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Biophysical and Computational Tools in Drug Discovery

Om Biophysical and Computational Tools in Drug Discovery

This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals frompharmaceutical industry interested in drug design and discovery.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9783030852832
  • Bindende:
  • Paperback
  • Sider:
  • 412
  • Utgitt:
  • 20. oktober 2022
  • Utgave:
  • 22001
  • Dimensjoner:
  • 155x23x235 mm.
  • Vekt:
  • 622 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 15. desember 2024

Beskrivelse av Biophysical and Computational Tools in Drug Discovery

This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals frompharmaceutical industry interested in drug design and discovery.

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