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Computational phytochemistry /

Annotation

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Sarker, Satyajit D. (Editor ), Nahar, Lutfun, 1969- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam, Netherlands : Elsevier, [2018]
Edición:First edition.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Computational phytochemistry /  |c edited by Satyajit D. Sarker, Lutfun Nahar. 
250 |a First edition. 
264 1 |a Amsterdam, Netherlands :  |b Elsevier,  |c [2018] 
264 4 |c �2018 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
588 0 |a Online resource; title from PDF title page (ScienceDirect, viewed May 9, 2018). 
505 0 |a Front Cover; Computational Phytochemistry; Copyright; Dedication; Contents; Contributors; Foreword; Preface; Chapter 1: An Introduction to Computational Phytochemistry; 1.1 Introduction; 1.2 Computational Phytochemistry; 1.3. Techniques, Theories, and Applications of Computational Phytochemistry; 1.3.1 Kohonen-Based Self-Organizing Map; 1.3.2 Density Functional Theory; 1.3.3 Docking Experiments and Virtual Screening (In Silico Screening); 1.3.4 Structure Prediction and Structure Determination; 1.3.5 Chemometrics and Principal Component Analysis; 1.3.6 Data Mining and Databases 
505 8 |a 1.3.7 Response Surface Methodology in Optimization of Extraction of Phytochemicals1.3.8 Computation in Isolation of Phytochemicals; 1.3.9 Miscellaneous; 1.4 Conclusions; References; Chapter 2: Prediction of Medicinal Properties Using Mathematical Models and Computation, and Selection of Plant Materials; 2.1 Introduction; 2.2 Mathematical Models; 2.3. Computational Models in Drug Discovery; 2.3.1 Structure-Based CADD; 2.3.2 Ligand-Based CADD; 2.3.3 Network Pharmacology; 2.4. Selection of Medicinal Plants; 2.4.1 Ethnobotany-Directed Drug Discovery; 2.4.2 Chemotaxonomic and Ecological Approach 
505 8 |a 2.4.3 Random Approach2.4.4 Integrated Approach; 2.5 Role of Medicinal Plants Databases; 2.6 Tools and Techniques; 2.7 Role of Data Mining in Medicinal Plant Selection; 2.8 Safety Considerations; 2.9 Conclusion; References; Chapter 3: Optimization of Extraction Using Mathematical Models and Computation; 3.1 Introduction; 3.2. Fundamentals of Design of Experiments; 3.2.1 Planning Phase; 3.2.2 Designing Phase; 3.2.2.1 Screening Phase; Full Factorial Design (2k); Fractional Factorial Design (2kp); Plackett-Burman Design; Taguchi Design; 3.2.2.2 Optimization Phase; Terminologies We Need to Know 
505 8 |a Sequential Nature of Response Surface MethodologyOptimization Designs; 3.3 DoE-Based Optimization of MAE Process; 3.4 DoE-Based Optimization of Supercritical Fluid Extraction Process; 3.5 DoE-Based Optimization of Accelerated Solvent Extraction Process; 3.6 Conclusions; References; Chapter 4: Application of Computational Methods in Isolation of Plant Secondary Metabolites; 4.1 Introduction; 4.2. Computational Methods in Natural Products Isolations; 4.2.1 Automated Flash Chromatography; 4.2.2 High-Performance/Pressure Liquid Chromatography 
505 8 |a 4.2.3 Ultra-Pressure/Performance Liquid Chromatography4.2.4 Counter Current Chromatography; 4.2.5 Capillary Electrophoresis; 4.2.6 Hyphenated Techniques; 4.2.6.1 GC-MS; 4.2.6.2 LC-MS; 4.2.6.3 LC-NMR; 4.3 Conclusion; References; Further Reading; Chapter 5: Application of Computation in Building Dereplicated Phytochemical Libraries; 5.1 Introduction; 5.2. Compound Library; 5.2.1 Combinatorial Library; 5.2.2 Phytochemical Library; 5.3 Dereplication; 5.4 Application of Computation in Building Dereplicated Phytochemical Libraries; 5.5 Conclusions; References 
520 8 |a Annotation  |b Computational Phytochemistry explores how recent advances in computational techniques and methods have been embraced by phytochemical researchers to enhance many of their operations, thus refocusing and expanding the possibilities of phytochemical studies. By applying computational aids and mathematical models to extraction, isolation, structure determination and bioactivity testing, researchers can extract highly detailed information about phytochemicals and optimize working approaches. This book aims to support and encourage researchers currently working with, or looking to incorporate, computational methods into their phytochemical work. Topics in this book include computational methods for predicting medicinal properties, optimizing extraction, isolating plant secondary metabolites and building dereplicated phytochemical libraries. The role of high-throughput screening, spectral data for structural prediction, plant metabolomics and biosynthesis are all reviewed, before the application of computational aids for assessing bioactivities and virtual screening are discussed. Illustrated with detailed figures and supported by practical examples, this book is an indispensable guide for all those involved with the identification, extraction and application of active agents from natural products. 
650 0 |a Botanical chemistry  |x Data processing. 
650 6 |a Chimie v�eg�etale  |0 (CaQQLa)201-0004280  |x Informatique.  |0 (CaQQLa)201-0380011 
650 7 |a SCIENCE  |x Life Sciences  |x Biochemistry.  |2 bisacsh 
700 1 |a Sarker, Satyajit D.,  |e editor. 
700 1 |a Nahar, Lutfun,  |d 1969-  |e editor. 
776 0 8 |i Print version:  |t Computational phytochemistry.  |b First edition.  |d Amsterdam, Netherlands : Elsevier, [2018]  |z 0128123648  |z 9780128123645  |w (OCoLC)1013736077 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128123645  |z Texto completo