Abstract
Urease enzyme (EC 3.5.1.5) has been determined as a virulence factor in pathogenic microorganisms that are accountable for the development of different diseases in humans and animals. In continuance of our earlier study on the helicobacter pylori urease inhibition by barbituric acid derivatives, 3D-QSAR (three dimensional quantitative structural activity relationship) advance studies were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. Different partial charges were calculated to examine their consequences on the predictive ability of the developed models. The finest developed model for CoMFA and CoMSIA were achieved by using MMFF94 charges. The developed CoMFA model gives significant results with cross-validation (q2) value of 0.597 and correlation coefficients (r2) of 0.897. Moreover, five different fields i.e., steric, electrostatic, and hydrophobic, H-bond acceptor and H-bond donors were used to produce a CoMSIA model, with q2 and r2 of 0.602 and 0.98, respectively. The generated models were further validated by using an external test set. Both models display good predictive power with r2pred ≥ 0.8. The analysis of obtained CoMFA and CoMSIA contour maps provided detailed insight for the promising modification of the barbituric acid derivatives with an enhanced biological activity.
Highlights
Urease (EC 3.5.1.5) is a metallo-enzyme that catalyzes the hydrolysis of urea into ammonia (NH3) and carbon dioxide (CO2)
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Summary
Urease (EC 3.5.1.5) is a metallo-enzyme that catalyzes the hydrolysis of urea into ammonia (NH3) and carbon dioxide (CO2). About half of overall population is sensitive to H. pylori This species of bacteria can survive in stomach of infected individuals for their whole life without causing disease symptoms. Other treatment methods have developed to battle H. pylori disease, which incorporate the utilization of bismuth salts joined with a proton pump cell inhibitor or the combination of different classes of anti-infection agents, such as aminopenicillins, fluoroquinolones, tetracycline, and so on [13,21]. For the last twenty years, ligand- and structure-based drug design strategy has been effectively utilized for the compound’s optimization In this regard, the 3D-QSAR technique is extensively utilized to develop and predict the bio-activities of novel compounds.
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