EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction

Joint Authors

Chien, Yu-Tung
Huang, Shao-Wei
Yu, Chin-Sheng
Lu, Chih-Hao

Source

BioMed Research International

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-09-11

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Medicine

Abstract EN

We propose a method (EXIA2) of catalytic residue prediction based on protein structure without needing homology information.

The method is based on the special side chain orientation of catalytic residues.

We found that the side chain of catalytic residues usually points to the center of the catalytic site.

The special orientation is usually observed in catalytic residues but not in noncatalytic residues, which usually have random side chain orientation.

The method is shown to be the most accurate catalytic residue prediction method currently when combined with PSI-Blast sequence conservation.

It performs better than other competing methods on several benchmark datasets that include over 1,200 enzyme structures.

The areas under the ROC curve (AUC) on these benchmark datasets are in the range from 0.934 to 0.968.

American Psychological Association (APA)

Lu, Chih-Hao& Yu, Chin-Sheng& Chien, Yu-Tung& Huang, Shao-Wei. 2014. EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction. BioMed Research International،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1034571

Modern Language Association (MLA)

Lu, Chih-Hao…[et al.]. EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction. BioMed Research International No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1034571

American Medical Association (AMA)

Lu, Chih-Hao& Yu, Chin-Sheng& Chien, Yu-Tung& Huang, Shao-Wei. EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1034571

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1034571