针对SP4靶向精神分裂症的计算机辅助药物设计

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摘要

精神分裂症(SZ)是一种精神障碍,影响着全球约1%的人口。它被认为是一种慢性和严重的疾病,影响患者的思想、情绪和行为,经常导致对现实的扭曲。利用线程技术、同源建模技术、从头算技术等多种计算技术对选定的SZ蛋白SP4进行了三维结构预测。利用Anolea、ProCheck和Errat评价工具对SP4的三维预测结构进行进一步评价和验证。有趣的是,所选结构的整体质量因子为77.542%。SP4的预测结构在Ramachandran图的离群区残差为3.97%,在评价图的允许区和有利区残差为96.03%。通过分子对接分析,鉴定了以SP4为靶点的抗SZ化合物。此外,化合物的结合能最低,为-10.1 Kcal/mol。结合残基(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和Ala-287)的结合亲和力最高。从选定的文库中筛选的分子可能具有通过靶向SP4调节SZ活性的能力。经过仔细检查的分子可以表现为潜在的化合物,并且SP4的3D预测结构对于结构见解和功能分析是可靠的。
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Computer-aided drug design against schizophrenia by targeting SP4
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.
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