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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Protein Organization01:24

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.
Protein Folding01:22

Protein Folding

Overview
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
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Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

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Related Experiment Video

Updated: Jun 15, 2026

High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography
06:19

High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography

Published on: March 10, 2023

Predicting protein crystallization propensity from protein sequence.

György Babnigg1, Andrzej Joachimiak

  • 1Midwest Center for Structural Genomics, Biosciences Division, Argonne National Laboratory, 9700 S Cass Ave., Argonne, IL 60439, USA. gbabnigg@anl.gov

Journal of Structural and Functional Genomics
|February 24, 2010
PubMed
Summary

Predicting protein crystallization is crucial for structural biology. This study identifies key protein properties that correlate with successful X-ray structure determination, aiding in the selection of targets for structural genomics.

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Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • High-throughput structural genomics pipelines generate vast datasets.
  • Understanding factors influencing protein crystallization is essential for structure determination.

Purpose of the Study:

  • To identify protein sequence-derived properties correlating with X-ray crystallizability.
  • To develop a predictive model for protein crystallization propensity.

Main Methods:

  • Computed protein properties for over 2,000 proteins (insoluble and crystallized).
  • Analyzed correlations between iso-electric point, GRAVY score, and crystallizability.
  • Developed a Support Vector Machine (SVM) classifier based on identified attributes.

Main Results:

  • Identified specific protein attributes that correlate with crystallization success.
  • Developed a functional SVM classifier for predicting crystallization propensity.
  • Created web-based tools for analyzing and visualizing predictive data.

Conclusions:

  • Protein sequence properties can predict the likelihood of obtaining X-ray quality crystals.
  • The developed SVM classifier and tools can aid in target selection for structural studies.
  • This approach enhances the efficiency of structural genomics efforts.