CHOYCE: a web server for constrained homology modelling with cryoEM maps.

Area of Science:

• Structural biology
• Biophysics
• Computational biology

Background:

• Cryo electron microscopy (cryoEM) is a powerful technique for determining the structure of biological macromolecules.
• Homology modeling is crucial for building atomic models of proteins when experimental structures are unavailable.
• Integrating computational modeling with experimental data, like cryoEM maps, is essential for accurate structural determination.

Purpose of the Study:

• To present CHOYCE, a novel web server designed for homology modeling of protein components.
• To facilitate the fitting of these modeled components into cryo electron microscopy (cryoEM) density maps.
• To provide an interactive platform for refining model selection based on fit quality.

Main Methods:

• Development of a web server integrating homology modeling algorithms.
• Implementation of algorithms for fitting protein models into cryoEM maps.
• Creation of an interactive user interface for model evaluation and selection.

Main Results:

• CHOYCE enables users to generate homology models for protein components.
• The server allows for the precise fitting of these models into experimental cryoEM maps.
• An interactive approach aids in assessing and improving the quality of model-map fits.

Conclusions:

• CHOYCE serves as a valuable tool for structural biologists working with cryoEM data.
• The web server streamlines the process of homology modeling and model fitting.
• Interactive model selection improves the accuracy and reliability of structural models derived from cryoEM.