a Centre for Interdisciplinary Research in Basic Sciences , Jamia Millia Islamia , Jamia Nagar, New Delhi , 110025 , India.
b Computational Mechanistic Chemistry and Drug Discovery , Rhodes University , Grahamstown , South Africa.
J Biomol Struct Dyn. 2019 Apr;37(7):1813-1829. doi: 10.1080/07391102.2018.1468282. Epub 2018 May 24.
Microtubule affinity-regulating kinase 4 (MARK4) has recently been identified as a potential drug target for several complex diseases including cancer, diabetes and neurodegenerative disorders. Inhibition of MARK4 activity is an appealing therapeutic option to treat such diseases. Here, we have performed structure-based virtual high-throughput screening of 100,000 naturally occurring compounds from ZINC database against MARK4 to find its potential inhibitors. The resulted hits were selected, based on the binding affinities, docking scores and selectivity. Further, binding energy calculation, Lipinski filtration and ADMET prediction were carried out to find safe and better hits against MARK4. Best 10 compounds bearing high specificity and binding efficiency were selected, and their binding pattern to MARK4 was analyzed in detail. Finally, 100 ns molecular dynamics simulation was performed to evaluate; the dynamics stability of MARK4-compound complex. In conclusion, these selected natural compounds from ZINC database might be potential leads against MARK4, and can further be exploited in drug design and development for associated diseases.
微管亲和调节激酶 4（MARK4）最近被确定为几种复杂疾病（包括癌症、糖尿病和神经退行性疾病）的潜在药物靶点。抑制 MARK4 的活性是治疗此类疾病的一种有吸引力的治疗选择。在这里，我们针对 MARK4 对 ZINC 数据库中的 100,000 种天然化合物进行了基于结构的虚拟高通量筛选，以寻找其潜在的抑制剂。根据结合亲和力、对接评分和选择性选择命中结果。此外，进行结合能计算、Lipinski 过滤和 ADMET 预测，以找到针对 MARK4 的安全且更好的命中结果。选择了 10 个具有高特异性和结合效率的最佳化合物，并详细分析了它们与 MARK4 的结合模式。最后，进行了 100ns 分子动力学模拟，以评估 MARK4-化合物复合物的动力学稳定性。总之，这些来自 ZINC 数据库的天然化合物可能是针对 MARK4 的潜在先导化合物，并可进一步用于相关疾病的药物设计和开发。
J Mol Graph Model. 2015-11
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