Computer-Aided and Machine Learning-Driven Drug Design : From Theory to Applications / edited by Vinícius Gonçalves Maltarollo.

Format:

Book

Author/Creator:

Maltarollo, Vinícius Gonçalves.

Contributor:

Maltarollo

Series:

Computer-Aided Drug Discovery and Design, 2730-5465 ; 3

Language:

English

Subjects (All):

Drug delivery systems.

Machine learning.

Drugs--Design.

Drugs.

Artificial intelligence.

Computer simulation.

Drug Delivery.

Machine Learning.

Structure-Based Drug Design.

Artificial Intelligence.

Computer Modelling.

Local Subjects:

Drug Delivery.

Machine Learning.

Structure-Based Drug Design.

Artificial Intelligence.

Computer Modelling.

Physical Description:

1 online resource (761 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

The computer-aided drug design research field comprises several different knowledge areas, and often, researchers are only familiar or experienced with a small fraction of them. Indeed, pharmaceutical industries and large academic groups rely on a broad range of professionals, including chemists, biologists, pharmacists, and computer scientists. In this sense, it is difficult to be an expert in every single CADD approach. Furthermore, there are well-established methods that are constantly revisited, and novel approaches are introduced, such as machine-learning based scoring functions for molecular docking. This book provides an organized update of the most commonly employed CADD techniques, as well as successful examples of actual applications to develop bioactive compounds/drug candidates. Also includes is a section of case studies that cover certain pharmacological/target classes, focusing on the applications of the previously described methods. This part will especially appeal to professionals who are not as interested in the theoretical aspects of CADD. This is an ideal book for students, researchers, and industry professionals in the fields of pharmacy, chemistry, biology, bioinformatics, computer sciences, and medicine who are seeking a go-to reference on drug design and medicinal chemistry.

Contents:

Echoes from the past, visions from the future: a journey into the Medicinal Chemistry and the Computational Drug Discovery

Molecular Databases

A Brief Introduction to Pharmacogenomics and Personalized Medicine in the Drug Design Context

Machine Learning and Neural Networks Methods Applied to Drug Discovery

Clustering of Small Molecules

QSAR and Machine learning predictors

Molecular docking: state-of-art scoring functions and search algorithms

Drug Design in Motion: concepts and applications of classical Molecular Dynamics simulations

Conformational sampling of proteins: methods for simulate protein plasticity and ensemble docking

Free energy perturbation and free energy calculations ap-plied to drug design

Ultra-large-scale Virtual Screening

Experimental assays: chemical properties, biochemical and cellular assays, and in vivo evaluations

Challenges faced in the development of computational methods for predicting pharmacokinetics behavior

Exploring the Significance of Experimental and Computational Methods in Protein Structure Determination

Molecular modeling strategies in drug design, development, and discovery targeting proteases

Computational study of conformational changes in nuclear receptors upon ligand binding

An Overview on Computational Methods Targeting the Endocannabinoid System

Kinase Inhibitors and Computer-aided Drug Design Methods

Prediction of Drug Metabolism with In Silico Models: A Case Study of Doping Detection.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031767180

3031767187

OCLC:

1505736705