Department of Chemical Technology, University of Calcutta, 92, A.P.C. Road, Kolkata, 700009, India.
Nutrition and Food Science, Department of Physical Sport Science, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Mol Divers. 2022 Jun;26(3):1697-1714. doi: 10.1007/s11030-021-10297-1. Epub 2021 Sep 5.
In this study, a set of dietary polyphenols was comprehensively studied for the selective identification of the potential inhibitors/modulators for galectin-1. Galectin-1 is a potent prognostic indicator of tumor progression and a highly regarded therapeutic target for various pathological conditions. This indicator is composed of a highly conserved carbohydrate recognition domain (CRD) that accounts for the binding affinity of β-galactosides. Although some small molecules have been identified as galectin-1 inhibitors/modulators, there are limited studies on the identification of novel compounds against this attractive therapeutic target. The extensive computational techniques include potential drug binding site recognition on galectin-1, binding affinity predictions of ~ 500 polyphenols, molecular docking, and dynamic simulations of galectin-1 with selective dietary polyphenol modulators, followed by the estimation of binding free energy for the identification of dietary polyphenol-based galectin-1 modulators. Initially, a deep neural network-based algorithm was utilized for the prediction of the druggable binding site and binding affinity. Thereafter, the intermolecular interactions of the polyphenol compounds with galectin-1 were critically explored through the extra-precision docking technique. Further, the stability of the interaction was evaluated through the conventional atomistic 100 ns dynamic simulation study. The docking analyses indicated the high interaction affinity of different amino acids at the CRD region of galectin-1 with the proposed five polyphenols. Strong and consistent interaction stability was suggested from the simulation trajectories of the selected dietary polyphenol under the dynamic conditions. Also, the conserved residue (His44, Asn46, Arg48, Val59, Asn61, Trp68, Glu71, and Arg73) associations suggest high affinity and selectivity of polyphenols toward galectin-1 protein.
在这项研究中，全面研究了一组膳食多酚，以选择性鉴定半乳糖凝集素-1的潜在抑制剂/调节剂。半乳糖凝集素-1是肿瘤进展的有力预后指标，也是各种病理状况的高度受关注的治疗靶点。该指标由高度保守的碳水化合物识别结构域（CRD）组成，该结构域决定了β-半乳糖苷的结合亲和力。尽管已经鉴定出一些小分子作为半乳糖凝集素-1抑制剂/调节剂，但针对该有吸引力的治疗靶点，鉴定新型化合物的研究有限。广泛的计算技术包括对半乳糖凝集素-1上潜在药物结合位点的识别、对约 500 种多酚的结合亲和力预测、分子对接以及对半乳糖凝集素-1与选择性膳食多酚调节剂的动态模拟，然后估算结合自由能，以鉴定基于膳食多酚的半乳糖凝集素-1调节剂。最初，使用基于深度神经网络的算法对半乳糖凝集素-1的可成药性结合位点和结合亲和力进行预测。此后，通过超高精度对接技术，对半乳糖凝集素-1与多酚化合物的分子间相互作用进行了深入探讨。此外，通过常规的原子 100ns 动力学模拟研究评估了相互作用的稳定性。对接分析表明，不同的多酚化合物与半乳糖凝集素-1的 CRD 区域的不同氨基酸具有高相互作用亲和力。在动态条件下，所选膳食多酚的模拟轨迹表明相互作用具有很强的稳定性。此外，保守残基（His44、Asn46、Arg48、Val59、Asn61、Trp68、Glu71 和 Arg73）的相互作用表明多酚对半乳糖凝集素-1蛋白具有高亲和力和选择性。
