Computational Approaches for the Discovery of Novel Chromen-2-one Derivatives as 5-HT1A Inhibitors for the Treatment of Schizophrenia

A severe and persistent mental condition, Schizophrenia, affects 1% of people worldwide. Conventional antipsychotics managed the disease’s negative symptoms and cognitive impairment, but they were ineffective in diminishing the positive symptoms. Furthermore, extrapyramidal symptoms and hyperprolactinemia are two serious adverse effects linked to standard antipsychotics. Here, we investigated poly-substituted chromen-2-one derivatives as possible atypical antipsychotics using computational methods. As mentioned above, the derivatives have undergone pharmacophore modeling, 3D-QSAR, virtual screening, R-group enumeration and docking studies. The model AAHPR_1 has been selected as the best hypothesis. The 3D-QSAR research yielded the most successful statistical models, with the atom-based model’s correlation coefficient ([Formula: see text] 0.7455) and cross-validated correlation ([Formula: see text] 0.8229), and the field-based model’s correlation coefficient ([Formula: see text] 0.7455) and [Formula: see text] 0.6124. A total of 5880 compounds were generated using the R-group enumeration study to produce new compounds. After screening, compounds move on to a virtual screening methodology that incorporates the Lipinski rule of five and multiple docking studies. Four compounds have been chosen in the final step based on their docking scores and binding interactions. Compound 1A exhibited binding interactions with amino acids ASP116 and TYR96 that were similar to those of conventional medications aripiprazole, risperidone and clozapine, with a docking score of −7.466 (PDB ID: 7E2Z). These compounds may also be used further in generating possible 5-HT1A inhibitors.