discovery is a compilation of the efforts of several experts on bioinf
The application of bioinformatics approaches in drug design involves an interdisciplinary array of sophisticated techniques and software tools to elucidate hidden or complex biological data. This work reviews the latest bioinformatics approaches used for drug discovery. The text covers ligand-based and structure-based approaches for computer-aided drug design, 3D pharmacophore modeling, molecular dynamics simulation, the thermodynamics of ligand−receptor and ligand−enzyme association, thermodynamic characterization and optimization, and techniques for computational genomics and proteomics.
|Author||: Adriano D. Andricopulo,Leonardo L. G. Ferreira|
|Publisher||: Frontiers Media SA|
|Release Date||: 2019-02-05|
|ISBN 10||: 2889457443|
|Pages||: 329 pages|
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||: Manikanta Murahari,Lakshmi Sundar,Soma Chaki,Vasanthanathan Poongavanam,Pritesh Bhat,Usha Y Nayak|
|Publisher||: Royal Society of Chemistry|
|Release Date||: 2019-11-20|
|ISBN 10||: 1788018621|
|Pages||: 350 pages|
This publication is based on peer-reviewed manuscripts from the 2019 Conference on Drug Design & Discovery Technologies (CDDT) held at Ramaiah University of Applied Sciences, India. Providing a wide range of up to date topics on the latest advancements in drug design and discovery technologies, this book ensures the reader receives a good understanding of the scope of the field. Aimed at scientists, students, regulators, academics and consultants throughout the world, this book is an ideal resource for anyone interested in the state of the art in drug design and discovery.
This book is a landmark in the continuously changing world of drugs. It is essential reading for scientists and managers in the pharmaceutical industry who are involved in drug finding, drug development and decision making in the development process.
|Pages||: 329 pages|
Abstract: Staphylococcus aureus, a member of Staphylococcacea has been considered as an opportunistic pathogen in humans and livestock. Thus, the suggestion has been made to discover a potential drug to address Staphylococcus aureus infections. In the present study, drug designing of natural antistaphylococcal compounds, comprised of docking study of acetylated abietane quinone against ClfA (clumping factor A) using the AutoDock tool, was performed and the formed hydrogen bonds in the docked complex were analyzed using Pymol software. A drug library of 86 natural antistaphylococcal compounds was generated and screened with Lipinski and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) filters using Molinspiration and PreADMET tools. A host-pathogen interaction network of Staphylococcus aureus and humans was developed using Cytoscape tool. After applying filters and performing an analysis, acetylated abietane quinone, which is a natural antistaphylococcal compound and a component of mint, was obtained. The binding energy of the docked complex of ligand acetylated abietane quinone against receptor ClfA was estimated to be −7.52kcal/mol, which showed good binding affinity. Thus, acetylated abietane quinone could serve as a drug for treating staphylococcal infections in humans. A total of 40 interactions between S.aureus and humans were identified and represented using the developed host-pathogen interaction network, which should provide a significant target-based drug discovery for treating S.aureus infections in humans.
This is the first resource to provide researchers in academia and industry with an urgently needed update on drug intervention against trypanosomatides. As such, it covers every aspect of the topic from basic research findings, via current treatments to translational approaches in drug development and includes both human and livestock diseases. The outstanding editor and contributor team reads like a Who?s Who of the field, thus guaranteeing the outstanding quality of this ready reference.
This book provides up-to-date information on bioinformatics tools for the discovery and development of new drug molecules. It discusses a range of computational applications, including three-dimensional modeling of protein structures, protein-ligand docking, and molecular dynamics simulation of protein-ligand complexes for identifying desirable drug candidates. It also explores computational approaches for identifying potential drug targets and for pharmacophore modeling. Moreover, it presents structure- and ligand-based drug design tools to optimize known drugs and guide the design of new molecules. The book also describes methods for identifying small-molecule binding pockets in proteins, and summarizes the databases used to explore the essential properties of drugs, drug-like small molecules and their targets. In addition, the book highlights various tools to predict the absorption, distribution, metabolism, excretion (ADME) and toxicity (T) of potential drug candidates. Lastly, it reviews in silico tools that can facilitate vaccine design and discusses their limitations.
|Author||: C. Gopi Mohan|
|Release Date||: 2019-01-10|
|ISBN 10||: 3030052826|
|Pages||: 406 pages|
This book reviews the advances and challenges of structure-based drug design in the preclinical drug discovery process, addressing various diseases, including malaria, tuberculosis and cancer. Written by internationally recognized researchers, this edited book discusses how the application of the various in-silico techniques, such as molecular docking, virtual screening, pharmacophore modeling, molecular dynamics simulations, and residue interaction networks offers insights into pharmacologically active novel molecular entities. It presents a clear concept of the molecular mechanism of different drug targets and explores methods to help understand drug resistance. In addition, it includes chapters dedicated to natural-product- derived medicines, combinatorial drug discovery, the CryoEM technique for structure-based drug design and big data in drug discovery. The book offers an invaluable resource for graduate and postgraduate students, as well as for researchers in academic and industrial laboratories working in the areas of chemoinformatics, medicinal and pharmaceutical chemistry and pharmacoinformatics.
