Athar Mohd, Lone Mohsin Y, Khedkar Vijay M, Radadiya Ashish, Shah Anamik, Jha Prakash C
School of Chemical Sciences, Central University of Gujarat, Gandhinagar 382030, Gujarat, India.
School of Health Sciences, Discipline of Pharmaceutical Sciences, University of KwaZulu-Natal, Westville, Durban 4000. South Africa.
Comb Chem High Throughput Screen. 2017;20(8):682-695. doi: 10.2174/1386207320666170509151253.
Vinca domain of tubulin protein is the potential target for different microtubule targeting drugs (MTD). However, its binding mechanism and structure-activityrelationship (SAR) is not well understood in terms of ligand-receptor interactions and structure functionality requirements. This limits the exploitation of vinca domain for developing novel clinical leads. Herein, as a progressive step towards the exploration of this target, we rendered the in-silico insight through the development of a robust pharmacophore model followed by the QSAR, Molecular Docking and Molecular Dynamics (MD) simulations. Furthermore, the study was undertaken to identify potent inhibitors that can inhibit vinca domain of tubulin.
Utilizing the well-defined tubulin polymerization inhibition activities, common pharmacophore hypotheses were constructed and scored for their rankings. The hypotheses were validated by 3D-Atom based QSAR and tested for various statistically relevant metrices. Thereafter, virtual screening was performed with ZINC natural product database and the screened hits were evaluated for structure-based studies via molecular docking and molecular dynamics simulations.
The predictive 3D-QSAR based pharmacophore model consists of two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one hydrophobic (H) group. Significance of the model was reflected from the statistical parameters viz. r2 = 0.98, q2 = 0.72, F = 562.9, RMSE = 0.11 and Pearson-R = 0.87. Further, the docking scores of the retrieved hits deciphered that the ligands were adequately bound in the pocket. Moreover, RMSD fluctuations of protein (1.0 to 1.75A) and ligand (0.3 to 2.3 Å) in molecular dynamics simulations insinuate towards the conformational and interactions stability of the complexes.
The quantitative pharmacophore model was developed from range of natural product scaffolds in order to incorporate all the complimentary features accountable for inhibition. The obtained hits were found to occupy similar binding region and superimpose well over the reference ligand. Therefore, it can be concluded that hierarchical combination of methods exploited in this study can steer the identification of novel scaffolds. Moreover, the rendered hit molecules could serve as potential inhibitory leads for the development of improved inhibitors targeting Vinca domain.
微管蛋白的长春花结构域是不同微管靶向药物（MTD）的潜在靶点。然而，就配体 - 受体相互作用和结构功能要求而言，其结合机制和构效关系（SAR）尚未得到充分理解。这限制了利用长春花结构域开发新型临床先导物。在此，作为探索该靶点的一个进步步骤，我们通过开发一个强大的药效团模型，随后进行定量构效关系（QSAR）、分子对接和分子动力学（MD）模拟，提供了计算机模拟的见解。此外，该研究旨在鉴定能够抑制微管蛋白长春花结构域的强效抑制剂。
利用明确的微管蛋白聚合抑制活性，构建了常见的药效团假设并对其排名进行评分。通过基于3D原子的QSAR对这些假设进行验证，并针对各种统计学相关指标进行测试。此后，使用ZINC天然产物数据库进行虚拟筛选，并通过分子对接和分子动力学模拟对筛选出的命中物进行基于结构的研究评估。
基于预测性3D - QSAR的药效团模型由两个氢键受体（A）、两个氢键供体（D）和一个疏水（H）基团组成。该模型的显著性从统计参数中得以体现，即r2 = 0.98，q2 = 0.72，F = 562.9，RMSE = 0.11以及Pearson - R = 0.87。此外，检索到的命中物的对接分数表明配体在口袋中结合良好。而且，分子动力学模拟中蛋白质（1.0至1.75埃）和配体（0.3至2.3埃）的均方根偏差（RMSD）波动暗示了复合物的构象和相互作用稳定性。
从一系列天然产物支架开发了定量药效团模型，以纳入所有负责抑制的互补特征。发现获得的命中物占据相似的结合区域，并且与参考配体很好地重叠。因此，可以得出结论，本研究中采用的方法的分层组合可以指导新型支架的鉴定。此外，所提供的命中分子可作为开发针对长春花结构域的改进抑制剂的潜在抑制先导物。
