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Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

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Related Experiment Video

Updated: May 6, 2026

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

Published on: January 10, 2018

Automatic protein structure solution from weak X-ray data.

Pavol Skubák¹, Navraj S Pannu

¹Department of Biophysical Structural Chemistry, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.

Nature Communications

|November 16, 2013

Summary

This summary is machine-generated.

A new multivariate algorithm automates protein structure determination from challenging X-ray data. This method successfully builds models where other algorithms fail, aiding researchers in structural biology.

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Last Updated: May 6, 2026

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

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Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Published on: November 5, 2018

Area of Science:

Structural biology
Biophysics
Computational biology

Background:

Determining protein structures from low-resolution X-ray diffraction data or weak anomalous signals is a significant challenge in structural biology.
Current algorithms often fail to build accurate models under these difficult conditions.

Purpose of the Study:

To develop a novel multivariate algorithm that integrates multiple structure determination steps.
To automate the process of protein structure determination, making it accessible to non-specialists.

Main Methods:

A multivariate algorithm was developed to simultaneously combine various steps of structure determination.
The algorithm was tested on over 140 real-world datasets from the Protein Data Bank.

Main Results:

The proposed algorithm successfully built models from datasets where existing methods failed.
Demonstrated success on a challenging 3.88 Å RNA polymerase II dataset with anisotropic diffraction.
The method automates the modeling process, reducing the need for specialized expertise.

Conclusions:

The developed multivariate algorithm offers a robust and automated solution for protein structure determination, particularly from low-resolution or weak anomalous signal data.
This approach provides a mathematical framework for integrating diverse information sources in image processing for structural biology.