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Int. J. Mol. Sci. 2012, 13(7), 8752-8761; doi:10.3390/ijms13078752

Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction

1,*  and 1,3,4,*
1 College of Life Science and Biotechnology, Tongji University, Shanghai 200092, China 2 College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China 3 Institute for Advanced Study of Translational Medicine, Tongji University, Shanghai 200092, China 4 School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian 116600, China These authors contributed equally to this work.
* Authors to whom correspondence should be addressed.
Received: 14 May 2012 / Revised: 19 June 2012 / Accepted: 2 July 2012 / Published: 16 July 2012
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In recent years, although many ligand-binding site prediction methods have been developed, there has still been a great demand to improve the prediction accuracy and compare different prediction algorithms to evaluate their performances. In this work, in order to improve the performance of the protein-ligand binding site prediction method presented in our former study, a comparison of different binding site ranking lists was studied. Four kinds of properties, i.e., pocket size, distance from the protein centroid, sequence conservation and the number of hydrophobic residues, have been chosen as the corresponding ranking criterion respectively. Our studies show that the sequence conservation information helps to rank the real pockets with the most successful accuracy compared to others. At the same time, the pocket size and the distance of binding site from the protein centroid are also found to be helpful. In addition, a multi-view ranking aggregation method, which combines the information among those four properties, was further applied in our study. The results show that a better performance can be achieved by the aggregation of the complementary properties in the prediction of ligand-binding sites.
Keywords: ranking aggregation; protein-ligand binding site; prediction ranking aggregation; protein-ligand binding site; prediction
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Gao, J.; Liu, Q.; Kang, H.; Cao, Z.; Zhu, R. Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction. Int. J. Mol. Sci. 2012, 13, 8752-8761.

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