GCDB: a glaucomatous chemogenomics database for in silico drug discovery

被引:0
|
作者
Wei, Yu [1 ,2 ]
Li, Jinlong [4 ]
Li, Baiqing [1 ,2 ]
Ma, Chunfeng
Xu, Xuanming [1 ,2 ]
Wang, Xu [1 ,2 ]
Liu, Aqin [1 ,2 ]
Du, Tengfei [1 ,2 ]
Wang, Zhonghua [4 ]
Hong, Zhangyong [3 ]
Lin, Jianping [1 ,2 ,4 ,5 ]
机构
[1] Nankai Univ, Coll Pharm, State Key Lab Med Chem Biol, Haihe Educ Pk,38 Tongyan Rd, Tianjin 300353, Peoples R China
[2] Nankai Univ, Tianjin Key Lab Mol Drug Res, Haihe Educ Pk,38 Tongyan Rd, Tianjin 300353, Peoples R China
[3] Nankai Univ, Coll Life Sci, State Key Lab Med Chem Biol, 94 Weijin Rd, Tianjin 300071, Peoples R China
[4] Chinese Acad Sci, Tianjin Inst Ind Biotechnol, Biodesign Ctr, Tianjin 300308, Peoples R China
[5] Tianjin Int Joint Acad Biomed, Platform Pharmaceut Intelligence, Tianjin 300000, Peoples R China
来源
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION | 2018年
基金
国家重点研发计划;
关键词
OPEN-ANGLE GLAUCOMA; OPTIC-NERVE HEAD; MOUSE MODEL; PHARMACOLOGY; ANTAGONISTS; ACTIVATION; RETINA;
D O I
10.1093/database/bay117
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Glaucoma is a group of neurodegenerative diseases that can cause irreversible blindness. The current medications, which mainly reduce intraocular pressure to slow the progression of disease, may have local and systemic side effects. Recently, medications with possible neuroprotective effects have attracted much attention. To assist in the identification of new glaucoma drugs, we created a glaucomatous chemogenomics database (GCDB; http://cadd. pharmacy. nankai. edu. cn/gcdb/home) in which various glaucoma-related chemogenomics data records are assembled, including 275 genes, 105 proteins, 83 approved or clinical trial drugs, 90 206 chemicals associated with 213 093 records of reported bioactivities from 22 324 corresponding bioassays and 5630 references. Moreover, an improved chemical similarity ensemble approach computational algorithm was incorporated in the GCDB to identify new targets and design new drugs. Further, we demonstrated the application of GCDB in a case study screening two chemical libraries, Maybridge and Specs, to identify interactions between small molecules and glaucoma-related proteins. Finally, six and four compounds were selected from the final hits for in vitro human glucocorticoid receptor (hGR) and adenosine A3 receptor (A3AR) inhibitory assays, respectively. Of these compounds, six were shown to have inhibitory activities against hGR, with IC50 values ranging from 2.92-28.43 mu M, whereas one compound showed inhibitory activity against A3AR, with an IC50 of 6.15 mu M. Overall, GCDB will be helpful in target identification and glaucoma chemogenomics data exchange and sharing, and facilitate drug discovery for glaucoma treatment.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] A review on computer-aided chemogenomics and drug repositioning for rational COVID-19 drug discovery
    Maghsoudi, Saeid
    Shahraki, Bahareh Taghavi
    Rameh, Fatemeh
    Nazarabi, Masoomeh
    Fatahi, Yousef
    Akhavan, Omid
    Rabiee, Mohammad
    Mostafavi, Ebrahim
    Lima, Eder C.
    Saeb, Mohammad Reza
    Rabiee, Navid
    CHEMICAL BIOLOGY & DRUG DESIGN, 2022, 100 (05) : 699 - 721
  • [2] Allosteric modulation of GPCRs: From structural insights to in silico drug discovery
    Persechino, Margherita
    Hedderich, Janik Bjoern
    Kolb, Peter
    Hilger, Daniel
    PHARMACOLOGY & THERAPEUTICS, 2022, 237
  • [3] In silico pharmacology for drug discovery:: applications to targets and beyond
    Ekins, S.
    Mestres, J.
    Testa, B.
    BRITISH JOURNAL OF PHARMACOLOGY, 2007, 152 (01) : 21 - 37
  • [4] Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors
    Meqbil, Yazan J.
    van Rijn, Richard M.
    PHARMACEUTICALS, 2022, 15 (07)
  • [5] In silico pharmacology for drug discovery:: methods for virtual ligand screening and profiling
    Ekins, S.
    Mestres, J.
    Testa, B.
    BRITISH JOURNAL OF PHARMACOLOGY, 2007, 152 (01) : 9 - 20
  • [6] Chemical Starting Matter for HNF4α Ligand Discovery and Chemogenomics
    Meijer, Isabelle
    Willems, Sabine
    Ni, Xiaomin
    Heering, Jan
    Chaikuad, Apirat
    Merk, Daniel
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2020, 21 (21) : 1 - 11
  • [7] The Pros and Cons of the In-silico Pharmaco-toxicology in Drug Discovery and Development
    Saeidnia, Soodabeh
    Manayi, Azadeh
    Abdollahi, Mohammad
    INTERNATIONAL JOURNAL OF PHARMACOLOGY, 2013, 9 (03) : 176 - 181
  • [8] AMTDB: A comprehensive database of autophagic modulators for anti-tumor drug discovery
    Fu, Jiahui
    Wu, Lifeng
    Hu, Gaoyong
    Shi, Qiqi
    Wang, Ruodi
    Zhu, Lingjuan
    Yu, Haiyang
    Fu, Leilei
    FRONTIERS IN PHARMACOLOGY, 2022, 13
  • [9] In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery
    Ivanov, Julian M.
    Tenchov, Rumiana
    Ralhan, Krittika
    Iyer, Kavita A.
    Agarwal, Shivangi
    Zhou, Qiongqiong Angela
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2024, 64 (19) : 7488 - 7502
  • [10] Drug repositioning using in silico compound profiling
    Dubus, Elodie
    Ijjaali, Ismail
    Barberan, Olivier
    Petitet, Francois
    FUTURE MEDICINAL CHEMISTRY, 2009, 1 (09) : 1723 - 1736