Phytochemical-based drug designing against efflux-pump of ESKAPE pathogen to combat multidrug-resistant: an in silico study

The Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter species are ciphered as ESKAPE pathogens leading agents for multidrug resistance (MDR) related infections. The current research study used kanamycin nucleotidyltransferase (PDB ID: 1KNY), OXA-24 class D beta-lactamase (PDB ID: 3ZNT), efflux pump proteins as a target to identify potential inhibitor phytochemical for ameliorating antimicrobial resistance caused by ESKAPE pathogens. A total of 61 MDR genes of ESKAPE pathogens were scrutinized phylogenetically and protein–protein interaction (PPIs) analysis were performed. The target proteins for structure-based drug design were culled based on functional partners of efflux pump proteins obtained after PPIs analysis in all ESKAPE pathogens. We deployed a comprehensive sequential filtering approach including high throughput virtual screening of an in-house created bioactive phytochemicals library from the IMPPAT database. First, a molecular docking-based high throughput virtual screening process, followed by meticulous filtering of hits based on binding energy and detailed active-site interaction analysis was performed on each target protein separately. During this stage, native ligands of the target proteins were deployed as a control ligand and for docking protocol validation. These 50 top phytochemicals against both proteins were culled. Then filtration of hits was done based on pharmacokinetics, toxicity and bioactivity of phytochemicals. The retained phytochemicals against each protein were analyzed through density functional theory (DFT) to check potential reactivity. After, analyzing DFT-based energy calculations final lead phytochemicals were selected. The lead phytochemical stability within respective active-site and dynamic behavior was analyzed through molecular dynamic (MD) simulations and principal component analysis (PCA). In this way, diosgenin and paulownin phytochemicals were identified as a lead inhibitor ligand against 1KNY and 3ZNT target receptors, respectively. The 1KNY–diosgenin and 3ZNT–paulownin complexes exhibited binding energies of −8.1 kcal/mol and −9.0 kcal/mol, respectively, forming hydrogen bonds with specific key residues (1KNY-Arg22, Ser105, Thr186) and (3ZNT-Trp221, Tyr 112, Met114) displaying stable dynamic behavior during 100 ns MD simulation, with DFT-based energy gaps of −0.254 52 eV and −0.195 87 eV, respectively, suggesting greater stability compared to control ligands. The diosgenin and paulownin phytochemicals are promising starting natural candidates for drug development against multidrug-resistant infections cure.

屎肠球菌（Enterococcus faecium）、金黄色葡萄球菌（Staphylococcus aureus）、肺炎克雷伯菌（Klebsiella pneumoniae）、鲍曼不动杆菌（Acinetobacter baumannii）、铜绿假单胞菌（Pseudomonas aeruginosa）及肠杆菌属（Enterobacter）物种被归类为ESKAPE病原体（ESKAPE pathogens），是多重耐药（MDR）相关感染的主要致病菌。本研究以卡那霉素核苷酸转移酶（PDB ID: 1KNY）、OXA-24型D类β-内酰胺酶（PDB ID: 3ZNT）及外排泵蛋白为靶标，旨在筛选可缓解ESKAPE病原体引发的抗菌药物耐药性的潜在植物化学抑制剂。研究人员对ESKAPE病原体的共计61个多重耐药基因进行了系统发育分析，并开展了蛋白质相互作用（PPIs）分析。基于所有ESKAPE病原体经PPIs分析得到的外排泵蛋白功能伙伴，筛选出用于基于结构的药物设计的靶标蛋白。本研究采用了一套完整的递进式筛选策略，包括对从IMPPAT数据库自主构建的生物活性植物化学物库进行高通量虚拟筛选。首先，针对每个靶标蛋白分别开展基于分子对接的高通量虚拟筛选流程，随后依据结合能与细致的活性位点相互作用分析对命中化合物进行严格筛选。此阶段以靶标蛋白的天然配体作为对照配体，用于对接方案的验证。最终筛选得到针对两种靶标蛋白的前50种植物化学物。随后依据植物化学物的药代动力学、毒性与生物活性对命中化合物进行进一步筛选。通过密度泛函理论（DFT）分析针对各靶标蛋白保留的植物化学物，以评估其潜在反应活性。在完成基于DFT的能量计算分析后，最终筛选得到先导植物化学物。通过分子动力学（MD）模拟与主成分分析（PCA），分析先导植物化学物在对应活性位点内的稳定性与动态行为。据此，分别确定薯蓣皂苷元（diosgenin）与泡桐素（paulownin）为针对1KNY与3ZNT靶标受体的先导抑制配体。1KNY-薯蓣皂苷元复合物与3ZNT-泡桐素复合物的结合能分别为-8.1 kcal/mol与-9.0 kcal/mol，分别与关键残基（1KNY的Arg22、Ser105、Thr186及3ZNT的Trp221、Tyr112、Met114）形成氢键，在100 ns的MD模拟中展现出稳定的动态行为；二者的DFT能隙分别为-0.25452 eV与-0.19587 eV，表明其稳定性优于对照配体。薯蓣皂苷元与泡桐素是极具潜力的天然候选化合物，可用于开发治疗多重耐药感染的药物。