Classification and comparison of ligand-binding sites derived from grid-mapped knowledge-based potentials. Export

@article{citeulike:472863, abstract = {We describe the application of knowledge-based potentials implemented in the MOE program to compare the ligand-binding sites of several proteins. The binding probabilities for a polar and a hydrophobic probe are calculated on a grid to allow easy comparison of binding sites of superimposed related proteins. The method is fast and simple enough to simultaneously use structural information of multiple proteins of a target family. The method can be used to rapidly cluster proteins into subfamilies according to the similarity of hydrophobic and polar fields of their ligand-binding sites. Regions of the binding site which are common within a protein family can be identified and analysed for the design of family-targeted libraries or those which differ for improvement of ligand selectivity. The field-based hierarchical clustering is demonstrated for three protein families: the ligand-binding domains of nuclear receptors, the ATP-binding sites of protein kinases and the substrate binding sites of proteases. More detailed comparisons are presented for serine proteases of the chymotrypsin family, for the peroxisome proliferator-activated receptor subfamily of nuclear receptors and for progesterone and androgen receptor. The results are in good accordance with structure-based analysis and highlight important differences of the binding sites, which have been also described in the literature.}, address = {Orion Pharma, Medicinal Chemistry, P.O. Box 65, FIN-02101 Espoo, Finland; University of Cologne, Cologne University Bioinformatics Center (CUBIC), Z\"{u}lpicher Str. 47, D-50674 K\"{o}ln, Germany.}, author = {Hoppe, Christian and Steinbeck, Christoph and Wohlfahrt, Gerd}, citeulike-article-id = {472863}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.jmgm.2005.09.013}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/16260161}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=16260161}, day = {27}, doi = {10.1016/j.jmgm.2005.09.013}, issn = {1093-3263}, journal = {J Mol Graph Model}, keywords = {bs-similarity, knowledge-based-potentials, moe, protein-ligand, structure-classification}, month = {October}, posted-at = {2006-01-20 20:21:30}, priority = {0}, title = {Classification and comparison of ligand-binding sites derived from grid-mapped knowledge-based potentials.}, url = {http://dx.doi.org/10.1016/j.jmgm.2005.09.013}, year = {2005} }

TY - JOUR ID - citeulike:472863 L3 - citeulike-article-id:472863 N2 - We describe the application of knowledge-based potentials implemented in the MOE program to compare the ligand-binding sites of several proteins. The binding probabilities for a polar and a hydrophobic probe are calculated on a grid to allow easy comparison of binding sites of superimposed related proteins. The method is fast and simple enough to simultaneously use structural information of multiple proteins of a target family. The method can be used to rapidly cluster proteins into subfamilies according to the similarity of hydrophobic and polar fields of their ligand-binding sites. Regions of the binding site which are common within a protein family can be identified and analysed for the design of family-targeted libraries or those which differ for improvement of ligand selectivity. The field-based hierarchical clustering is demonstrated for three protein families: the ligand-binding domains of nuclear receptors, the ATP-binding sites of protein kinases and the substrate binding sites of proteases. More detailed comparisons are presented for serine proteases of the chymotrypsin family, for the peroxisome proliferator-activated receptor subfamily of nuclear receptors and for progesterone and androgen receptor. The results are in good accordance with structure-based analysis and highlight important differences of the binding sites, which have been also described in the literature. JF - J Mol Graph Model SN - 1093-3263 AD - Orion Pharma, Medicinal Chemistry, P.O. Box 65, FIN-02101 Espoo, Finland; University of Cologne, Cologne University Bioinformatics Center (CUBIC), Zülpicher Str. 47, D-50674 Köln, Germany. TI - Classification and comparison of ligand-binding sites derived from grid-mapped knowledge-based potentials. KW - bs-similarity KW - knowledge-based-potentials KW - moe KW - protein-ligand KW - structure-classification AU - Hoppe, Christian AU - Steinbeck, Christoph AU - Wohlfahrt, Gerd PY - 2005/10/27/ UR - http://dx.doi.org/10.1016/j.jmgm.2005.09.013 ER -