Name: Current Trends in Computational Modeling for Drug Discovery (en Inglés)
SKU: 67317711
Price: 51.75 USD
Availability: InStock
Author: Supratik Kar;Jerzy Leszczynski

portada Current Trends in Computational Modeling for Drug Discovery (en Inglés)

Current Trends in Computational Modeling for Drug Discovery (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Supratik Kar;Jerzy Leszczynski

Año

2023

Idioma

Inglés

N° páginas

320

Encuadernación

Tapa Blanda

Dimensiones

23.4x15.6x1.7 cm

ISBN13

9783031338724

Current Trends in Computational Modeling for Drug Discovery (en Inglés)

Supratik Kar;Jerzy Leszczynski (Autor) · Springer · Tapa Blanda

Libro Nuevo Importado

Envío: 16 a 22 días háb.

$ 103.50$ 51.75

-50%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 50 unidades

$ 51.75

Llega entre el 15 Sep y el 25 Sep a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Current Trends in Computational Modeling for Drug Discovery (en Inglés)"

This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The different chapters deal with the classical and most advanced techniques, theories, protocols, databases, and tools employed in computer-aided drug design (CADD) covering diverse therapeutic classes. Multiple components of Structure-Based Drug Discovery (SBDD) along with its workflow and associated challenges are presented while potential leads for Alzheimer's disease (AD), antiviral agents, anti-human immunodeficiency virus (HIV) drugs, and leads for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) disease are discussed in detail. Computational toxicological aspects in drug design and discovery, screening adverse effects, and existing or future in silico tools are highlighted, while a novel in silico tool, RASAR, which can be a major technique for small to big datasets when not much experimental data are present, is presented. The book also introduces the reader to the major drug databases covering drug molecules, chemicals, therapeutic targets, metabolomics, and peptides, which are great resources for drug discovery employing drug repurposing, high throughput, and virtual screening. This volume is a great tool for graduates, researchers, academics, and industrial scientists working in the fields of cheminformatics, bioinformatics, computational biology, and chemistry.