Repositioning of strongly integrated drugs against achromatopsia (CNGB3)

[Display omitted] •Studies shows that bioinformatics-primarily based methods have the capability to offer systematic insights into the complex relationships.•Virtual screening is used, to filter and identify new compounds on the basis of their biological structures from the large set of drug compounds library.•K means algorithm was used for grouping homologous drug compounds by using bioinformatics tool.•The clustered drug compounds were analyzed by applying the attribute of modularity and layouts of expansion, fruchterman Reingold.•Modularity based clustering technique determine the potential of drug’s interactions for treatments.•DDIs reflect the intervention of several behaviors of the drug.•LD50 indicates the relative intense risks of modern chemicals, particularly at the point when no other toxicology information are accessible for the chemicals.•For Protein structure prediction ab initio method was used and a number of possible confirmations were generated. Achromatopsia (ACHM) is a genetically heterogeneous visual disorder, also known as rod monochromatism, in which human get affected due to cone cells. Mutation in five genes viz. CNGA3, CNGB3, GNAT2, PDE6C, and PDE6H have been reported in ACHM. These genes encode essential constitutes of the cone-specific photo transduction cascade. Present study was focused on CNGB3 gene that accounts 40%-50% mutations of all ACHM cases. A new approach for analyzing drug-drug interactions based on modularity was adopted. This approach depends on the behavioral relationship of drugs against CNGB3 for ACHM, particularly the ADME and toxicity between drugs. Data of 2475 compounds were retrieved, out of which 185 were selected on the basis of Lipinski rule of five. In total, eight clusters were made for which the strongly interacted DDI networks were build based on their modularity values. Strong DDI and minimum toxic values indicates that 5 drugs are effective, but on the basis of docking only 2 drugs indicated no bumps, which shows that they are most appropriate for treating ACHM. Our findings revealed that drug-drug interactions disclose the intervention of drug nature and can also successfully diagnose new indications and more convincing drugs for other diseases as well.