In the current drug research environment in academia and industry, cheminformatics and virtual screening methods are well established and integrated tools. Computational tools are used to predict a compound’s 3D structure, the 3D structure and function of a pharmacological target, ligand-target interactions, binding energies, and other factors essential for a successful drug. This includes molecular properties such as solubility, logP value, susceptibility to metabolism, cell permeation, blood brain barrier permeation, interaction with drug transporters and potential off-target effects. Given that approximately 40 million unique compounds are readily available for purchase, such computational modeling and filtering tools are essential to support the drug discovery and development process. The aim of all these calculations is to focus experimental efforts on the most promising candidates and exclude problematic compounds early in the project. In this Research Topic on virtual activity predictions, we cover several aspects of this research area such as historical perspectives, data sources, ligand treatment, virtual screening methods, hit list handling and filtering.
|Author||: Jujjvarapu Satya Eswari,Swasti Dhagat,Manisha Yadav|
|Publisher||: CRC Press|
|Release Date||: 2019-09-24|
|ISBN 10||: 1351018299|
|Pages||: 130 pages|
Increase in antibiotic resistance has forced researchers to develop new drugs against microorganisms. Lipopeptides are produced as secondary metabolites by some microorganisms. Computer-aided Design of Antimicrobial Lipopeptides as Prospective Drug Candidates provides the identification of novel ligands for different antimicrobial lipopeptides. Along with identification, it also provides some of the in silico drug design processes, namely homology modelling, molecular docking, QSAR studies, drug ADMET studies and pharmacophore studies to check the ligand-lipopeptide interaction. Some lipopeptides have shown anti-cancerous properties too, and this book discusses the required templates to design new drugs using computational techniques. Key Features: Focuses on the use lipopeptides as new antimicrobial compounds Presents the basics of in silico modelling for design and development of new drug molecules, and is therefore of interest to beginners in the field Provides a step-by-step process for identification of drug molecules and testing its efficacy in silico Couples with courses on patents and intellectual property rights
Drug discovery is an expensive, time-consuming process and the modern drug discovery community is constantly challenged not only with discovering novel bioactive agents to combat resistance from known diseases and fight against new ones, but to do so in a way that is economically effective. Advances in both experimental and theoretical/computational methods envisage that the greatest challenges in drug discovery can be most successfully addressed by using a multi-scale approach, drawing on the specialties of a whole host of different disciplines. Multi-Scale Approaches to Drug Discovery furnishes chemists with the detail they need to identify drug leads with the highest potential before isolating and synthesizing them to produce effective drugs with greater swiftness than classical methods may allow. This significantly speeds up the search for more efficient therapeutic agents. After an introduction to multi-scale approaches outlining the need for and benefits of their use, the book goes on to explore a range of useful techniques and research areas, and their potential applications to this process. Profiling drug binding by thermodynamics, machine learning for predicting enzyme sub-classes, and multitasking models for computer-aided design and virtual compound screening are discussed, before the book goes on to review Alkaloid Menispermaceae leads, natural chemotherapeutic agents and methods for speeding up the design and virtual screening of therapeutic peptides. Flavonoids as multi-target compounds are then explored, before the book concludes with a review of Quasi-SMILES as a novel tool. Collecting together reviews and original research contributions written by leading experts in the field, Multi-Scale Approaches to Drug Discovery highlights cutting-edge approaches and practical examples of their implementation for those involved in the drug discovery process at many different levels. Using the combined knowledge of medicinal, computational, pharmaceutical and bio- chemists, it aims to support growth in the multi-scale approach to promote greater success in the development of new drugs. Offers practical guidance on ways to implement multiscale approaches for increased efficiency in drug discovery Draws on the experience of a highly skilled team of authors under the editorial guidance of one of the field's leading experts Includes cutting-edge techniques at the forefront of medicinal chemistry and drug discovery optimization
|Author||: Steve Suib,Huangxian Ju,Serge Cosnier,Bunsho Ohtani,John D. Wade,Gil Garnier,Nosang Vincent Myung,Luís D. Carlos,Michael Kassiou,Fan Zhang,Iwao Ojima,Pellegrino Musto,Tony D. James,Thomas S. Hofer,Sam P. De Visser|
|Publisher||: Frontiers Media SA|
|Release Date||: 2020-04-17|
|ISBN 10||: 2889635805|
|Pages||: 329 pages|
The Frontiers in Chemistry Editorial Office team are delighted to present the inaugural “Frontiers in Chemistry: Rising Stars” article collection, showcasing the high-quality work of internationally recognized researchers in the early stages of their independent careers. All Rising Star researchers featured within this collection were individually nominated by the Journal’s Chief Editors in recognition of their potential to influence the future directions in their respective fields. The work presented here highlights the diversity of research performed across the entire breadth of the chemical sciences, and presents advances in theory, experiment and methodology with applications to compelling problems. This Editorial features the corresponding author(s) of each paper published within this important collection, ordered by section alphabetically, highlighting them as the great researchers of the future. The Frontiers in Chemistry Editorial Office team would like to thank each researcher who contributed their work to this collection. We would also like to personally thank our Chief Editors for their exemplary leadership of this article collection; their strong support and passion for this important, community-driven collection has ensured its success and global impact. Laurent Mathey, PhD Journal Development Manager
Helps you choose the right computational tools and techniques to meet your drug design goals Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes. Following an introduction, the book is divided into three parts: Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals. Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques. Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches. The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies. Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.