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Cryo-electron Microscopy

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Updated: Jan 11, 2026

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

KNexPHENIX: A PHENIX-Based Workflow for Improving Cryo-EM and Crystallographic Structural Models.

Suparno Nandi¹, Graeme L Conn¹

¹Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA.

Biorxiv : the Preprint Server for Biology

|November 19, 2025

Summary

KNexPHENIX is a new workflow that improves macromolecular model building for cryo-electron microscopy (cryo-EM) and X-ray crystallography. It refines structures, yielding better stereochemistry and accuracy than standard methods.

Keywords:

PHENIX X-ray crystallography cryo-electron microscopy macromolecular model refinement structural biology

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Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

The Protein Data Bank (PDB) has seen exponential growth in deposited structures.
Refining atomic models from experimental maps is challenging due to limitations in current methods.
Standard PHENIX refinement is fast and accessible but may not produce optimal models.

Purpose of the Study:

To develop a customized, semi-automated workflow for optimal macromolecular model building.
To enhance the refinement of structures obtained from cryo-electron microscopy (cryo-EM) and X-ray crystallography.
To provide a practical and accessible approach for generating high-quality macromolecular models.

Main Methods:

Developed KNexPHENIX, a semi-automated PHENIX-based workflow.
Applied KNexPHENIX to refine structures from cryo-EM and X-ray crystallography.
Evaluated KNexPHENIX against standard PHENIX, REFMAC, and CERES using deposited and de novo models.

Main Results:

KNexPHENIX consistently produced models with lower MolProbity scores, indicating improved stereochemistry.
Model-to-map correlation was maintained for cryo-EM datasets.
Rfree-Rwork difference was maintained or reduced for X-ray crystallography, limiting overfitting.

Conclusions:

KNexPHENIX is a practical and accessible workflow for refining both cryo-EM and crystallographic structures.
The workflow enables the generation of models with enhanced quality metrics.
Improved models are suitable for deposition and can guide further experimental studies.