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Related Concept Videos

Deconvolution01:20

Deconvolution

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Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
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¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

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Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
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¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
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Extraction: Advanced Methods00:56

Extraction: Advanced Methods

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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
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Combining experimental strategies for successful target deconvolution.

Isabel V L Wilkinson1, Georg C Terstappen2, Angela J Russell3

  • 1Department of Chemistry, University of Oxford, Chemistry Research Laboratory, Mansfield Road, Oxford, OX1 3TA, UK.

Drug Discovery Today
|September 24, 2020
PubMed
Summary
This summary is machine-generated.

Target deconvolution is crucial for drug development. This study highlights how combining orthogonal approaches aids in identifying and validating drug targets, even beyond the proteome, for efficient drug discovery.

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Area of Science:

  • Pharmacology
  • Drug Discovery
  • Biochemistry

Background:

  • Phenotypic drug discovery necessitates efficient target deconvolution.
  • Current methods often yield lists of potential targets, complicating validation.
  • Validating therapeutic targets requires rigorous binding, engagement, and functional studies.

Purpose of the Study:

  • To address the challenge of target validation in drug development.
  • To explore methods for identifying and prioritizing drug targets.
  • To enable target identification beyond the proteome.

Main Methods:

  • Utilizing a combination of orthogonal approaches for target identification.
  • Employing techniques for target validation in relevant physiological contexts.
  • Integrating diverse methods to prioritize targets for further study.

Main Results:

  • Demonstrated the ability to identify targets beyond the proteome.
  • Showcased how orthogonal approaches facilitate target deconvolution.
  • Provided a framework for prioritizing targets for validation studies.

Conclusions:

  • Combining orthogonal methods is effective for target deconvolution in drug discovery.
  • This strategy aids in prioritizing targets for resource-intensive validation.
  • Successful drug development relies on robust target identification and validation.