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Multi-scale Approaches in Drug Discovery : From Empirical Knowledge to in Silico Experiments and Back
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Multi-Scale Approaches to Drug Discovery: From Empirical Knowledge to In Silico Experiments and Back furnishes chemists with the detail they need to identify drug leads with the highest potential before isolating and synthesizing them to produce effective drugs with greater swiftness than classical methods may allow. This significantly speeds up the search for more efficient therapeutic agents.
After an introduction to multiscale approaches that outline the need for, and benefits of, their use, the book goes on to explore a range of useful techniques, research areas, and their potential applications to this process. Activity cliffs in drug discovery, computational biology in drug discovery, and the use of a novel multitasking chemo-bioinformatic models to speed up the discovery of potent and safer antibacterial peptides are all discussed before the book goes on to review drug and gene delivery, Nano-QSAR in drug discovery, medicinal chemistry, computational approaches in peptide discovery, and the design of multi-target drugs/ligands against neurodegenerative disorders.<
A study in multitasking chemoinformatic models follows, with a further discussion of polypharmacology. Complex networks for analyzing and studying biochemical pathways, and in combination with QSAR approaches are then explored before the book concludes with a review of medicinal chemistry of therapeutic agents against neglected diseases and natural products as constant sources of efficient chemoth.
- Offers practical guidance on ways to implement multiscale approaches for increased efficiency in drug discovery
- Draws on the experience of a highly skilled team of authors under the editorial guidance of one of the field's leading experts
- Includes cutting-edge techniques at the forefront of medicinal chemistry and drug discovery optimization