Samanta Priyanka, Doerksen Robert J
Department of BioMolecular Sciences, School of Pharmacy, University of Mississippi, University, MS, USA, 38677-1848.
Research Institute of Pharmaceutical Sciences, School of Pharmacy, University of Mississippi, University, MS, USA, 38677-1848.
Appl Sci (Basel). 2024 May;14(10). doi: 10.3390/app14104277. Epub 2024 May 17.
Bacterial infections are the second-leading cause of death, globally. The prevalence of antibacterial resistance has kept the demand strong for the development of new and potent drug candidates. It has been demonstrated that Src protein tyrosine kinases (TKs) play an important role in the regulation of inflammatory responses to tissue injury, which can trigger the onset of several severe diseases. We carried out a search for novel Src protein TK inhibitors, commencing from reported highly potent anti-bacterial compounds obtained using the Mannich reaction, using a combination of e-pharmacophore modeling, virtual screening, ensemble docking, and core hopping. The top-scoring compounds from ligand-based virtual screening were modified using protein structure-based design approaches and their binding to the Src homology-2 domain of p56 TK was predicted using ensemble molecular docking. We have prepared a database of 202 small molecules and have identified 6 novel top hits that can be subjected to further investigation. We have also performed ADMET property prediction for the hit compounds. This combined computer-aided drug design approach can serve as a starting point for identifying novel TK inhibitors that could be further subjected to studies and validation of antimicrobial activity.
细菌感染是全球第二大致死原因。抗菌耐药性的普遍存在使得对新型高效候选药物的开发需求强劲。已证明Src蛋白酪氨酸激酶(TKs)在调节对组织损伤的炎症反应中起重要作用,而这种反应可引发多种严重疾病的发作。我们从使用曼尼希反应获得的已报道的高效抗菌化合物开始,结合电子药效团建模、虚拟筛选、集成对接和核心跳跃,开展了新型Src蛋白TK抑制剂的搜寻工作。基于配体的虚拟筛选中得分最高的化合物采用基于蛋白质结构的设计方法进行修饰,并使用集成分子对接预测它们与p56 TK的Src同源2结构域的结合情况。我们制备了一个包含202个小分子的数据库,并鉴定出6个可进一步研究的新型顶级命中物。我们还对命中化合物进行了ADMET性质预测。这种计算机辅助药物设计的综合方法可作为识别新型TK抑制剂的起点,这些抑制剂可进一步进行抗菌活性研究和验证。