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Predicting ion mobility collision cross sections using projection approximation with ROSIE-PARCS webserver.

S M Bargeen Alam Turzo1, Justin T Seffernick1, Sergey Lyskov2

  • 1Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH 43210, USA.

Briefings in Bioinformatics
|August 23, 2023
PubMed
Summary
This summary is machine-generated.

We developed ROSIE-PARCS, a user-friendly web tool for predicting protein collision cross sections (CCSIM) from structures. This tool accurately estimates protein size and shape, aiding in the assessment of protein structure prediction models like AlphaFold2.

Keywords:
AlphaFold2collision cross sectionion mobilitymass spectrometryprotein structure predictionwebserver

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Area of Science:

  • Structural biology
  • Computational chemistry
  • Biophysics

Background:

  • Ion mobility-mass spectrometry provides insights into protein structure, specifically collision cross section (CCSIM).
  • Existing computational methods for CCSIM prediction often require command-line expertise.
  • The Projection Approximation with Rough Circular Shapes (PARCS) is a computational method for CCSIM prediction.

Purpose of the Study:

  • To present a user-friendly web application for predicting CCSIM from protein structures.
  • To simplify the application of the PARCS method for a wider scientific audience.
  • To evaluate the accuracy of the new web application and its utility in assessing protein structure predictions.

Main Methods:

  • Development of a web application integrated into the Rosetta Online Server that Includes Everyone (ROSIE) webserver.
  • Inputting protein structures via PDB files into the ROSIE-PARCS web interface.
  • Utilizing the PARCS algorithm within the web application for CCSIM prediction.

Main Results:

  • The ROSIE-PARCS web application provides highly accurate CCSIM predictions with an average error of 6.12%.
  • The difference between experimental CCSIM and predicted CCSPARCS can differentiate accurate from inaccurate AlphaFold2 structure predictions.
  • The web interface is publicly accessible, free to use, and supports all major web browsers.

Conclusions:

  • ROSIE-PARCS offers a simplified and accurate method for predicting protein CCSIM.
  • This tool enhances the accessibility of computational structure analysis for researchers.
  • ROSIE-PARCS serves as a valuable tool for validating protein structure models, including those from AlphaFold2.