title: Enhancing the Enrichment of Pharmacophore-Based Target Prediction for the Polypharmacological Profiles of Drugs.
abstract: PharmMapper is a web server for drug target identification by reversed pharmacophore matching the query compound against an annotated pharmacophore model database, which provides a computational polypharmacology prediction approach for drug repurposing and side effect risk evaluation. But due to the inherent nondiscriminative feature of the simple fit scores used for prediction results ranking, the signal/noise ratio of the prediction results is high, posing a challenge for predictive reliability. In this paper, we improved the predictive accuracy of PharmMapper by generating a ligand-target pairwise fit score matrix from profiling all the annotated pharmacophore models against corresponding ligands in the original complex structures that were used to extract these pharmacophore models. The matrix reflects the noise baseline of fit score distribution of the background database, thus enabling estimation of the probability of finding a given target randomly with the calculated ligand-pharmacophore fit score. Two retrospective tests were performed which confirmed that the probability-based ranking score outperformed the simple fit score in terms of identification of both known drug targets and adverse drug reaction related off-targets.
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, and ‡School of Information Science and Engineering, East China University of Science and Technology , Shanghai 200237, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Wang
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, and ‡School of Information Science and Engineering, East China University of Science and Technology , Shanghai 200237, China.
authors.forename: Chenxu
authors.initials: C
authors.lastname: Pan
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, and ‡School of Information Science and Engineering, East China University of Science and Technology , Shanghai 200237, China.
authors.forename: Jiayu
authors.initials: J
authors.lastname: Gong
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, and ‡School of Information Science and Engineering, East China University of Science and Technology , Shanghai 200237, China.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Liu
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, and ‡School of Information Science and Engineering, East China University of Science and Technology , Shanghai 200237, China.
authors.forename: Honglin
authors.initials: H
authors.lastname: Li
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D062313:Databases, Pharmaceutical; D020407:Internet; D008024:Ligands; D058990:Molecular Targeted Therapy; D064798:Polypharmacology; D012984:Software
chemical_list: D008024:Ligands