title: Predicting subtype selectivity of dopamine receptor ligands with three-dimensional biologically relevant spectrum.
abstract: We applied a novel molecular descriptor, three-dimensional biologically relevant spectrum (BRS-3D), in subtype selectivity prediction of dopamine receptor (DR) ligands. BRS-3D is a shape similarity profile calculated by superimposing the objective compounds against 300 template ligands from sc-PDB. First, we constructed five subtype selectivity regression models between DR subtypes D1-D2, D1-D3, D2-D3, D2-D4, and D3-D4. The models' 10-fold cross-validation-squared correlation coefficient (Q2, for training sets) and determination coefficient (R2, for test sets) were in the range of 0.5-0.7 and 0.6-0.8, respectively. Then, four pair-wise (D1-D2, D2-D3, D2-D4, and D3-D4) and a multitype (D2, D3, and D4) classification models were developed with the prediction accuracies around or over 90% (for test sets). Lastly, we compared the performances of the models developed on BRS-3D and classical descriptors. The results showed that BRS-3D performed similarly to classical 2D descriptors and better than other 3D descriptors. Combining BRS-3D and 2D descriptors can further improve the prediction performance. These results confirmed the capacity of BRS-3D in the prediction of DR subtype-selective ligands.
authors.affiliation: State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.|Agricultural Bioinformatics Key Laboratory of Hubei Province, College of informatics, Huazhong Agricultural University, Wuhan, China.
authors.forename: Zheng-Kun
authors.initials: ZK
authors.lastname: Kuang
authors.affiliation: Agricultural Bioinformatics Key Laboratory of Hubei Province, College of informatics, Huazhong Agricultural University, Wuhan, China.
authors.forename: Shi-Yu
authors.initials: SY
authors.lastname: Feng
authors.affiliation: State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.|Agricultural Bioinformatics Key Laboratory of Hubei Province, College of informatics, Huazhong Agricultural University, Wuhan, China.
authors.forename: Ben
authors.initials: B
authors.lastname: Hu
authors.affiliation: Agricultural Bioinformatics Key Laboratory of Hubei Province, College of informatics, Huazhong Agricultural University, Wuhan, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Wang
authors.affiliation: Agricultural Bioinformatics Key Laboratory of Hubei Province, College of informatics, Huazhong Agricultural University, Wuhan, China.
authors.forename: Song-Bing
authors.initials: SB
authors.lastname: He
authors.affiliation: State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China. dxkong@mail.hzau.edu.cn.|Agricultural Bioinformatics Key Laboratory of Hubei Province, College of informatics, Huazhong Agricultural University, Wuhan, China. dxkong@mail.hzau.edu.cn.
authors.forename: De-Xin
authors.initials: DX
authors.lastname: Kong
mesh_terms: D008024:Ligands; D008956:Models, Chemical; D021281:Quantitative Structure-Activity Relationship; D011954:Receptors, Dopamine / Q000145:classification / Q000378:metabolism*; D060388:Support Vector Machine
chemical_list: D008024:Ligands; D011954:Receptors, Dopamine
keywords: 
  QSAR
  ; BRS-3D; dopamine receptor; subtype selectivity; support vector machine