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CADD and Informatics in Drug Discovery

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

13.05.2023

Abbildungen

IX, 366 p. 1 illus.

Herausgeber

Mithun Rudrapal + weitere

Verlag

Springer Singapore

Seitenzahl

366

Maße (L/B/H)

24,1/16/2,6 cm

Gewicht

677 g

Auflage

2023

Sprache

Englisch

ISBN

978-981-9913-15-2

Beschreibung

Portrait


Mithun Rudrapal, PhD, FIC, CChem, is Associate Professor at the Department of Pharmaceutical Sciences, School of Biotechnology & Pharmaceutical Sciences, Vignan’s Foundation for Science, Technology and Research (Deemed to be University) Guntur, India. Dr. Rudrapal has been actively engaged in teaching and research the field of Pharmaceutical and Allied Sciences for more than 12 years. He has over a hundred publications in peer-reviewed international journals to his credit and has filed a number Indian and International patents. In addition, Dr. Rudrapal is the author of dozen published or forthcoming books. Dr. Rudrapal works in the areas of Medicinal Chemistry, CADD, Drug Repurposing, Phytochemistry, Herbal Drugs and Nanophytotherapeutics.

Dr. Johra KhanDepartment of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University  

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

13.05.2023

Abbildungen

IX, 366 p. 1 illus.

Herausgeber

Verlag

Springer Singapore

Seitenzahl

366

Maße (L/B/H)

24,1/16/2,6 cm

Gewicht

677 g

Auflage

2023

Sprache

Englisch

ISBN

978-981-9913-15-2

Herstelleradresse

Springer-Verlag GmbH
Europaplatz 3
69115 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: CADD and Informatics in Drug Discovery
  • Produktbild: CADD and Informatics in Drug Discovery

  • Chapter 1: Fundamentals of Computational Drug Design Approaches (CADD).- Chapter 2: Molecular and Computational Modeling in Drug Design.- Chapter 3: Bioinformatics/Chemo-informatics Tools and Database in Drug Discovery.- Chapter 4: Computational Screening of Phytochemicals/Natural Products in Drug Discovery.- Chapter 5: Virtual Screening in Lead Discovery and Optimization.- Chapter 6: Target-based Screening (SBDD) in Lead Discovery.- Chapter 7: Pharmacophore-based and Similarity Search (LBDD) Screening in Lead Discovery.- Chapter 8: Receptor-based De Novo and Fragment-based Drug Design.- Chapter 9: Artificial Intelligence and Machine Learning in Drug Discovery.- Chapter 10: Network Pharmacology and System Biology Approaches.- Chapter 11: In Silico Pharmacology and Drug Repurposing Approaches.- Chapter 12: Advances in Bioinformatics and Computational Approaches in Drug Discovery.- Chapter 13: Challenges in Bioinformatics and Computational Approaches in Drug Discovery.