Abstract：
Protein tyrosine phosphatase 1B (PTP1B) has been identified as a promising drug target for the development of diabetes medications via an inhibition mechanism. Using a computational approach, this study investigates the binding mechanism of lead optimized natural compounds from Allium sativum against the human PTP1B. The molecular docking, induced-fit docking, and binding free energy calculations were analyzed using Schrödinger Suite 2021-2. MD simulation, and gene enrichment analysis was achieved via the Desmond module of Schrödinger to identify best compounds as inhibitors against PTP1B in diabetes management. The docking scores of the lead optimized compounds were good; 5280443_121 from apigenin had the best binding score of -9.345 kcal/mol, followed by 5280443_129 with a binding score of -9.200 kcal/mol, and 5280863_177 from kaempferol had a binding score of -8.528 kcal/mol, followed by 5280863_462 with a binding score of -8.338 kcal/mol. The top two lead optimized compounds, docked better than the standard PTP1B inhibitor (-7.155 kcal/mol), suggesting them as potent inhibitors than the standard PTP1B inhibitor. The outcomes of the induced-fit docking were consistent with the increased binding affinity used in the Glide computation of the five conformed poses between the derivatives (5280443_121, 5280443_129, 5280863_177, and 5280863_462) and the protein (PTP1B). Based on the binding fee energies (MM-GBSA), the lead optimized compounds from kaempferol exhibited more stability than those from apigenin. In the pharmacophore development, all the models exhibit good results across the different metrics. The best performing model with five of five matches on a 1.34 and 1.33 phase score was DDRRR_1, DDRRR_2, and DDDRR_1. The average BEDROC value (= 160.9) was 1, while the average EF 1% value across all models was 101. There were no substantial conformational modifications during the MD simulation process, indicating that the apigenin derivatives (5280443_121) was stable in the protein\'s active site in 100 ns. IGF1R, EGFR, INSR, PTPN1, SRC, JAK2, GRB2, BCAR1, and IRS1 are among the 11 potential targets found in the protein-protein interaction (PPI) of A. sativum against PTP1B that may be important in A. sativum\'s defense against PTP1B. Sixty-four (64) pathways were found by KEGG pathway enrichment analysis to be potentially involved in the anti-PTP1B of A. sativum. Consequently, data obtained indicates the effectiveness of the in silico studies in identifying potential lead compounds in A. sativum against PTP1B target.Communicated by Ramaswamy H. Sarma.
摘要：
蛋白酪氨酸磷酸酶1B（PTP1B）已被确定为通过抑制机制开发糖尿病药物的有希望的药物靶标。使用计算方法，本研究调查了大蒜中铅优化的天然化合物对人PTP1B的结合机制。分子对接，诱导配合对接，和结合自由能计算使用薛定谔套件2021-2进行分析。MD模拟,通过Schrödinger的Desmond模块进行基因富集分析，以确定在糖尿病管理中作为PTP1B抑制剂的最佳化合物。前导优化化合物的对接得分良好；芹菜素5280443_121的最佳结合得分为-9.345kcal/mol，其次是5280443_129，结合评分为-9.200kcal/mol，来自山奈酚的5280863_177的结合评分为-8.528kcal/mol，其次是5280863_462，结合评分为-8.338kcal/mol。前两个铅优化化合物，对接优于标准PTP1B抑制剂（-7.155kcal/mol），表明它们是比标准PTP1B抑制剂有效的抑制剂。诱导拟合对接的结果与衍生物（5280443_121、5280443_129、5280863_177和5280863_462）和蛋白质（PTP1B）之间的五个一致姿势的Glide计算中使用的结合亲和力增加一致。基于绑定费能量(MM-GBSA)，山奈酚中的先导优化化合物比芹菜素具有更高的稳定性。在药效团的发展中，所有模型在不同的指标上都表现出良好的结果。在1.34和1.33阶段得分的五个匹配中表现最好的模型是DDRRR_1，DDRRR_2和DDDRR_1。平均BEDROC值（=160.9）为1，而所有模型的平均EF为1％值为101。在MD模拟过程中没有实质性的构象修饰，表明芹菜素衍生物（5280443_121）在100ns内在蛋白质的活性位点稳定。IGF1R,EGFR,INSR,PTPN1,SRC,JAK2，GRB2，BCAR1和IRS1是在马铃薯抗PTP1B的蛋白质-蛋白质相互作用（PPI）中发现的11个潜在靶标之一，这些靶标可能在马铃薯抗PTP1B的防御中很重要。通过KEGG途径富集分析发现六十四（64）个途径可能参与了A的抗PTP1B。因此,获得的数据表明，计算机模拟研究在识别针对PTP1B靶标的A.sativum中潜在的铅化合物方面的有效性。由RamaswamyH.Sarma沟通。
