ContinuousFlex

ContinuousFlex analyzes continuous conformational variability of macromolecules from cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) data to characterize dynamic molecular complexes.

Key Features:

• HEMNMA (Hybrid Electron Microscopy Normal Mode Analysis): Computes normal modes of a reference model (atomic structure or electron microscopy map) and applies these modes to single-particle images to determine the distribution of continuous conformational variability and, via iterative optimization, simultaneously estimate particle conformation, orientation, and shift.
• HEMNMA-3D: Extends HEMNMA for three-dimensional data analysis.
• TomoFlow: Analyzes tomographic (cryo-ET) data for conformational variability.
• NMMD (Normal Mode Molecular Dynamics): Applies normal mode–based molecular dynamics approaches to study conformational dynamics.
• StructMap: Provides published structural mapping methods within the package.
• Simulation and preprocessing tools: Simulates cryo-EM and cryo-ET datasets with conformational variability and provides preprocessing methods for experimental data.
• Integration with external software: Incorporates GENESIS for molecular dynamics simulation and ElNemo for normal mode analysis.
• DeepHEMNMA: Implements a deep learning extension of HEMNMA for analysis of conformational variability.
• Scipion integration: Operates as a plugin within the Scipion framework (V2.0).

Scientific Applications:

• Structural biology: Study dynamic molecular complexes by mapping continuous conformational variability.
• Mechanistic interpretation: Link conformational distributions to the functional mechanisms of macromolecules.
• Cryo-EM and cryo-ET data analysis: Extract conformational landscapes from single-particle images and tomographic datasets.

Methodology:

Computational methods explicitly include normal mode computation from atomic structures or EM maps, mode-based fitting to single-particle images, iterative optimization of conformation/orientation/shift, normal mode molecular dynamics (NMMD), HEMNMA-3D, TomoFlow, StructMap, simulation and preprocessing of cryo-EM/cryo-ET data, integration with GENESIS and ElNemo, and the deep-learning extension DeepHEMNMA.