| Edition |
2nd ed. |
| Description |
1 online resource (532 p.) |
| Note |
Description based upon print version of record. |
| Contents |
Intro -- Computational Phytochemistry -- Copyright -- Contents -- Contributors -- Preface to the first edition -- Preface to the second edition -- Chapter 1: Computational phytochemistry: An overview -- 1.1. Introduction -- 1.2. Computational phytochemistry -- 1.3. Techniques, theories and applications of computational phytochemistry -- 1.3.1. Kohonen-based self-organizing map (SOM) -- 1.3.2. Density functional theory (DFT) -- 1.3.3. Docking experiments and virtual screening (in silico screening) -- 1.3.4. Structure prediction and structure determination |
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1.3.5. Chemometrics and principal component analysis (PCA) -- 1.3.6. Data-mining and databases -- 1.3.7. Response surface methodology (RSM) in optimization of extraction of phytochemicals -- 1.3.8. Computation in isolation of phytochemicals -- 1.3.9. Predictive toxicology based on QSAR (quantitative structure-activity relationship) -- 1.3.10. Miscellaneous -- 1.4. Conclusions -- Acknowledgement -- References -- Chapter 2: Response surface methodology (RSM) in phytochemical research -- 2.1. Introduction -- 2.2. Generic steps in response surface methodology |
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2.3. Application of response surface methodology (RSM) in phytochemical research -- 2.3.1. Optimization of extraction of phytochemicals -- Accelerated solvent extraction (ASE) -- Maceration and refluxing -- Microwave-assisted extraction (MAE) -- Soxhlet extraction -- Ultrasound-assisted extraction (UAE) -- 2.3.2. Optimization of herbal formulations/products -- 2.3.3. Optimization of oil extraction from plants -- 2.3.4. Optimization of solid char yield and its caloric value -- 2.3.5. Optimization of antibiotics removal from the environment by plant extracts |
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2.3.6. Optimization of hydrothermal processing -- 2.3.7. Optimization of steel corrosion inhibition using plant materials -- 2.3.8. Optimization of biodiesel production -- 2.4. Conclusion -- Acknowledgement -- References -- Chapter 3: Prediction of medicinal properties using mathematical models and computation, and selection of plant materials -- 3.1. Introduction -- 3.2. Mathematical models -- 3.3. Computational models in drug discovery -- 3.3.1. Structure-based CADD -- 3.3.2. Ligand-based CADD -- 3.3.3. Network pharmacology -- 3.4. Selection of medicinal plants |
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3.4.1. Ethnobotany-directed drug discovery -- 3.4.2. Chemotaxonomic and ecological approach -- 3.4.3. Random approach -- 3.4.4. Integrated approach -- 3.5. Role of medicinal plant databases -- 3.6. Tools and techniques -- 3.7. Role of data mining in medicinal plant selection -- 3.8. Safety considerations -- 3.9. Conclusion -- Acknowledgement -- References -- Chapter 4: Optimization of extraction using mathematical models and computation -- 4.1. Introduction -- 4.2. Designs of experiment (DOE) -- 4.2.1. Planning phase -- 4.2.2. Designing phase -- 4.2.3. Screening phase |
| Note |
Central composite design (CCD) |
| Subject |
Botanical chemistry -- Data processing.
|
|
Chimie végétale -- Informatique.
|
| Added Author |
Sarker, Satyajit Dey.
|
|
Nahar, Lutfun.
|
| Other Form: |
Print version: Sarker, Satyajit Dey Computational Phytochemistry San Diego : Elsevier,c2024 9780443161025 |
| ISBN |
9780443161032 |
|
0443161038 |
|
9780443161025 |
| Standard No. |
AU@ 000076181508 |
|
