Nedunchezhian Dharani, Langeswaran Kulanthaivel, Santhoshkumar Sundar
Department of Biotechnology and Bioinformatics,Bishop Heber College,Bharathidasan University,Tiruchirapalli,Tamil Nadu,India.
Cancer Genetics and Molecular Biology Laboratory, Department of Bioinformatics, Science Campus, Alagappa University, Karaikudi, Tamil Nadu, India.
Bioinformation. 2019 Jun 15;15(6):419-424. doi: 10.6026/97320630015419. eCollection 2019.
Identification of tyrosine Fyn kinase inhibitor is recognized as an effective and feasible therapeutic measure in reducing consequences of memory loss disorder Alzheimer's. The present investigation has been attempted with an objective to find out a novel potent inhibitor with similar homological structure to Fyn kinase using structure based in silico screening measure. Such derived structure was compared with natural data base pool and were systematically analyzed. Ligand based interaction was also tested and evaluated. We applied a molecular dynamic simulation technique to validate the stability of the identified complexes and to understand the ligand binding mechanism. Results provide information on the characteristics of novel and potent inhibitor for tyrosinase Fyn kinase protein so as to develop an innovative strategy to treat AD.
鉴定酪氨酸Fyn激酶抑制剂被认为是减轻记忆丧失疾病阿尔茨海默病后果的一种有效且可行的治疗措施。本研究旨在通过基于结构的计算机筛选方法，寻找一种与Fyn激酶具有相似同源结构的新型强效抑制剂。将这种推导得到的结构与天然数据库进行比较并进行系统分析。还对基于配体的相互作用进行了测试和评估。我们应用分子动力学模拟技术来验证所鉴定复合物的稳定性，并了解配体结合机制。结果提供了有关酪氨酸酶Fyn激酶蛋白新型强效抑制剂特性的信息，以便制定治疗阿尔茨海默病的创新策略。
