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Predicting allosteric pockets in protein biological assemblages.

Ambuj Kumar1,2, Burak T Kaynak3,4, Karin S Dorman1,5

  • 1Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, United States.

Bioinformatics (Oxford, England)
|April 28, 2023
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Summary
This summary is machine-generated.

A new method, APOP, identifies allosteric pockets in proteins by simulating ligand binding effects. This tool accurately predicts known pockets and discovers novel ones, aiding in understanding protein dynamics.

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Area of Science:

  • Protein dynamics
  • Allosteric regulation
  • Computational biology

Background:

  • Allostery is a key mechanism for regulating protein function through distant conformational changes.
  • Predicting allosteric sites is crucial for drug discovery and understanding protein mechanisms.

Purpose of the Study:

  • To introduce APOP, a novel computational method for predicting allosteric pockets.
  • To evaluate APOP's accuracy and its ability to identify new allosteric sites.

Main Methods:

  • APOP emulates ligand binding by stiffening pairwise interactions within potential pockets in an elastic network model.
  • Pockets are ranked based on shifts in global mode frequencies and local hydrophobicity.

Main Results:

  • APOP achieved high prediction success, identifying 92 out of 104 known allosteric pockets within the top 3 ranks.
  • The method successfully identified novel allosteric pockets, including large central pockets in protein assemblies.

Conclusions:

  • APOP is an effective tool for predicting allosteric pockets in proteins.
  • The discovered pockets suggest new strategies for modulating protein dynamics and function.