Computational 3D structure prediction followed by molecular docking to reveal the novel drug targets against ADA

Abstract

Adenosine deaminase (ADA) is a functional enzyme that transforms deoxyadenosine and adenosine into deoxyinosine and inosine respectively. ADA deficiency causes toxic purine degradation byproducts to build up in the body, which has a particularly negative impact on lymphocytes and results in adenosine deaminase-deficient severe combined immunodeficiency. Different in silico techniques including threading, ab initio and homology modeling for 3D structure prediction were applied for the prediction of ADA structures. Following the three-dimensional structure prediction analyses, an extensive computational assessment of all predicted structures for reliability was performed. The overall quality factor of the predicted ADA structures was observed 62.45% in the predicted 3D models. A Ramachandran plot was created, and 94.80% of the residues were found in the allowed and favored regions of the protein structure plot. The molecular docking analyses were performed in order to identify the potential therapeutic medication targets against ADA. The virtually examined molecules through a virtually high throughput screening may have the ability the regulation the ADA activity. The least binding energy was calculated through the molecular docking analyses and the energy values were observed -8.7 Kcal/mol. The binding residues (Lys-367, Glu-424, Asp-422, Phe-381, Ile-377, Ser-430 and Glu-374) were conserved in all the interactional analyses of the docked complexes. Finding the effective binding domain in a protein three-dimensional structure is crucial for understanding of its structural makeup and determining its functions.