Automated prediction of ligand-binding sites in proteins |
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Authors: | Harris Rodney Olson Arthur J Goodsell David S |
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Affiliation: | Department of Molecular Biology, The Scripps Research Institute, La Jolla, California 92037, USA. |
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Abstract: | We present a method, termed AutoLigand, for the prediction of ligand-binding sites in proteins of known structure. The method searches the space surrounding the protein and finds the contiguous envelope with the specified volume of atoms, which has the largest possible interaction energy with the protein. It uses a full atomic representation, with atom types for carbon, hydrogen, oxygen, nitrogen and sulfur (and others, if desired), and is designed to minimize the need for artificial geometry. Testing on a set of 187 diverse protein-ligand complexes has shown that the method is successful in predicting the location and approximate volume of the binding site in 73% of cases. Additional testing was performed on a set of 96 protein-ligand complexes with crystallographic structures of apo and holo forms, and AutoLigand was able to predict the binding site in 80% of the apo structures. |
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Keywords: | functional site prediction structural genomics rational drug design AutoDock |
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