Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development (eBook, ePUB)

Redaktion: Roy, Kunal

• Format: ePub

Produktbeschreibung

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book. The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates.

• Presents chemometrics, cheminformatics and machine learning methods under a single reference
• Showcases the different structure-based, ligand-based and machine learning tools currently used in drug design
• Highlights special topics of computational drug design and available tools and databases

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 768
• Erscheinungstermin: 23. Mai 2023
• Englisch
• ISBN-13: 9780443186394
• Artikelnr.: 68118542

Inhaltsangabe

Section I: Introduction 1. Quantitative structure-activity relationships
(QSARs) in medicinal chemistry 2. Computer-aided Drug Design - An overview
3. Structure-based virtual screening in Drug Discovery 4. The impact of
Artificial Intelligence methods on drug design
Section 2. Methods and Case studies 5. Graph Machine Learning in Drug
Discovery 6. Support Vector Machine in Drug Design 7. Understanding
protein-ligand interactions using state-of-the-art computer simulation
methods 8. Structure-based methods in drug design 9. Structure-based
virtual screening 10. Deep learning in drug design 11. Computational
methods in the analysis of viral-host interactions 12. Chemical space and
Molecular Descriptors for QSAR studies 13. Machine learning methods in drug
design 14. Deep learning methodologies in drug design 15. Molecular
dynamics in predicting stability of drug receptor interactions
Section 3. Special topics 16. Towards models for bioaccumulation suitable
for the pharmaceutical domain 17. Machine Learning as a Modeling Approach
for the Account of Nonlinear Information in MIA-QSAR Applications: A Case
Study with SVM Applied to Antimalarial (Aza)aurones 18. Deep Learning using
molecular image of chemical structure 19. Recent Advances in Deep Learning
Enabled Approaches for Identification of Molecules of Therapeutics
Relevance 20. Computational toxicology of pharmaceuticals 21.
Ecotoxicological QSAR modelling of pharmaceuticals 22. Computational
modelling of drugs for neglected diseases 23. Modelling ADMET properties
based on Biomimetic Chromatographic Data 24. A systematic chemoinformatic
analysis of chemical space, scaffolds and antimicrobial activity of LpxC
inhibitors
Section 4. Tools and databases 25. Tools and Software for Computer Aided
Drug Design and Discovery 26. Machine learning resources for drug design
27. Building Bioinformatics Web Applications with Streamlit 28. Free tools
and databases in ligand and structure-based drug design