title: Finding protein targets for small biologically relevant ligands across fold space using inverse ligand binding predictions.
abstract: Inverse ligand binding prediction utilizes a few protein-ligand (drug) complexes to predict other secondary therapeutic and off-targets of a given drug molecule on a proteomic scale. We adapt two binding site predictors, FINDSITE and SMAP, to perform the inverse predictions and evaluate them on over 30 representative ligands. Use of just one complex allows the identification of other protein targets; the availability of additional complexes improves the results. Both methods offer comparable quality when using three complexes with diverse proteins. SMAP is better when fewer complexes are available, while FINDSITE provides stronger predictions for smaller ligands. We propose a consensus that combines (and outperforms) the two complementary approaches implemented by FINDSITE and SMAP. Most importantly, we demonstrate that these methods successfully find distant targets that belong to structurally different folds compared to the proteins in the input complexes.
authors.affiliation: School of Mathematical Sciences and LPMC, Nankai University, Tianjin 300071, People's Republic of China.
authors.forename: Gang
authors.initials: G
authors.lastname: Hu
authors.forename: Jianzhao
authors.initials: J
authors.lastname: Gao
authors.forename: Kui
authors.initials: K
authors.lastname: Wang
authors.forename: Marcin J
authors.initials: MJ
authors.lastname: Mizianty
authors.forename: Jishou
authors.initials: J
authors.lastname: Ruan
authors.forename: Lukasz
authors.initials: L
authors.lastname: Kurgan
mesh_terms: D008024:Ligands; D011485:Protein Binding; D011506:Proteins / Q000378:metabolism*
chemical_list: D008024:Ligands; D011506:Proteins