Computational Drug Discovery, 2 Volumes: Methods and Applications

Computational Drug Discovery is a comprehensive resource that explains a wide array of computational technologies and methods driving innovation in drug discovery. It covers recent advances, particularly focusing on artificial intelligence (AI) and its application for protein structure prediction, AI-enabled virtual screening, and generative modeling for compound design. It also covers key technological advancements in computing such as quantum and cloud computing. The book is organized into eight thematic sections, each focusing on a specific computational method or technology applied to drug discovery. It is authored by renowned experts from academia, the pharmaceutical industry, and major drug discovery software providers and offers an overview of the latest advances in computational drug discovery.

Format: Hardback
Length: 736 pages
Publication date: 21 February 2024
Publisher: Wiley-VCH Verlag GmbH

Computational Drug Discovery is a comprehensive resource that delves into the cutting-edge technologies and methods driving innovation in the field of drug discovery. This two-volume set presents a wide range of computational technologies and computational chemistry methods that are revolutionizing the drug discovery process.

The book explores recent advancements, particularly in artificial intelligence (AI), which is being utilized for protein structure prediction, AI-enabled virtual screening, and generative modeling for compound design. It also covers key technological advancements in computing, such as quantum and cloud computing, which are propelling innovations in drug discovery.

Furthermore, dedicated chapters address the recent trends in computer-aided drug design, including ultra-large-scale virtual screening for hit identification, computational strategies for designing new therapeutic modalities like PROTACs and covalent inhibitors that target residues beyond cysteine, and the use of molecular dynamics and other related methods.

To provide the most up-to-date information on computational methods employed in Computational Drug Discovery, the book covers chapters highlighting the use of molecular dynamics and other related methods, application of quantum mechanics (QM) and quantum mechanics/molecular mechanics (QM/MM) methods in computational drug design, and techniques for navigating and visualizing the chemical space. Additionally, it explores the use of big data to drive drug discovery efforts.

The book is thoughtfully organized into eight thematic sections, each focusing on a specific computational method or technology applied to drug discovery. Authored by renowned experts from academia, the pharmaceutical industry, and major drug discovery software providers, it offers an overview of the latest advancements in the field.

Computational Drug Discovery is a valuable resource for researchers, scientists, and professionals involved in drug discovery, providing them with a comprehensive understanding of the latest technologies and methods driving innovation in this critical field.

Weight: 1701g
Dimension: 244 x 170 x 47 (mm)
ISBN-13: 9783527351664