通过 QSAR、药效团建模、虚拟筛选和分子对接研究发现针对膀胱癌的潜在 FGFR3 抑制剂。
Discovery of potential FGFR3 inhibitors via QSAR, pharmacophore modeling, virtual screening and molecular docking studies against bladder cancer.
机构信息
Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.
出版信息
J Transl Med. 2023 Feb 10;21(1):111. doi: 10.1186/s12967-023-03955-5.
BACKGROUND
Fibroblast growth factor receptor 3 is known as a favorable aim in vast range of cancers, particularly in bladder cancer treatment. Pharmacophore and QSAR modeling approaches are broadly utilized for developing novel compounds for the determination of inhibitory activity versus the biological target. In this study, these methods employed to identify FGFR3 potential inhibitors.
METHODS
To find the potential compounds for bladder cancer targeting, ZINC and NCI databases were screened. Pharmacophore and QSAR modeling of FGFR3 inhibitors were utilized for dataset screening. Then, with regard to several factors such as Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties and Lipinski's Rule of Five, the recognized compounds were filtered. In further step, utilizing the flexible docking technique, the obtained compounds interactions with FGFR3 were analyzed.
RESULTS
The best five compounds, namely ZINC09045651, ZINC08433190, ZINC00702764, ZINC00710252 and ZINC00668789 were selected for Molecular Dynamics (MD) studies. Off-targeting of screened compounds was also investigated through CDD search and molecular docking. MD outcomes confirmed docking investigations and revealed that five selected compounds could make steady interactions with the FGFR3 and might have effective inhibitory potencies on FGFR3.
CONCLUSION
These compounds can be considered as candidates for bladder cancer therapy with improved therapeutic properties and less adverse effects.
背景
成纤维细胞生长因子受体 3 是广泛存在于各种癌症中的一个有利靶点，尤其是在膀胱癌治疗中。配体和定量构效关系建模方法广泛应用于开发新化合物，以确定其对生物靶标的抑制活性。在本研究中，这些方法被用于鉴定 FGFR3 的潜在抑制剂。
方法
为了找到针对膀胱癌的潜在化合物，筛选了 ZINC 和 NCI 数据库。利用 FGFR3 抑制剂的配体和定量构效关系建模方法对数据集进行筛选。然后，根据吸收、分布、代谢、排泄和毒性（ADMET）特性和 Lipinski 的五规则等几个因素，对识别出的化合物进行筛选。在进一步的步骤中，利用柔性对接技术分析了获得的化合物与 FGFR3 的相互作用。
结果
选择了最好的五个化合物，即 ZINC09045651、ZINC08433190、ZINC00702764、ZINC00710252 和 ZINC00668789，进行分子动力学（MD）研究。通过 CDD 搜索和分子对接研究了筛选化合物的脱靶作用。MD 结果证实了对接研究，并表明这五种选定的化合物可以与 FGFR3 形成稳定的相互作用，并且可能对 FGFR3 具有有效的抑制作用。
结论
这些化合物可以被认为是膀胱癌治疗的候选药物，具有改善的治疗特性和较少的不良反应。
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