Chemoinformatics And Computational Chemical Biology
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Chemoinformatics and Computational Chemical Biology
Over the past years, the chem(o)informatics field has further evolved and new application areas have opened up, for example, in the broadly defined area of chemical biology. In Chemoinformatics and Computational Chemical Biology, leading investigators bring together a detailed series of reviews and methods including, among others, system-directed approaches using small molecules, the design of target-focused compound libraries, the study of molecular selectivity, and the systematic analysis of target-ligand interactions. Furthermore, the book delves into similarity methods, machine learning, probabilistic approaches, fragment-based methods, as well as topics that go beyond the current chemoinformatics spectrum, such as knowledge-based modeling of G protein-coupled receptor structures and computational design of siRNA libraries. As a volume in the highly successful Methods in Molecular BiologyTM series, this collection provides detailed descriptions and implementation advice that are exceedingly relevant for basic researchers and practitioners in this highly interdisciplinary research and development area. Cutting-edge and unambiguous, Chemoinformatics and Computational Chemical Biology serves as an ideal guide for experts and newcomers alike to this vital and dynamic field of study.
Cheminformatics and its Applications
Author: Amalia Stefaniu
language: en
Publisher: BoD – Books on Demand
Release Date: 2020-07-15
Cheminformatics has emerged as an applied branch of Chemistry that involves multidisciplinary knowledge, connecting related fields such as chemistry, computer science, biology, pharmacology, physics, and mathematical statistics.The book is organized in two sections, including multiple aspects related to advances in the development of informatic tools and their specific use in compound structure databases with various applications in life sciences, mainly in medicinal chemistry, for identification and development of new therapeutically active molecules. The book covers aspects related to genomic analysis, semantic similarity, chemometrics, pattern recognition techniques, chemical reactivity prediction, drug-likeness assessment, bioavailability, biological target recognition, machine-based drug discovery and design. Results from various computational tools and methods are discussed in the context of new compound design and development, sharing promising opportunities, and perspectives.
Chemoinformatics for Drug Discovery
Chemoinformatics strategies to improve drug discovery results With contributions from leading researchers in academia and the pharmaceutical industry as well as experts from the software industry, this book explains how chemoinformatics enhances drug discovery and pharmaceutical research efforts, describing what works and what doesn't. Strong emphasis is put on tested and proven practical applications, with plenty of case studies detailing the development and implementation of chemoinformatics methods to support successful drug discovery efforts. Many of these case studies depict groundbreaking collaborations between academia and the pharmaceutical industry. Chemoinformatics for Drug Discovery is logically organized, offering readers a solid base in methods and models and advancing to drug discovery applications and the design of chemoinformatics infrastructures. The book features 15 chapters, including: What are our models really telling us? A practical tutorial on avoiding common mistakes when building predictive models Exploration of structure-activity relationships and transfer of key elements in lead optimization Collaborations between academia and pharma Applications of chemoinformatics in pharmaceutical research experiences at large international pharmaceutical companies Lessons learned from 30 years of developing successful integrated chemoinformatic systems Throughout the book, the authors present chemoinformatics strategies and methods that have been proven to work in pharmaceutical research, offering insights culled from their own investigations. Each chapter is extensively referenced with citations to original research reports and reviews. Integrating chemistry, computer science, and drug discovery, Chemoinformatics for Drug Discovery encapsulates the field as it stands today and opens the door to further advances.