MolAxis: a server for identification of channels in macromolecules
Eitan Yaffe1, Dan Fishelovitch, Haim J Wolfson
1School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Department of Human Genetics, Sackler Institute of Molecular Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
Nucleic Acids Research
|May 2, 2008
Summary
MolAxis is a new web server that identifies protein channels. It uses computational geometry for efficient analysis of macromolecule structures, aiding in understanding biological transport processes.
Area of Science:
- Structural biology
- Computational biophysics
- Bioinformatics
Background:
- Biological channels are crucial for cellular functions like transport and catalysis.
- Identifying these channels in macromolecules is vital for understanding physiological processes.
- Existing methods may lack efficiency or ease of use for channel identification.
Purpose of the Study:
- To develop an efficient and user-friendly web server for identifying channels in macromolecules.
- To provide detailed information about identified channels, including gating residues and bottleneck radii.
- To offer a tool for both general and advanced users to explore channel structures.
Main Methods:
- Development of the MolAxis web server and stand-alone program.
- Implementation of computational geometry techniques for channel identification.
- Processing of protein and nucleic acid structures in PDB format.
Main Results:
- MolAxis successfully identifies channels connecting buried cavities to the exterior of macromolecules.
- The server accurately detects transmembrane (TM) channels in proteins.
- Detailed channel information, including gating residues, bottleneck, lining residues, and 3D surface representation, is provided.
Conclusions:
- MolAxis provides an efficient and accessible tool for identifying and analyzing biological channels.
- The server aids in the study of protein function related to transport and catalysis.
- MolAxis facilitates research in structural biology and bioinformatics through its advanced features.
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