Parves Md Rimon, Riza Yasir Mohamed, Alam Sanjida, Jaman Sadia
Department of Biochemistry and Biotechnology, Faculty of Basic Medical and Pharmaceutical Sciences, University of Science and Technology Chittagong (USTC), Foy's Lake, Khulshi, 4202, Chittagong, Bangladesh.
Department of Genetic Engineering & Biotechnology, Jagannath University, Dhaka, 100, Bangladesh.
J Mol Model. 2022 Dec 23;29(1):17. doi: 10.1007/s00894-022-05427-x.
Inhibition of vascular endothelial growth factor receptor 2 (VEGFR-2) tyrosine kinase by small molecules has become a promising target in the treatment of cancer.
In this study, we approached pharmacophore modeling coupled with a structure-based virtual screening workflow to identify the potent inhibitors.
The top selected hit compounds have been rescored using the MM/GBSA approach. To understand the molecular reactivity, electronic properties, and stability of those inhibitors, we have employed density functional theory and molecular dynamics. Following that, the best 21 hit compounds have been further post-processed with a Quantum ligand partial charge-based rescoring process and further validated by implementing molecular dynamics simulation.
The ten hit compounds have been hypothesized and considered as potent inhibitors of VEGFR-2 tyrosine kinase. This study also signifies the contribution of QM-based ligand partial charge, which is more accurate in predicting reliable free binding energy and filtering large ligand libraries to hit optimization, rather than assigning those of the force field-based method. From the binding pattern analysis of all the complexes, amino acids, such as Glu885, Cys919, Cys1045, Thr916, Thr919, and Asp1046, were found to have comprehensive interaction with the hit compounds.
Hence, this could prove to be useful as a potential inhibition site of the VEGFR-2 tyrosine kinase domain for future researchers. Moreover, this study also emphasizes the conformational changes upon ATP binding, based on either the receptor's rigidity or flexibility.
小分子抑制血管内皮生长因子受体2(VEGFR - 2)酪氨酸激酶已成为癌症治疗中一个有前景的靶点。
在本研究中,我们采用药效团模型结合基于结构的虚拟筛选工作流程来鉴定强效抑制剂。
使用MM/GBSA方法对筛选出的顶级命中化合物重新评分。为了解这些抑制剂的分子反应性、电子性质和稳定性,我们采用了密度泛函理论和分子动力学。随后,对最佳的21种命中化合物进一步进行基于量子配体部分电荷的重新评分后处理,并通过分子动力学模拟进一步验证。
已推测出十种命中化合物并将其视为VEGFR - 2酪氨酸激酶的强效抑制剂。本研究还表明了基于量子力学的配体部分电荷的贡献,其在预测可靠的自由结合能和筛选大型配体库以优化命中方面比基于力场的方法更准确。从所有复合物的结合模式分析中发现,诸如Glu885、Cys919、Cys1045、Thr916、Thr919和Asp1046等氨基酸与命中化合物有全面的相互作用。
因此,这可能被证明对未来研究人员作为VEGFR - 2酪氨酸激酶结构域的潜在抑制位点有用。此外,本研究还强调了基于受体的刚性或柔性,ATP结合时的构象变化。