Department of Chemistry, School of Advanced Science, Vellore Institute of Technology, Vellore, India.
Department of Biotechnology, School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
J Comput Chem. 2021 Sep 15;42(24):1736-1749. doi: 10.1002/jcc.26712. Epub 2021 Jul 2.
Drug resistance in tuberculosis is major threat to human population. In the present investigation, we aimed to identify novel and potent benzimidazole molecules to overcome the resistance management. A series of 20 benzimidazole derivatives were examined for its activity as selective antitubercular agents. Initially, AutodockVina algorithm was performed to assess the efficacy of the molecules. The results are further enriched by redocking by means of Glide algorithm. The binding free energies of the compounds were then calculated by MM-generalized-born surface area method. Molecular docking studies elucidated that benzimidazole derivatives has revealed formation of hydrogen bond and strong binding affinity in the active site of Mycobacterium tuberculosis protein. Note that ARG308, GLY189, VAL312, LEU403, and LEU190 amino acid residues of Mycobacterium tuberculosis protein PrpR are involved in binding with ligands of benzimidazoles. Interestingly, the ligands exhibited same binding potential to the active site of protein complex PrpR in both the docking programs. In essence, the result portrays that benzimidazole derivatives such as 1p, 1q, and 1 t could be potent and selective antitubercular agents than the standard drug isoniazid. These compounds were then subjected to molecular dynamics simulation to validate the dynamics activity of the compounds against PrpR. Finally, the inhibitory behavior of compounds was predicted using a machine learning algorithm trained on a data collection of 15,000 compounds utilizing graph-based signatures. Overall, the study concludes that designed benzimidazoles can be employed as antitubercular agents. Indeed, the results are helpful for the experimental biologists to develop safe and non-toxic drugs against tuberculosis.
结核分枝杆菌的耐药性是人类面临的主要威胁。在本研究中，我们旨在鉴定新的有效苯并咪唑类分子以克服耐药性管理。评估了一系列 20 种苯并咪唑衍生物作为选择性抗结核药物的活性。首先，使用 AutodockVina 算法评估分子的功效。然后通过 Glide 算法进行再对接来进一步丰富结果。然后通过 MM-广义Born 表面积方法计算化合物的结合自由能。分子对接研究表明，苯并咪唑衍生物与结核分枝杆菌蛋白 PrpR 的活性部位形成氢键并具有很强的结合亲和力。值得注意的是，结核分枝杆菌蛋白 PrpR 的 ARG308、GLY189、VAL312、LEU403 和 LEU190 氨基酸残基参与与苯并咪唑配体的结合。有趣的是，配体在两种对接程序中均显示出与蛋白复合物 PrpR 活性部位相同的结合潜力。本质上，结果表明，苯并咪唑衍生物如 1p、1q 和 1t 可能比标准药物异烟肼更有效和更具选择性的抗结核药物。然后对这些化合物进行分子动力学模拟，以验证它们对 PrpR 的动态活性。最后，使用基于图形签名的 15000 种化合物数据集训练的机器学习算法预测化合物的抑制行为。总的来说，该研究得出结论，设计的苯并咪唑类化合物可用作抗结核药物。事实上，这些结果有助于实验生物学家开发针对结核病的安全无毒药物。
