By Gisbert Schneider
ISBN-10: 3527334610
ISBN-13: 9783527334612
ISBN-10: 3527677011
ISBN-13: 9783527677016
Systematically studying present equipment and techniques, this prepared reference covers a variety of molecular constructions, from organic-chemical medications to peptides, Proteins and nucleic acids, based on rising new drug periods derived from biomacromolecules.
A chief within the box and one of many pioneers of this younger self-discipline has assembled the following the main popular specialists from the world over to supply first-hand wisdom. whereas such a lot in their equipment and examples come from the world of pharmaceutical discovery and improvement, the methods are both appropriate for chemical probes and diagnostics, insecticides, and the other molecule designed to engage with a organic method. a variety of photographs and screenshots illustrate the various examples and process descriptions.
With its large and balanced assurance, this may be the firststop source not just for medicinal chemists, biochemists and biotechnologists, yet both for bioinformaticians and molecular designers for a few years to come.
From the content:
* Reaction-driven de novo design
* Adaptive equipment in molecular design
* layout of ligands opposed to multitarget profiles
* loose strength tools in ligand design
* Fragment-based de novo design
* computerized layout of targeted and objective family-oriented compound libraries
* Molecular de novo layout by way of nature-inspired computing
* 3D QSAR ways to de novo drug design
* Bioisosteres in de novo design
* De novo layout of peptides, proteins and nucleic acid constructions, together with RNA aptamers
and many more.
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Extra resources for De novo Molecular Design
Example text
Cell- and dissimilarity-based clustering and partitioning methods are often employed for this purpose. Diverse compound sets often represent reasonable starting points for screening campaigns, whereas focused libraries, in contrast, typically contain substances only from a certain region (activity island) of the chemical space. Generic filtering steps for drug- and lead-like compounds in conjunction with target-specific prediction and selection tools have been shown to be suited for designing activity-enriched focused libraries [47].
In fact, we will see later in several chapters of this book that such predictive functions may (i) either be developed from scratch (empirical or knowledge-based approach), provided that a sufficient number of accurate reference examples are available, or (ii) be derived from first principles (physically motivated approach). In general, we aim at designing noncovalent ligands, as the complex formation between drug molecules and their macromolecular targets is governed by noncovalent interactions.
17 Examples of ‘‘polypharmacological’’ fitness landscapes. Two such landscapes (b) resulted from combining different target-specific landscapes (a). The individual landscapes were modeled using activity data for selected GPCRs (CB2, cannabinoid receptor 2; 5HT2c, serotonin receptor 2c; A1, adenosine receptor 1; and beta2AR, beta-2 adrenergic receptor). Plus signs designate desired target activity (on-targets), and minus signs indicate off -targets. Arbitrary mixtures of activity landscapes are possible, so that the design tasks can be combined in a single fitness landscape.
De novo Molecular Design by Gisbert Schneider
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