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Merging conformational landscapes in a single consensus space with FlexConsensus algorithm.

David Herreros1, Carlos Perez Mata2, Carlos Oscar Sanchez Sorzano3

  • 1Centro Nacional de Biotecnologia-CSIC, Madrid, Spain. dherreros@cnb.csic.es.

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|September 25, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

FlexConsenus integrates multiple structural heterogeneity algorithms in cryo-EM, creating a reliable consensus space. This approach enhances the accuracy and interpretability of protein conformational landscapes from experimental data.

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Area of Science:

  • Structural Biology
  • Biophysics
  • Computational Biology

Background:

  • Cryo-electron microscopy (cryo-EM) structural heterogeneity analysis is advancing, enabling more accurate conformational landscape estimations.
  • New methods aim to improve understanding of protein dynamics, but direct comparison of heterogeneity algorithms is lacking.
  • Assessing algorithm reliability is crucial for validating conformational landscape interpretations.

Purpose of the Study:

  • To develop a method for comparing and integrating different structural heterogeneity algorithms in cryo-EM.
  • To create a shared consensus space for multiple conformational landscapes.
  • To enhance the reliability and interpretability of cryo-EM derived structural variability.

Main Methods:

  • Introduction of FlexConsenus, a multi-autoencoder neural network.
  • Learning commonalities and differences among various conformational landscapes.
  • Mapping multiple landscapes into a unified consensus space.

    • Main Results:

    • FlexConsenus successfully integrates diverse conformational landscapes into a reliable consensus space.
    • The consensus space allows for the measurement of reproducibility in heterogeneity estimations.
    • Enables focused analysis on stable structural variability or method-specific particle subsets.

    Conclusions:

    • FlexConsenus provides a robust framework for comparing and consolidating structural heterogeneity analyses in cryo-EM.
    • Facilitates more reliable interpretation of protein conformational dynamics.
    • Improves the overall accuracy and trustworthiness of cryo-EM structural studies.