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Related Concept Videos

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences01:20

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Inductively coupled plasma–mass spectrometry (ICP–MS) is a highly selective and sensitive technique for accurate elemental analysis. Though the analysis of ICP–MS mass spectra is comparatively straightforward, it is affected by spectroscopic and non-spectroscopic interferences. Spectroscopic interferences arise when the plasma contains ionic species with an m/z value the same as the analyte ion. Spectroscopic interference can be categorized as isobaric, polyatomic ions, and...
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Interference leads to systematic error in atomic absorption (AA) measurements by enhancing or diminishing the analytical signal or the background. These interferences can be grouped into three main categories: spectral interference, chemical interference, and physical interference.
Spectral interference occurs when signals from other elements or molecules overlap with the analyte signal, falsely elevating or masking the analyte's absorbance. This interference can be corrected using Zeeman,...
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Identification of Pan-Assay INterference compoundS (PAINS) Using an MD-Based Protocol.

Pedro R Magalhães1, Pedro B P S Reis1, Diogo Vila-Viçosa1

  • 1Faculty of Sciences, BioISI - Biosystems and Integrative Sciences Institute, University of Lisboa, Lisboa, Portugal.

Methods in Molecular Biology (Clifton, N.J.)
|July 24, 2021
PubMed
Summary

We developed a computational method to identify membrane Pan-Assay Interference Compounds (PAINS). This approach predicts how compounds affect lipid bilayers, aiding in the discovery of reliable drug candidates.

Keywords:
Molecular dynamicsPotential of mean forceUmbrella sampling

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Area of Science:

  • Biochemistry
  • Computational Chemistry
  • Pharmacology

Background:

  • Pan-Assay Interference Compounds (PAINS) are problematic in drug discovery.
  • Membrane PAINS specifically interfere with membrane protein assays by disrupting lipid bilayers.
  • Accurate identification of these compounds is crucial for reliable screening.

Purpose of the Study:

  • To present a novel computational protocol for identifying membrane PAINS.
  • To provide a tool for predicting compound-induced alterations in lipid bilayer properties.

Main Methods:

  • Calculation of bilayer deformation propensity for small molecules.
  • Utilizing computational simulations to assess membrane perturbation.
  • Developing a predictive model for membrane PAINS identification.

Main Results:

  • The protocol effectively quantifies the impact of compounds on membrane structure.
  • Identified key molecular features associated with membrane PAINS activity.
  • Demonstrated the utility of the method in flagging potential interferents.

Conclusions:

  • The developed computational protocol offers a promising approach to identify membrane PAINS.
  • This method can improve the efficiency and reliability of drug discovery screening.
  • Minimizing interference from membrane PAINS is essential for advancing membrane protein research.