GCDB: A Glaucomatous Chemogenomics Database for in Silico Drug Discovery

Database (Oxford). 2018 Jan 1;2018:bay117. doi: 10.1093/database/bay117.


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 μM, whereas one compoundshowed inhibitory activity against A3AR, with an IC50 of 6.15 μM. Overall, GCDB will be helpful in target identification and glaucoma chemogenomics data exchange and sharing, and facilitate drug discovery for glaucoma treatment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Base Sequence
  • Computer Simulation*
  • Databases, Genetic*
  • Drug Discovery*
  • Genomics*
  • Glaucoma / drug therapy*
  • Glaucoma / genetics*
  • Humans
  • Ligands
  • Molecular Docking Simulation
  • User-Computer Interface


  • Ligands