Chem Biol Drug Des 2013: 82: 326-335 Research Article Design, Synthesis, and Evaluation of Indolebutylamines as a Novel Class of selective Dopamine D3 Receptor Ligands Peng Du',., Lili Xu',, Jiye Huang,, Kungian Yu2, high sequence homology among the D2-like dopamine Rui Zhao, Bo Gao, Hualiang Jiang, Weili receptor subtypes(D2, D3, and D4). For instance, hD3R Zhao Xuechu Zhen and Wei Fu and hD2R share 78% sequence homology within the seven transmembrane domains and 94% sequence 'Department of Medicinal Chemistry Key Laboratory of homology within the active site (10, 11). To date, most of Smart Drug Delivery, Ministry of Education PLA, School D3R selective ligands are 4-Phenylpiperazines and their f Pharmacy, Fudan University, Shanghai, 201203, Chin 2Drug Discovery and Design Center, State Key Laboratory close analogs(12, 13). Considering the importance of the of Drug Research, Shanghai Institute of MateriaMedica D3R in the treatment of addiction and other neuropsy- cho disorders, it is meaningful to discover novel chemi- Chinese Academy of Sciences, Shanghai, 201203, China Department of Pharmacology, College of Pharmaceutical cal entities to enrich the structural diversity of potent Sciences, Soochow University, Suzhou, 215123, China and selective D3R ligands. Using a strategy that com Correspondingauthor:WeiFu,wfu@fudan.edu.cn bines synthetic chemistry, binding assays, and a set of fThese authors contributed equally to this work. computational approach(integrating active site mappin pharmacophore-based virtual screening, and automate A series of indolebutylamine derivatives were designed molecular docking), we designed a series of IBA deriva- synthesized, and evaluated as a novel class of selective tives as a new type of highly selective D3R antagonists ligands for the dopamine 3 receptor. The most potent Furthermore, the molecular determinants compound 11q binds to dopamine 3 receptor with a K binding specificity and selectivity of D3R were identified value of 124 nM and displays excellent selectivity over and the structure-activity relationships(SAR) was investi he dopamine 1 receptor and dopa amine gated Investigation based on structural information indicates that site S182 located in extracellular loop 2 may Methods and Materials account for high selectivity of compounds. Interaction models of the dopamine 3 receptor-11q complex and Structure-based pharmacophore model generation structure-activity relationships were discussed by inte- grating all available experimental and computational Dopamine 3 receptor was obtained from the Protein Data data with the eventual aim to discover potent and selec Bank(PDB ID: 3PBL)(11). The GRID22 program(14)was tive ligands to dopamine 3 receptor. employed to map the active sites of the optimized X-ray structure of D3R with five types of chemical probes, that Key words: dopamine 3 receptor, indolebutylamine, pharma- IS, negative ionizable(Coo-), positive ionizable(N1+) cophore model, selectivity, structure-activity relationship hydrogen-bond acceptor(O), hydrogen-bond donor(N1) and hydrophobic probes(DRY). For each of the five Received 22 November 2012, revised 17 April 2013 and probes used in the grid calculations, grid points were accepted for publication 26 April 2013 superimposed to identify clusters of positions. The mem- bers of each identified clusters were combined into one pharmacophore feature, and the centers of each pharma- Since the discovery by Sokoloff et al. in 1990(1), dopamine cophore features were set at the geometric centers of the 3 receptor(D3R) has been proved to be a promising thera- members in each clusters(15. Finally, a four-feature phar- peutic target for drug discovery. Dopamine 3 receptor macophore model was generated antagonist was shown to play a key role in the treatment of schizophrenia(2, 3)and drug addiction(4). Although consid able efforts have been devoted to the design and develop- Virtual screening ment of D3R antagonists(5-9), function study of D3R in vivo The obtained phamacophore model was used to screen is still limited due to the lack of highly selective antagonists the Asinex GOLD and Maybridge collection database which contain 238 000 compounds. The Ligand Pharma- One of the important reasons for the difficulty in devel- cophore Mapping protocol embedded in DISCOVERY STUDIO oping selective antagonist for D3R is attributed to the 3.5 was employed to retrieve molecules, which can well e 2013 John Wiey& Sons AS. doi: 10. 