与传统癌症疗法相比，靶向纳米药物递送系统（TNDDS）在抑制脱靶效应方面具有独特的属性，使其成为最有前途的癌症治疗选择之一。有证据表明，表面共轭配体的密度是实现 TNDDS 所需治疗效果的关键因素，但这在传统纳米材料中很难控制。在这种情况下，配体保护的金纳米团簇 (AuNC) 是开发新型 TNDDS 的绝佳候选者，其表面功能具有独特的控制，从而有助于实现增强的递送性能。在这里，我们使用分子动力学模拟和伞式采样方法研究了十种不同的功能化 Au144(SR)60（SR = 硫醇配体）纳米团簇和整合素 αvβ3 之间的相互作用和结合自由能，以获得最佳配方。 AuNCs 用抗癌药物（5-氟尿嘧啶或信号通路抑制剂，如 capivasertib、linifanib、tanespimycin 和 taselisib）和整合素靶向肽（RGD4C 或 QS13）进行功能化，我们确定了最佳的混合配体层以增强它们的结合与癌细胞受体的亲和力。结果表明，改变 AuNC 表面同类型配体的比例会导致计算的结合自由能差异高达 38 kcal/mol。 RGD4C 作为靶向肽导致对 αvβ3 具有更大的亲和力，并且在大多数研究的制剂中，需要比肽更高量的药物。极性和带电残基，例如 Ser123、Asp150、Tyr178、Arg214 和 Asp251，被发现在 AuNC 结合中发挥重要作用。我们的模拟还表明，Mn2+ 阳离子对于稳定 αvβ3-AuNC 复合物至关重要。这些发现证明了仔细设计 TNDDS 的表面组成以优化其靶标亲和力和特异性的潜力。

The unique attributes of targeted nano-drug delivery systems (TNDDSs) over conventional cancer therapies in suppressing off-target effects make them one of the most promising options for cancer treatment. There is evidence that the density of surface-conjugated ligands is a crucial factor in achieving the desired therapeutic efficacy of TNDDSs, but this is hardly manageable in conventional nanomaterials. In this context, ligand-protected gold nanoclusters (AuNCs) are excellent candidates for developing new TNDDSs with a unique control on their surface functionalities, thus helping to achieve enhanced delivery performance. Here, we study the interactions and binding free energies between ten different functionalized Au144(SR)60 (SR = thiolate ligand) nanoclusters and integrin αvβ3 using molecular dynamics simulations and the umbrella sampling method to obtain the optimal formulations. The AuNCs were functionalized with anticancer drugs (5-fluorouracil or signaling pathways inhibitors, such as capivasertib, linifanib, tanespimycin, and taselisib) and integrin-targeting peptides (RGD4C or QS13), and we identified the optimal mixed ligand layer to enhance their binding affinity to the cancer cell receptor. The results showed that changing the proportions of the same type of ligands on the surface of AuNCs led to differences of up to 38 kcal/mol in computed binding free energies. RGD4C as the targeting peptide resulted in greater affinity for αvβ3, and in most formulations studied, a higher amount of drug than peptide was needed. Polar and charged residues, such as Ser123, Asp150, Tyr178, Arg214, and Asp251 were found to play a significant role in AuNC binding. Our simulations also revealed that Mn2+ cations are crucial for stabilizing the αvβ3-AuNC complex. These findings demonstrate the potential of carefully designing the surface composition of TNDDSs to optimize their target affinity and specificity.