Kumar Pawan, Kumari Indu, Prasad Rajendra, Ray Shashikant, Banerjee Atanu, Prakash Amresh
School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
Amity Institute of Biotechnology, Amity University Haryana, Gurugram, India.
Mol Divers. 2025 Jan 9. doi: 10.1007/s11030-024-11078-2.
The ATP-binding cassette transporter superfamily plays a pivotal role in cellular detoxification and drug efflux. ATP-binding cassette subfamily G member 2 (ABCG2) referred to as the Breast cancer resistance protein has emerged as a key member involved in multidrug resistance displayed by cancer cells. Understanding the molecular basis of substrate and inhibitor recognition, and binding within the transmembrane domain of ABCG2 is crucial for the development of effective therapeutic strategies. Herein, utilizing state-of-the-art molecular docking algorithms and molecular dynamic (MD) simulations, molecular binding of substrates and inhibitors with ABCG2 are defined, distinctly. We performed extensive virtual screening of Drugbank to identify the potential candidates, and MD simulations of docked complexes were carried out in POPC lipid bilayer. Further, the binding affinities of compounds were estimated by free binding energy employing MM-GBSA. To gain deeper insight into the binding affinities and molecular characteristics contributing to inhibitory potential of certain substrates, we included some well-known inhibitors, like Imatinib, Tariquidar, and Ko 143, in our analysis. Docking results show three compounds, Docetaxel > Tariquidar > Tezacaftor having the highest binding affinities (≤ 12.00 kcal/mol) for ABCG2. Remarkably, MM-GBSA results suggest the most stable binding of Tariquidar with ABCG2 as compared to the other inhibitors. Furthermore, our results suggested that Docetaxel, Ozanimod, Pitavastatin, and Tezacaftor have the strongest affinity for the drug-binding site(s) of ABCG2. These results provide valuable insights into the key residues that may govern substrate/inhibitor recognition, shedding light on the molecular determinants influencing substrate specificity, transport kinetics, and ABCG2-mediated drug efflux.
ATP结合盒转运蛋白超家族在细胞解毒和药物外排中起关键作用。ATP结合盒亚家族G成员2（ABCG2），即乳腺癌耐药蛋白，已成为参与癌细胞多药耐药的关键成员。了解ABCG2跨膜结构域内底物和抑制剂识别及结合的分子基础对于开发有效的治疗策略至关重要。在此，利用最先进的分子对接算法和分子动力学（MD）模拟，明确确定了底物和抑制剂与ABCG2的分子结合。我们对药物银行进行了广泛的虚拟筛选以识别潜在候选物，并在POPC脂质双层中对对接复合物进行了MD模拟。此外，采用MM-GBSA通过自由结合能估计化合物的结合亲和力。为了更深入地了解有助于某些底物抑制潜力的结合亲和力和分子特征，我们在分析中纳入了一些知名抑制剂，如伊马替尼、 tariquidar和Ko 143。对接结果显示，多西他赛＞tariquidar＞替扎考昔对ABCG2具有最高的结合亲和力（≤12.00千卡/摩尔）。值得注意的是，MM-GBSA结果表明，与其他抑制剂相比，tariquidar与ABCG2的结合最稳定。此外，我们的结果表明，多西他赛、奥扎莫德、匹伐他汀和替扎考昔对ABCG2的药物结合位点具有最强的亲和力。这些结果为可能控制底物/抑制剂识别的关键残基提供了有价值的见解，揭示了影响底物特异性、转运动力学和ABCG2介导的药物外排的分子决定因素。
