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Structural, QSAR, machine learning and molecular docking studies of 5-thiophen-2-yl pyrazole derivatives as potent and selective cannabinoid-1 receptor antagonists
New Journal of Chemistry ( IF 2.7 ) Pub Date : 2021-08-23 , DOI: 10.1039/d1nj02261j
Riadh Hanachi 1 , Ridha Ben Said 1, 2 , Hamza Allal 3, 4 , Seyfeddine Rahali 2, 5 , Mohammed A. M. Alkhalifah 6 , Faisal Alresheedi 7 , Bahoueddine Tangour 5 , Majdi Hochlaf 8
Affiliation  

We performed a structural study followed by theoretical analysis of the chemical descriptors and biological activity of a series of 5-thiophen-2-yl pyrazole derivatives as potent and selective cannabinoid-1 (CB1) receptor antagonists. The structures and molecular properties of these compounds were obtained using a DFT-D3 (B3LYP(+D3)) approach in conjunction with the 6-311G(d,p) basis set. We also derived the physicochemical properties and the binding of these derivatives interacting with the CB1 receptor. Computations show that all of them present the same molecular subunit structure, miming that of rimonabant, an efficient CB1 antagonist. The 3D structure of this subunit, important for the interaction with the receptor, is strongly influenced by long-range interactions. Moreover, we derived a QSAR equation to model the biological activity of this series. Close agreement with experimental data is found. Moreover, molecular docking studies were carried out between the most active compound and both the inactive and active states of the CB1 receptor. Results reveal high affinity between this compound and the inactive CB1 conformation, mainly governed by van der Waals forces. In conclusion, our work suggests that this compound could be a novel efficient inhibitor of CB1.

中文翻译:

作为有效和选择性大麻素 1 受体拮抗剂的 5-噻吩-2-基吡唑衍生物的结构、QSAR、机器学习和分子对接研究

我们进行了结构研究,然后对一系列作为有效和选择性大麻素 1 (CB1) 受体拮抗剂的 5-噻吩-2-基吡唑衍生物的化学描述符和生物活性进行了理论分析。这些化合物的结构和分子特性是使用 DFT-D3 (B3LYP(+D3)) 方法结合 6-311G(d,p) 基组获得的。我们还推导出了这些衍生物与 CB1 受体相互作用的物理化学特性和结合。计算表明,它们都具有相同的分子亚基结构,模拟了有效的 CB1 拮抗剂利莫那班的分子亚基结构。该亚基的 3D 结构对于与受体的相互作用很重要,受到长程相互作用的强烈影响。而且,我们推导出 QSAR 方程来模拟该系列的生物活性。发现与实验数据非常吻合。此外,在活性最强的化合物与 CB1 受体的非活性和活性状态之间进行了分子对接研究。结果表明,该化合物与主要受范德华力控制的非活性 CB1 构象之间具有高亲和力。总之,我们的工作表明该化合物可能是 CB1 的新型有效抑制剂。
更新日期:2021-09-08
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