Pharmacophore modelling-based screening of natural allosteric EGFR inhibitors using molecular docking, DFT, and molecular dynamics simulations

IF 3.1 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Fatima Munir, Muhammad Bilal Amir, Kashif Hussain, Muhammad Zahid, Jian Zhang
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引用次数: 0

Abstract

The development of allosteric inhibitors is a promising strategy for targeting epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC), especially in cases where orthosteric inhibitors face resistance. However, despite their selective inhibition of EGFR mutations, fourth-generation allosteric inhibitors show limited antiproliferative efficacy without cetuximab. The present study aims to identify potent natural product-derived allosteric inhibitors for NSCLC using a comprehensive approach, including pharmacophore modelling, Lipinski's Rule of Five (Ro5), ADMET profiling, density functional theory, and molecular docking. Experimentally validated EGFR tyrosine kinase inhibitors (TKIs) were used to build a pharmacophore model. The validated pharmacophore model was used to screen the Natural Product Activity and Species Source database. Drug-likeness was assessed using Ro5 and ADMET to predict pharmacokinetic and toxicity profiles for further drug development. Molecular docking studies revealed that the identified natural compounds exhibited more favorable docking scores (−8.74 to −7.87 kcal/mol) than the co-crystallized ligand (−7.32 kcal/mol), indicating significant interactions with the receptor residues. Geometry optimization, electrostatic potential, and frontier molecular orbital analyses were performed to assess potential reactive sites and molecular stability. Molecular dynamics (MD) simulations, subsequent post-MD analyses, and binding free energy calculations provided additional support for these findings. The free-energy landscape revealed stable, favorable binding conformations, suggesting that they may act as allosteric inhibitors. These results highlight the potential of natural compounds to combat resistance to EGFR-TKIs in NSCLC. In particular, compounds 1 and 2 emerged as promising candidates targeting mutant EGFR and warrant further experimental validation as potential leads for NSCLC treatment.
基于药效团模型的天然变构性EGFR抑制剂筛选,使用分子对接、DFT和分子动力学模拟。
针对非小细胞肺癌(NSCLC)的表皮生长因子受体(EGFR)突变,开发变构抑制剂是一种很有前景的策略,尤其是在正构抑制剂面临耐药性的情况下。然而,尽管第四代变构抑制剂选择性抑制EGFR突变,但在没有西妥昔单抗的情况下,其抗增殖效果有限。本研究旨在通过综合方法,包括药效团模型、Lipinski's Rule of 5 (Ro5)、ADMET谱、密度泛函数理论和分子对接,确定有效的天然产物衍生的非小细胞肺癌变构抑制剂。利用经实验验证的EGFR酪氨酸激酶抑制剂(TKIs)构建药效团模型。利用验证的药效团模型筛选天然产物活性和物种源数据库。使用Ro5和ADMET评估药物相似性,以预测药代动力学和毒性特征,为进一步的药物开发提供依据。分子对接研究表明,天然化合物的对接分数(-8.74 ~ -7.87 kcal/mol)高于共结晶配体的对接分数(-7.32 kcal/mol),表明与受体残基有显著的相互作用。通过几何优化、静电势和前沿分子轨道分析来评估潜在的反应位点和分子稳定性。分子动力学(MD)模拟,随后的MD后分析和结合自由能计算为这些发现提供了额外的支持。自由能图显示出稳定、有利的结合构象,表明它们可能具有变构抑制剂的作用。这些结果强调了天然化合物在非小细胞肺癌中对抗EGFR-TKIs耐药的潜力。特别是,化合物1和2作为靶向突变EGFR的有希望的候选者,值得进一步的实验验证,作为治疗非小细胞肺癌的潜在线索。
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来源期刊
Journal of molecular graphics & modelling
Journal of molecular graphics & modelling 生物-计算机:跨学科应用
CiteScore
5.50
自引率
6.90%
发文量
216
审稿时长
35 days
期刊介绍: The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.
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