免疫疗法，特别是针对 PD-1/PD-L1 通路的免疫疗法，通过调节免疫反应并防止癌细胞逃避免疫破坏，为癌症治疗带来了希望。尽管如此，这种方法存在针对健康细胞的不必要的免疫系统激活的风险。为了最大限度地降低这种风险，我们的研究提出了一种基于肿瘤酸性微环境中 PD-L1 通路选择性靶向的策略。我们采用虚拟筛选、分子力学和分子动力学模拟等计算机方法，分析了 MolPort 数据库中的大约 10,000 种天然化合物，以找到具有所需特性的潜在化合物。模拟在两种 pH 条件（pH = 7.4 和 5.5）下进行，以模拟健康细胞和癌细胞的环境。化合物 MolPort-001-742-690 成为一种有前途的 pH 选择性抑制剂，在酸性条件下对 PD-L1 显示出显着的亲和力，并且与 BMS-202 和 LP23 等已知抑制剂相比毒性更低。详细的 1000 ns 分子动力学模拟证实了抑制剂-PD-L1 复合物在酸性条件下的稳定性。这项研究强调了使用计算机技术发现新型 pH 选择性抑制剂的潜力，经过实验验证，该抑制剂可以提高免疫疗法的精度并降低免疫疗法的毒性，为癌症治疗提供一种变革性的方法。

Immunotherapy, particularly targeting the PD-1/PD-L1 pathway, holds promise in cancer treatment by regulating the immune response and preventing cancer cells from evading immune destruction. Nonetheless, this approach poses a risk of unwanted immune system activation against healthy cells. To minimize this risk, our study proposes a strategy based on selective targeting of the PD-L1 pathway within the acidic microenvironment of tumors. We employed in silico methods, such as virtual screening, molecular mechanics, and molecular dynamics simulations, analyzing approximately 10,000 natural compounds from the MolPort database to find potential hits with the desired properties. The simulations were conducted under two pH conditions (pH = 7.4 and 5.5) to mimic the environments of healthy and cancerous cells. The compound MolPort-001-742-690 emerged as a promising pH-selective inhibitor, showing a significant affinity for PD-L1 in acidic conditions and lower toxicity compared to known inhibitors like BMS-202 and LP23. A detailed 1000 ns molecular dynamics simulation confirmed the stability of the inhibitor-PD-L1 complex under acidic conditions. This research highlights the potential of using in silico techniques to discover novel pH-selective inhibitors, which, after experimental validation, may enhance the precision and reduce the toxicity of immunotherapies, offering a transformative approach to cancer treatment.