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Upgrading Affinity Screening Experiments by Analysis of Next-Generation Sequencing Data.

Christian Grohmann1, Michael Blank2

  • 1AptaIT GmbH, Am Klopferspitz 19a, 82152, Planegg-Martinsried, Germany.

Methods in Molecular Biology (Clifton, N.J.)
|November 9, 2017
PubMed
Summary
This summary is machine-generated.

Computational analysis of next-generation sequencing (NGS) data enhances ligand identification from biopanning experiments. This approach improves the discovery of peptides and antibodies with specific binding properties.

Keywords:
BioinformaticsBiopanningIn silico analysisIn vitro selectionNGSNext-generation sequencing

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Area of Science:

  • Biotechnology
  • Bioinformatics
  • Molecular Biology

Background:

  • Affinity screening methods like biopanning identify ligands with desired properties.
  • Analyzing selection data computationally offers deeper insights than traditional methods.

Purpose of the Study:

  • To present a concept for identifying relevant ligands using next-generation sequencing (NGS) data.
  • To demonstrate how NGS data can be structured for both single-round and comparative analyses.
  • To introduce the AptaAnalyzer tool for accessible computational ligand identification.

Main Methods:

  • Leveraging computational analysis of NGS data from affinity screening.
  • Structuring NGS data for single-round analysis to identify ligands.
  • Structuring NGS data for comparative analysis across multiple selection rounds.

Main Results:

  • Computational analysis of NGS data significantly deepens the understanding of affinity screening outcomes.
  • Improved identification of peptide and antibody ligands with specific binding or functional properties.
  • Comparative analysis of multiple selection rounds opens new possibilities in ligand discovery.

Conclusions:

  • Computational analysis of NGS data is a powerful approach for ligand identification in biopanning.
  • The AptaAnalyzer tool makes advanced computational methods accessible to a wider scientific audience.
  • This strategy enhances the efficiency and depth of ligand discovery for various applications.