Computer-aided drug design against schizophrenia by targeting SP4

Abstract

Schizophrenia (SZ) is a mental disorder and affects ~1% of the worldwide population. It is considered a chronic and severe condition that impacts the thoughts, emotions, and behavior, of the patient often leading to a distortion of reality. Numerous computational techniques such as threading technique, homology modeling technique, and ab initio technique were applied for 3D structure prediction of the selected SZ protein SP4. The 3D predicted structures of SP4 were further evaluated and validated by utilizing Anolea, ProCheck, and Errat evaluation tools. Interestingly, it was observed that the overall quality factor of the selected structure was 77.542%. The predicted structure of SP4 showed 3.97% residues in the outlier region of Ramachandran plot while 96.03% in the allowed and the favored region of the evaluated plot. The study of molecular docking analyses was done to identify the compounds against SZ by targeting SP4. Moreover, the scrutinized compounds showed the least binding energy of -10.1 Kcal/mol. The highest binding affinity was observed among the binding residues (Leu-199, Ala-275, Gly-262, Leu-198, Thr-333, Ser-334, Leu-339, Ala-206, Leu-208, Gly-281, Ile-207, Val-283, Pro-286, and Ala-287). The scrutinized molecules from the selected library may have the ability to regulate the activity of SZ by targeting SP4. The scrutinized molecules can behave as a potential compound and the 3D predicted structure of SP4 is reliable for structural insights and functional analyses.