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Related Concept Videos

Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
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Applications Of NMR In Biology01:25

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Nuclear magnetic resonance (NMR) spectroscopy is a very valuable analytical technique for researchers. It has been used for more than 50 years as an analytical tool. F. Bloch and E. Purcell formulated NMR in 1946 and won the 1952 Nobel Prize in Physics  for their work. Biological macromolecules such as proteins, nucleic acids, lipids, and organic molecules including pharmaceutical compounds, can be studied using this versatile tool that exploits the magnetic properties of certain nuclei.
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Nuclear Magnetic Resonance (NMR): Overview01:07

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Nuclear magnetic resonance (NMR) is a phenomenon exhibited by certain nuclei that can absorb characteristic radio frequency radiation under certain conditions. NMR has been extensively applied in molecular spectroscopy and medical diagnostic imaging. In both these applications, the molecule or subject under study is placed in a magnetic field and irradiated with radio frequency energy.
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Drug Discovery: Overview01:26

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Drug-Receptor Bonds01:25

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Drug-receptor bonds are formed through various chemical forces when drugs interact with target cells. Covalent bonds, strong and irreversible, are exemplified by DNA-alkylating anticancer agents that inhibit cell division. However, such irreversible drug binding lacks selectivity and can modify the DNA of the surrounding healthy cells. Covalent binding often contributes to tissue toxicity, as seen with chloroform and paracetamol metabolites binding to the liver, causing hepatotoxicity.
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Adrenergic Agonists: Chemistry and Structure-Activity Relationship01:16

Adrenergic Agonists: Chemistry and Structure-Activity Relationship

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Adrenergic agonists' structure-activity relationship (SAR) determines their selectivity and efficacy. These agonists comprise a phenylethylamine moiety with an aromatic ring and an ethylamine side chain.
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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
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NMR in structure-based drug design.

Marta G Carneiro1, Eiso Ab1, Stephan Theisgen1

  • 1ZoBio, J.H. Oortweg 19, 2333CH Leiden, The Netherlands.

Essays in Biochemistry
|November 10, 2017
PubMed
Summary
This summary is machine-generated.

Nuclear Magnetic Resonance (NMR) spectroscopy offers crucial structural insights for drug discovery. This review covers NMR applications, paramagnetic NMR, and automation advancements for faster drug development.

Keywords:
Drug DiscoveryNMR spectroscopystructural biology

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Medicinal Chemistry

Background:

  • Nuclear Magnetic Resonance (NMR) spectroscopy is a key technique for determining molecular structures.
  • Structural information is vital for structure-based drug discovery (SBDD).

Purpose of the Study:

  • To review the strengths and limitations of NMR applications in drug discovery.
  • To highlight different resolution and throughput levels achievable with NMR.
  • To discuss emerging paramagnetic NMR techniques and automation in data processing.

Main Methods:

  • Review of existing literature on NMR spectroscopy in drug discovery.
  • Discussion of various NMR techniques, including paramagnetic NMR.
  • Exploration of automated data collection and analysis methods for protein-observed NMR.

Main Results:

  • NMR provides valuable structural data for drug discovery with varying resolution and throughput.
  • Paramagnetic NMR offers unique insights for drug discovery applications.
  • Automation significantly speeds up and streamlines protein-observed NMR data handling.

Conclusions:

  • NMR spectroscopy remains a powerful tool in structure-based drug discovery.
  • Emerging techniques and automation are enhancing NMR's utility and efficiency.
  • Continued development in NMR promises further advancements in drug development pipelines.