Computational Drug Discovery and Design

Mohini Gore, Umesh B. Jagtap (Herausgeber)

Buch | Softcover

356 Seiten

2024 | Second Edition 2024
Springer-Verlag New York Inc.
978-1-0716-3443-1 (ISBN)

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This second edition provides new and updated methods and techniques for identification of drug target, binding sites prediction, high- throughput virtual screening, lead discovery and optimization, conformational sampling, prediction of pharmacokinetic properties using computer-based methodologies. Chapters also focus on the application of the latest artificial intelligence technologies for computer aided drug discovery. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.

Authoritative and cutting-edge, Computational Drug Discovery and Design, Second Edition aims to effectively utilize computational methodologies in discovery and design of novel drugs.

Computer-Aided Drug Discovery and Design – Recent Advances and Future Prospects.- Virtual Screening Process - A Guide in Modern Drug Designing.- Molecular dynamics as a tool for virtual ligand screening.- Antiviral Drug Target Identification and Ligand Discovery.- GRAMM webserver for protein docking.- Protein–ligand blind docking using CB-Dock2.- Applications of Molecular Dynamics Simulations in Drug Discovery.- Molecular dynamics simulation-based prediction of glycosaminoglycan interactions with drug molecules.- Mining chemogenomic spaces for prediction of drug-target interactions.- Expanding the landscape of amyloid sequences with CARs-DB: a database of polar amyloidogenic peptides from disordered proteins.- Accelerating molecular dynamics simulations for drug discovery.- Exploring the Role of Chemoinformatics in Accelerating Drug Discovery: A Computational Approach. -Recent Deep-Learning Applications to Structure-BasedDrug Design.- Techniques for Developing Reliable Machine Learning Classifiers Applied to Understanding and Predicting Protein:Protein Interaction Hot Spots.- AI driven enhancements in drug screening and optimisation.- Applications of big data and AI-driven technologies in CADD (computer-aided drug design).- Artificial Intelligence in ADME Property Prediction.- Accelerating the discovery and design of antimicrobial peptides with artificial intelligence.

Erscheinungsdatum	21.09.2024
Reihe/Serie	Methods in Molecular Biology
Zusatzinfo	1 Illustrations, black and white; XI, 356 p. 1 illus.
Verlagsort	New York, NY
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Informatik ► Weitere Themen ► Bioinformatik
	Medizin / Pharmazie ► Medizinische Fachgebiete ► Pharmakologie / Pharmakotherapie
	Medizin / Pharmazie ► Pharmazie
	Naturwissenschaften ► Chemie ► Physikalische Chemie
Schlagworte	Chemoinformatics • computer-aided drug design • Drug target identification • Lead discovery and optimization • machine learning • Pharmacokinetics
ISBN-10	1-0716-3443-7 / 1071634437
ISBN-13	978-1-0716-3443-1 / 9781071634431
Zustand	Neuware