GPCR Pharmacophore Model Database(GPCRPMD)


    GPCR-based drug discovery is hindered by a lack of effective screening methods for most GPCRs that have neither ligands nor high-quality structures. With the aim to identify lead molecules for these GPCRs, we developed a new method called Pharmacophore-Map-Pick to generate pharmacophore models for all human GPCRs. The model of ADRB2 generated using this method not only predicts the binding mode of ADRB2-ligands correctly but also performs well in virtual screening. Findings also demonstrate that this method is powerful for generating high-quality pharmacophore models. The average enrichment for the pharmacophore models of the 15 targets in different GPCR families reached 15-fold at 0.5% false-positive rate. Therefore, the pharmacophore models can be applied in virtual screening directly with no requirement for any ligand information or shape constraints. A total of 2386 pharmacophore models for 819 different GPCRs (99% coverage (819/825)) were generated and are available at http://bsb.kiz.ac.cn/GPCRPMD.

Comparison of the pharmacophore models generated using two methods

Search the database using UniProt AC

for example: P41143

Batch Download

Download all pharmacophore models: all_pharmacophore_models.rar
Download 825 GPCRs structure models: 825_structure_models.rar

Description of GPCRPMD

    G-protein coupled receptors (GPCRs) are the most prominent therapeutic target family for various diseases. However, drug discovery in the GPCR field are hindered by lacking effective screening methods for most GPCRs which do neither have ligands nor high-quality structures. With the aim to speed up the process of identifying lead molecules for these GPCRs, we developed a new method Pharmacophore-Map-Pick to generate pharmacophore models for all human GPCRs.
    The model of ADRB2 generated using this method not only predict the binding mode of ADRB2-ligands correctly but also perform well in virtual screening. Further validations demonstrated that this method is powerful for generating high-quality pharmacophore models which achieve acceptable enrichments. The average of enrichments for the pharmacophore models of 15 targets in different GPCR family is reached almost 15-fold at 0.5% false-positive rate. Therefore, our pharmacophore models can be applied in virtual screening directly with no requirement of any ligand information and shape constraints.
    Using this method, 2386 pharmacophore models for 819 different GPCRs were generated. The coverage of pharmacophore models for human GPCRs reaches 99% (819/825). All pharmacophore models of GPCRs are available at http://bsb.kiz.ac.cn/GPCRPMD. For the first time, the largest specialized GPCR pharmacophore model database is available online. Our method and database presented here offer a useful resource for drug design and discovery in the GPCR field.

Citation

Dai S X, Li G H, Gao Y D, Huang J F*. Pharmacophore‐Map‐Pick: A Method to Generate Pharmacophore Models for All Human GPCRs[J]. Molecular Informatics, 2015.   Paper link

Contact

Dr. Shao-xing Dai
Kunming Institute of Zoology, Chinese Academy of Sciences,China
E-mail: daishaoxing@mail.kiz.ac.cn

Update notes

2014-07-24: GPCR Pharmacophore Database(GPCRPMD) was released.