Smriti Sharma, Shahista Chauhan and Brij Kishore Sharma* Pages 1 - 12 ( 12 )
Background: The well-known histamine H3 receptor antagonists are based on an imidazole scaffold. However, the interaction between hepatic CYP450 and imidazole-based drugs leads to some side effects, such as low potential, physicochemical problems, etc. Therefore, another category of chemical class, benzimidazolone has been explored as an antihistaminic H3 agent.
Objectives: In this study, the histamine H3 binding affinity of benzimidazolone derivatives has been quantitatively investigated using Dragon descriptors.
Methods: The models were developed from statistically corroborated quantitative structure-activity relationship (QSAR) models that delivered rationales for the description of the binding affinity of benzimidazolonebased derivatives. In addition, the identified descriptors through CP-MLR analysis for the histamine H3 binding affinity highlighted the role of symmetry, atomic mass, information content, electrostaticity, rings in the structures, number of chlorine atoms (nCL), and average valence connectivity index chi-3 (X3Av).
Results: The PLS assessment validated the power of CP-MLR-identified descriptors. The applicability domain suggested that the model fulfills the superior feature parameters with good fit and predictive power.
Conclusion: All the compounds were found to be within the applicability domain of the recommended models.
Quantitative Structure-activity Relationship (QSAR), G-protein coupled receptor, Partial least square (PLS), histamine H3- receptor, Combinatorial protocol in multiple linear regression (CP-MLR) analysis, Benzimidazolone derivatives.