School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China.
Center Lab of Longhua Branch and Department of Infectious Disease, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, Guangdong, PR China.
J Chem Inf Model. 2021 Mar 22;61(3):1275-1286. doi: 10.1021/acs.jcim.0c00961. Epub 2021 Mar 3.
As an emerging immune checkpoint, CD73 has received more attention in the past decade. Inhibition of CD73 enzymatic activity can enhance antitumor immunity. Several CD73 inhibitors have been identified by in vitro assays in recent years, but they remain premature for clinical application, indicating that more novel CD73 inhibitors should be studied. Herein, we aimed to identify novel CD73 inhibitors that hopefully are suitable drug candidates by using computer-aided drug discovery and enzymatic-based assays. Five-hundred molecules with high binding affinity were retrieved from the Chemdiv-Plus database by using a structure-based virtual screening approach. Then, we analyzed the drug properties of these molecules and obtained 68 small molecules based on the oral noncentral nervous system (CNS) drug profile. The inhibition rates of these molecules against CD73 enzymatic activities were determined at a concentration of 100 μM, and 20 molecules had an inhibition rate greater than 20%, eight of which were dose-dependent, with IC50 values of 6.72-172.1 μM. Among the screening hits, phelligridin-based compounds had the best experimental inhibition values. Modeling studies indicate that the phelligridin group is sandwiched by the rings of F417 and F500 residues. The identified inhibitors have a molecular weight of approximately 500 Dal and are predicted to form primarily hydrogen bonds with CD73 in addition to hydrophobic stacking interactions. In conclusion, novel inhibitors with satisfactory drug properties may serve as lead compounds for the development of CD73-targeting drugs, and the binding modes may provide insight for phelligridin-based drug design.
作为一种新兴的免疫检查点,CD73 在过去十年中受到了更多的关注。抑制 CD73 的酶活性可以增强抗肿瘤免疫。近年来,通过体外检测已经鉴定出几种 CD73 抑制剂,但它们仍处于临床应用的早期阶段,这表明应该研究更多新型的 CD73 抑制剂。在此,我们旨在通过计算机辅助药物发现和基于酶的检测方法来鉴定新型的 CD73 抑制剂,希望这些抑制剂能够成为合适的候选药物。我们通过基于结构的虚拟筛选方法从 Chemdiv-Plus 数据库中检索到 500 种具有高结合亲和力的分子。然后,我们分析了这些分子的药物特性,并根据口服非中枢神经系统 (CNS) 药物特征获得了 68 种小分子。在 100 μM 的浓度下测定这些分子对 CD73 酶活性的抑制率,有 20 种分子的抑制率大于 20%,其中 8 种为剂量依赖性,IC50 值为 6.72-172.1 μM。在筛选出的化合物中,基于 phelligridin 的化合物具有最佳的实验抑制效果。建模研究表明,phelligridin 基团夹在 F417 和 F500 残基的环之间。鉴定出的抑制剂的分子量约为 500Dal,除了疏水堆积相互作用外,还预测主要与 CD73 形成氢键。总之,具有满意药物特性的新型抑制剂可能成为 CD73 靶向药物开发的先导化合物,并且结合模式可能为基于 phelligridin 的药物设计提供启示。