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Enveloping triangulation method for detecting internal cavities in proteins and algorithm for computing their surface

Ján Busa¹, Shura Hayryan, Chin-Kun Hu

¹Institute of Physics, Academia Sinica, Nankang, Taipei 11529, Taiwan.

Journal of Computational Chemistry

|July 17, 2008

Summary

This study introduces a new method for detecting and measuring internal protein cavities, offering reliable calculations of their volumes and surface areas. The CAVE package provides accurate characterization of these protein structures.

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Area of Science:

Structural biology
Computational biophysics
Protein science

Background:

Internal cavities in proteins are crucial for structure-function relationships.
Accurate detection and quantification of these cavities are essential.
Existing methods may have limitations in characterizing protein interiors.

Purpose of the Study:

To develop a novel analytical method for detecting protein cavities.
To create an algorithm and software package (CAVE) for computing cavity volumes and surface areas.
To validate the reliability and accuracy of the new method.

Main Methods:

Constructing a special enveloping triangulation to enclose protein cavities.
Developing a Fortran package named CAVE for computational analysis.
Testing the method with artificial systems of spheres and real protein structures from the Protein Data Bank.

Main Results:

The method accurately detects and quantifies internal cavities in proteins.
Calculated volumes and surface areas show consistency with exact results in artificial systems.
Comparison with other methods confirms the reliability of the CAVE package.

Conclusions:

The proposed method and CAVE package provide a reliable approach for characterizing protein internal cavities.
This tool aids in understanding protein structure and function through detailed cavity analysis.
The findings contribute to advancements in computational structural biology.