Abstract：
BACKGROUND: Chronic inflammation is a risk factor for diabetes, but it can also be a complication of diabetes, leading to severe diabetes and causing many other clinical manifestations. Inflammation is a major emerging complication in both type I and type II diabetes, which causes increasing interest in targeting inflammation to improve and control diabetes. Diabetes with insulin resistance and impaired glucose utilization in humans and their underlying mechanism is not fully understood. But a growing understanding of the intricacy of the insulin signaling cascade in diabetic inflammatory cells reveals potential target genes and their proteins responsible for severe insulin resistance. With this baseline concept, the current project explores the binding affinities of the hyaluronic acid anti-diabetic compounds conjugates to such target proteins in diabetic inflammatory cells and their molecular geometries. A range of 48 anti-diabetic compounds was screened against aldose reductase binding pocket 3 protein target through in silico molecular docking, and results revealed that three compounds viz, metformin (CID:4091), phenformin (CID:8249), sitagliptin (CID:4,369,359), possess significant binding affinity out of 48 chosen drugs. Further, these three anti-diabetic compounds were conjugated with hyaluronic acid (HA), and their binding affinity and their molecular geometrics towards aldose reductase enzyme were screened compared with the free form of the drug. The molecular geometries of three shortlisted drugs (metformin, phenformin, sitagliptin) and their HA conjugates were also explored through density functional theory studies, and it proves their good molecular geometry towards pocket 3 of aldose reductase target. Further, MD simulation trajectories affirm that HA conjugates possess good binding affinity and simulation trajectories with protein target aldose reductase than a free form of the drug. Our current study unravels the new mechanism of drug targeting for diabetes through HA conjugation for inflammatory diabetes. HA conjugates act as novel drug candidates for treating inflammatory diabetes; however, it needs further human clinical trials.
METHODS: For ligand structure, PubChem, ACD chem sketch, and online structure file generator platform are utilized for ligand preparation. Target protein aldose reductase obtained from protein database (PDB). For molecular docking analysis, AutoDock Vina (Version 4) was utilized. pKCSM online server used to predict ADMET properties of the above three shortlisted drugs from the docking study. Using mol-inspiration software (version 2011.06), three shortlisted compounds\' bioactivity scores were predicted. DFT analysis for three shortlisted anti-diabetic drugs and their hyaluronic acid conjugates were calculated using a functional B3LYP set of Gaussian 09 software. Molecular dynamics simulation calculations for six chosen protein-ligand complexes were done through YASARA dynamics software and AMBER14 force field.
METHODS: For ligand structure, PubChem, ACD chem sketch, and online structure file generator platform are utilized for ligand preparation. Target protein aldose reductase obtained from protein database (PDB). For molecular docking analysis, AutoDock Vina (Version 4) was utilized. pKCSM online server used to predict ADMET properties of the above three shortlisted drugs from the docking study. Using mol-inspiration software (version 2011.06), three shortlisted compounds\' bioactivity scores were predicted. DFT analysis for three shortlisted anti-diabetic drugs and their hyaluronic acid conjugates were calculated using a functional B3LYP set of Gaussian 09 software. Molecular dynamics simulation calculations for six chosen protein-ligand complexes were done through YASARA dynamics software and AMBER14 force field.
摘要：
背景：慢性炎症是糖尿病的危险因素，但它也可能是糖尿病的并发症，导致严重的糖尿病并引起许多其他临床表现。炎症是I型和II型糖尿病的主要新兴并发症，这引起了人们对靶向炎症以改善和控制糖尿病的兴趣。人类中具有胰岛素抵抗和葡萄糖利用受损的糖尿病及其潜在机制尚未完全了解。但是，对糖尿病炎症细胞中胰岛素信号级联的复杂性的日益了解揭示了导致严重胰岛素抵抗的潜在靶基因及其蛋白质。有了这个基线概念，本项目探讨了透明质酸抗糖尿病化合物与糖尿病炎症细胞中这些靶蛋白的结合亲和力及其分子几何形状。通过硅胶分子对接，针对醛糖还原酶结合口袋3蛋白靶标筛选了48种抗糖尿病化合物，结果表明，三种化合物，二甲双胍（CID：4091），苯乙双胍（CID：8249），西格列汀（CID：4,369,359），在48种选择的药物中具有显著的结合亲和力。Further,这三种抗糖尿病化合物与透明质酸（HA）缀合，与游离形式的药物相比，筛选了它们对醛糖还原酶的结合亲和力和分子几何形状。三种入围药物(二甲双胍，苯乙双胍,西格列汀）及其HA缀合物也通过密度泛函理论研究进行了探索，它证明了它们对醛糖还原酶靶标的口袋3的良好分子几何形状。Further,MD模拟轨迹确认HA缀合物比药物的游离形式具有与蛋白质靶标醛糖还原酶的良好结合亲和力和模拟轨迹。我们目前的研究揭示了通过HA结合治疗炎症性糖尿病的药物靶向糖尿病的新机制。HA缀合物作为治疗炎性糖尿病的新型候选药物;然而,它需要进一步的人体临床试验。
方法：对于配体结构，PubChem,ACD化学草图,和在线结构文件生成器平台用于配体制备。从蛋白质数据库(PDB)获得的靶蛋白醛糖还原酶。对于分子对接分析，利用了AutoDockVina(版本4)。pKCSM在线服务器用于预测来自对接研究的上述三种入围药物的ADMET特性。使用mol-inspination软件（2011.06版），预测了三个入围化合物的生物活性评分。使用高斯09软件的功能性B3LYP集计算三种入围抗糖尿病药物及其透明质酸缀合物的DFT分析。通过YASARA动力学软件和AMBER14力场对6种选定的蛋白质-配体复合物进行了分子动力学模拟计算。
方法：对于配体结构，PubChem,ACD化学草图,和在线结构文件生成器平台用于配体制备。从蛋白质数据库(PDB)获得的靶蛋白醛糖还原酶。对于分子对接分析，利用了AutoDockVina(版本4)。pKCSM在线服务器用于预测来自对接研究的上述三种入围药物的ADMET特性。使用mol-inspination软件（2011.06版），预测了三个入围化合物的生物活性评分。使用高斯09软件的功能性B3LYP集计算三种入围抗糖尿病药物及其透明质酸缀合物的DFT分析。通过YASARA动力学软件和AMBER14力场对6种选定的蛋白质-配体复合物进行了分子动力学模拟计算。
