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αCharges: partial atomic charges for AlphaFold structures in high quality.

Ondřej Schindler1,2, Karel Berka3, Alessio Cantara1,2

  • 1CEITEC - Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic.

Nucleic Acids Research
|May 9, 2023
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Summary

We developed αCharges, a web tool providing partial atomic charges for over 200 million protein structures in AlphaFoldDB. This enhances functional annotation for predicted protein structures, aiding chemical behavior analysis.

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Area of Science:

  • Structural biology
  • Computational chemistry
  • Bioinformatics

Background:

  • AlphaFold2 has generated millions of protein structure predictions, available in AlphaFoldDB.
  • These structures lack detailed functional annotations, such as partial atomic charges, which are crucial for understanding chemical reactivity.
  • Existing methods for charge calculation are not optimized for the scale of AlphaFoldDB data.

Purpose of the Study:

  • To introduce αCharges, a web application for calculating partial atomic charges for AlphaFoldDB protein structures.
  • To provide essential chemical behavior data for large-scale predicted protein structures.
  • To facilitate the use of predicted protein structures in downstream chemical and biological analyses.

Main Methods:

  • Developed the αCharges web application.
  • Employed the SQE+qp empirical method for charge calculation.
  • Utilized quantum mechanics (B3LYP/6-31G*/NPA) derived charges on PROPKA3 protonated structures for parameterization.
  • Integrated with the Mol* viewer for visualization and common data formats for download.

Main Results:

  • Successfully calculated partial atomic charges for millions of protein structures from AlphaFoldDB.
  • Provided a user-friendly web interface for accessing and visualizing charge data.
  • Enabled download of charge data in standard formats.

Conclusions:

  • αCharges significantly enhances the functional annotation of predicted protein structures.
  • The tool democratizes access to crucial chemical information for large protein structure datasets.
  • αCharges will aid research in protein function, drug design, and chemical biology.