Centre for Molecular Modelling, CSIR-Indian Institute of Chemical Technology, Hyderabad, 500007, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
Mol Divers. 2022 Jun;26(3):1675-1695. doi: 10.1007/s11030-021-10296-2. Epub 2021 Sep 1.
Development of potential antitubercular molecules is a challenging task due to the rapidly emerging drug-resistant strains of Mycobacterium tuberculosis (M.tb). Structure-based approaches hold greater benefit in identifying compounds/drugs with desired polypharmacological profiles. These methods can be employed based on the knowledge of protein binding sites to identify the complementary ligands. In this study, polypharmacology guided computational drug repurposing approach was applied to identify potential antitubercular drugs. 20 important druggable protein targets in M.tb were considered from the target library of Molecular Property Diagnostic Suite-Tuberculosis (MPDS- http://mpds.neist.res.in:8084 ) for virtual screening. FDA approved drugs were collected, preprocessed and docked in the active sites of the 20 M.tb targets. The top 300 drug molecules from each target (20 × 300) were filtered-in and subsequently screened for possible antitubercular and antimycobacterial activity using PASS tool. Using this approach, 34 drugs with predicted antitubercular and anti-mycobacterial activity were identified along with good binding affinity against multiple M.tb targets. Interestingly, 21 out of the 34 identified drugs are antibiotics while 4 drug molecules (nitrofural, stavudine, quinine and quinidine) are non-antibiotics showing promising predicted antitubercular activity. Most of these molecules have the similar privileged antimycobacterial drugs scaffold. Further drug likeness properties were calculated to get deeper insights to M.tb lead molecules. Interestingly, it was also observed that the drugs identified from the study are under different stages of drug discovery (i.e., in vitro, clinical trials) for the effective treatment of various diseases including cancer, degenerative diseases, dengue virus infection, tuberculosis, etc. Krasavin et al., 2017 synthesized nitrofuran analogues with appreciable MICs (22-23 µM) against M.tb H37Rv. These experiments further add to the credibility of the drugs identified in this study (TB).
由于结核分枝杆菌(M.tb)耐药菌株的迅速出现,开发潜在的抗结核药物是一项具有挑战性的任务。基于结构的方法在确定具有所需多药效学特征的化合物/药物方面具有更大的优势。这些方法可以根据蛋白质结合位点的知识来识别互补配体。在这项研究中,应用多药效学指导的计算药物再利用方法来鉴定潜在的抗结核药物。从分子性质诊断套件-结核(MPDS-http://mpds.neist.res.in:8084)的靶标库中选择了 20 个重要的结核分枝杆菌可成药靶标进行虚拟筛选。收集了 FDA 批准的药物,进行预处理并在 20 个结核分枝杆菌靶标的活性部位对接。从每个靶标(20×300)中筛选出前 300 个药物分子(20×300),并使用 PASS 工具筛选可能的抗结核和抗分枝杆菌活性。通过这种方法,鉴定了 34 种具有预测抗结核和抗分枝杆菌活性的药物,并且对多个结核分枝杆菌靶标具有良好的结合亲和力。有趣的是,在所鉴定的 34 种药物中,有 21 种是抗生素,而 4 种药物分子(硝呋拉嗪、司他夫定、奎宁和奎尼丁)是非抗生素,显示出有希望的预测抗结核活性。这些分子中的大多数都具有相似的特权抗分枝杆菌药物支架。进一步计算药物相似性性质,以更深入地了解结核分枝杆菌的先导分子。有趣的是,还观察到,从这项研究中鉴定的药物处于不同的药物发现阶段(即在体外、临床试验),用于有效治疗各种疾病,包括癌症、退行性疾病、登革热病毒感染、结核病等。Krasavin 等人,2017 年合成了具有可观 MIC(22-23µM)的硝呋拉嗪类似物,对结核分枝杆菌 H37Rv 有抑制作用。这些实验进一步增加了本研究(TB)中鉴定药物的可信度。
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