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Current Concepts in Drug Design - Librerie.coop

Current Concepts in Drug Design

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€ 92,99
Dettagli
FORMATO epub
EDITORE BSP BOOKS
EAN 9789388305211
ANNO PUBBLICAZIONE 2020
CATEGORIA Medicina
LINGUA eng
Dispositivi supportati
Computer
E-Readers
iPhone/iPad
Androids
Kindle
Kobo

Descrizione

The newer research areas in pharmaceutical sciences, in particular molecular modeling and simulations prompted more efficient drug discovery process. Informatics integrated with pharmaceutical sciences (cheminformatics and bioinformatics) became an essential component of drug research. Drug informatics such as genomics and proteomics assists in the Rational Drug Design (RDD). This emerging discipline is known as “Computer-Aided Drug Design (CADD)”, which has profound application in rational drug design (RDD). Pharmacy Council of India (PCI), New Delhi also introduced these concepts into the curriculum of pharmacy graduate courses. The advanced and adequate practice in drug design informatics is essential for pharmacy graduates (B. Pharmacy and M. Pharmacy). Hence, a companion for acquiring the knowledge on these concepts is essential. With this intension, the author has taken an attempt to bring this book. The students of B. Pharmacy, M. Pharmacy (Pharmaceutical Chemistry, Pharmacology, and Pharmaceutics), bio-technology, biomedical engineering and other interdisciplinary fields may find this book as reference guide. The salient features of this book are: • Systematic and simple approach • Emphasis on traditional and modern drug design strategies • Comprehensive coverage for the current advances in the drug design • Experimental section to ensure hands-on-experience
Contents: 


1. Drug Discovery Informatics 
2. Receptors
3. Molecular Biology 
4. Drug Discovery and Development 
5. Quantitative –Structure Activity Relationship (QSAR) 
6. Molecular Modeling 
7. Virtual Screening 
8. Molecular Docking 
9. Sequence Analysis 
10. Pairwise Sequence Alignment (PSA) 
11. Molecular Evolution, Multiple Sequence Alignment (MSA) and Phylogenetic Analysis
12. Gene Prediction, Hidden Markov Model and Motif Identification 
13. Structure Prediction
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