Abstract：
This research delves into the exploration of the potential of tocopherol-based nanoemulsion as a therapeutic agent for cardiovascular diseases (CVD) through an in-depth molecular docking analysis. The study focuses on elucidating the molecular interactions between tocopherol and seven key proteins (1O8a, 4YAY, 4DLI, 1HW9, 2YCW, 1BO9 and 1CX2) that play pivotal roles in CVD development. Through rigorous in silico docking investigations, assessment was conducted on the binding affinities, inhibitory potentials and interaction patterns of tocopherol with these target proteins. The findings revealed significant interactions, particularly with 4YAY, displaying a robust binding energy of -6.39 kcal/mol and a promising Ki value of 20.84 μM. Notable interactions were also observed with 1HW9, 4DLI, 2YCW and 1CX2, further indicating tocopherol\'s potential therapeutic relevance. In contrast, no interaction was observed with 1BO9. Furthermore, an examination of the common residues of 4YAY bound to tocopherol was carried out, highlighting key intermolecular hydrophobic bonds that contribute to the interaction\'s stability. Tocopherol complies with pharmacokinetics (Lipinski\'s and Veber\'s) rules for oral bioavailability and proves safety non-toxic and non-carcinogenic. Thus, deep learning-based protein language models ESM1-b and ProtT5 were leveraged for input encodings to predict interaction sites between the 4YAY protein and tocopherol. Hence, highly accurate predictions of these critical protein-ligand interactions were achieved. This study not only advances the understanding of these interactions but also highlights deep learning\'s immense potential in molecular biology and drug discovery. It underscores tocopherol\'s promise as a cardiovascular disease management candidate, shedding light on its molecular interactions and compatibility with biomolecule-like characteristics.
摘要：
这项研究通过深入的分子对接分析，探讨了基于生育酚的纳米乳液作为心血管疾病（CVD）治疗剂的潜力。该研究的重点是阐明生育酚与七个关键蛋白之间的分子相互作用（1O8a，4YAY,4DLI,1HW9,2YCW,1BO9和1CX2）在CVD发展中起关键作用。通过严格的硅对接调查，对具有约束力的亲和力进行了评估，生育酚与这些靶蛋白的抑制潜力和相互作用模式。这些发现揭示了重要的相互作用，特别是4YAY,显示-6.39kcal/mol的稳健结合能和20.84μM的有希望的Ki值。还观察到与1HW9，4DLI，2YCW和1CX2，进一步表明生育酚的潜在治疗相关性。相比之下,没有观察到与1BO9的相互作用。此外，对与生育酚结合的4YAY的常见残基进行了检查，突出了有助于相互作用稳定性的关键分子间疏水键。生育酚符合药代动力学（Lipinski's和Veber's）的口服生物利用度规则，并证明安全无毒和非致癌。因此，利用基于深度学习的蛋白质语言模型ESM1-b和ProtT5进行输入编码，以预测4YAY蛋白质和生育酚之间的相互作用位点。因此，对这些关键的蛋白质-配体相互作用进行了高度准确的预测。这项研究不仅促进了对这些相互作用的理解，而且突出了深度学习在分子生物学和药物发现方面的巨大潜力。它强调了生育酚作为心血管疾病管理候选人的承诺，揭示其分子相互作用和与生物分子样特征的相容性。