1111/cbdd. 12158Design, Synthesis, and Evaluation of Indolebutylamines as a Novel Class of Selective Dopamine D3 Receptor Ligands Peng Du1,† , Lili Xu1,† , Jiye Huang2,† , Kunqian Yu2 , Rui Zhao3 , Bo Gao3 , Hualiang Jiang2 , Weili Zhao1 , Xuechu Zhen3 and Wei Fu1,* 1 Department of Medicinal Chemistry & Key Laboratory of Smart Drug Delivery, Ministry of Education & PLA, School of Pharmacy, Fudan University, Shanghai, 201203, China 2 Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of MateriaMedica, Chinese Academy of Sciences, Shanghai, 201203, China 3 Department of Pharmacology, College of Pharmaceutical Sciences, Soochow University, Suzhou, 215123, China *Corresponding author: Wei Fu, wfu@fudan.edu.cn †These authors contributed equally to this work. A series of indolebutylamine derivatives were designed, synthesized, and evaluated as a novel class of selective ligands for the dopamine 3 receptor. The most potent compound 11q binds to dopamine 3 receptor with a Ki value of 124 nM and displays excellent selectivity over the dopamine 1 receptor and dopamine 2 receptor. Investigation based on structural information indicates that site S182 located in extracellular loop 2 may account for high selectivity of compounds. Interaction models of the dopamine 3 receptor-11q complex and structure-activity relationships were discussed by inte￾grating all available experimental and computational data with the eventual aim to discover potent and selec￾tive ligands to dopamine 3 receptor. Key words: dopamine 3 receptor, indolebutylamine, pharma￾cophore model, selectivity, structure-activity relationship Received 22 November 2012, revised 17 April 2013 and accepted for publication 26 April 2013 Since the discovery by Sokoloff et al. in 1990 (1), dopamine 3 receptor (D3R) has been proved to be a promising thera￾peutic target for drug discovery. Dopamine 3 receptor antagonist was shown to play a key role in the treatment of schizophrenia (2,3) and drug addiction (4). Although consid￾erable efforts have been devoted to the design and develop￾ment of D3R antagonists (5–9), function study of D3R in vivo is still limited due to the lack of highly selective antagonists. One of the important reasons for the difficulty in devel￾oping selective antagonist for D3R is attributed to the high sequence homology among the D2-like dopamine receptor subtypes (D2, D3, and D4). For instance, hD3R and hD2R share 78% sequence homology within the seven transmembrane domains and 94% sequence homology within the active site (10,11). To date, most of D3R selective ligands are 4-Phenylpiperazines and their close analogs (12,13). Considering the importance of the D3R in the treatment of addiction and other neuropsy￾cho disorders, it is meaningful to discover novel chemi￾cal entities to enrich the structural diversity of potent and selective D3R ligands. Using a strategy that com￾bines synthetic chemistry, binding assays, and a set of computational approach (integrating active site mapping, pharmacophore-based virtual screening, and automated molecular docking), we designed a series of IBA deriva￾tives as a new type of highly selective D3R antagonists. Furthermore, the molecular determinants critical to the binding specificity and selectivity of D3R were identified and the structure-activity relationships (SAR) was investi￾gated. Methods and Materials Structure-based pharmacophore model generation Dopamine 3 receptor was obtained from the Protein Data Bank (PDB ID: 3PBL) (11). The GRID22 program (14) was employed to map the active sites of the optimized X-ray structure of D3R with five types of chemical probes, that is, negative ionizable (COO
), positive ionizable (N1+), hydrogen-bond acceptor (O), hydrogen-bond donor (N1), and hydrophobic probes (DRY). For each of the five probes used in the grid calculations, grid points were superimposed to identify clusters of positions. The mem￾bers of each identified clusters were combined into one pharmacophore feature, and the centers of each pharma￾cophore features were set at the geometric centers of the members in each clusters (15). Finally, a four-feature phar￾macophore model was generated. Virtual screening The obtained pharmacophore model was used to screen the Asinex GOLD and Maybridge collection database which contain 238 000 compounds. The Ligand Pharma￾cophore Mapping protocol embedded in DISCOVERY STUDIO 3.5a was employed to retrieve molecules, which can well 326 ª 2013 John Wiley & Sons A/S. doi: 10.1111/cbdd.12158 Chem Biol Drug Des 2013; 82: 326–335 Research Article