TY - JOUR
T1 - Recognition of functional sites in protein structures
AU - Shulman-Peleg, Alexandra
AU - Nussinov, Ruth
AU - Wolfson, Haim J.
N1 - Funding Information:
We thank Maxim Shatsky and Dina Schneidman for useful discussions and for contribution of software to this project. We thank Dr Shuo Liang Lin for particularly valuable ideas and for critical reading of the manuscript. We thank Drs David Zanuy, Buyong Ma and K. Gunasekaran for useful suggestions. This research has been supported, in part, by the “Center of Excellence in Geometric Computing and its Applications” funded by the Israel Science Foundation (administered by the Israel Academy of Sciences). The research of H.J.W. and A.S.-P. is partially supported by the Hermann Minkowski-Minerva Center for Geometry at Tel Aviv University. The research of R.N. has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract number NO1-CO-12400. The content of this publication does not necessarily reflect the view or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organization imply endorsement by the US Government. The publisher or recipient acknowledges right of the US Government to retain a non-exclusive, royalty-free license in and to any copyright covering the article. Funded, in part, by the NCI under contract NO1-CO-12400.
PY - 2004/6/4
Y1 - 2004/6/4
N2 - Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.
AB - Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.
KW - 3D database searches
KW - ALBP, adipocyte lipid-binding protein
KW - HFABP, heart muscle fatty acid-binding protein
KW - RMSD, root-mean-square deviation
KW - binding sites similarity
KW - computer-aided drug design
KW - pharmacophore
KW - protein function prediction
UR - http://www.scopus.com/inward/record.url?scp=2442614144&partnerID=8YFLogxK
U2 - 10.1016/j.jmb.2004.04.012
DO - 10.1016/j.jmb.2004.04.012
M3 - מאמר
AN - SCOPUS:2442614144
VL - 339
SP - 607
EP - 633
JO - Journal of Molecular Biology
JF - Journal of Molecular Biology
SN - 0022-2836
IS - 3
ER -