Zeng Xincheng, Wang Tianqun, Kang Yue, Bai Ganggang, Ma Buyong
Engineering Research Center of Cell & Therapeutic Antibody (MOE), School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China.
Shanghai Digiwiser Biological Inc., Shanghai 200240, China.
Antibodies (Basel). 2023 Sep 17;12(3):58. doi: 10.3390/antib12030058.
T cell receptor β-chain constant (TRBC) is a promising class of cancer targets consisting of two highly homologous proteins, TRBC1 and TRBC2. Developing targeted antibody therapeutics against TRBC1 or TRBC2 is expected to eradicate the malignant T cells and preserve half of the normal T cells. Recently, several antibody engineering strategies have been used to modulate the TRBC1 and TRBC2 specificity of antibodies. Here, we used molecular simulation and artificial intelligence methods to quantify the affinity difference in antibodies with various mutations for TRBC1 and TRBC2. The affinity of the existing mutants was verified by FEP calculations aided by the AI. We also performed long-time molecular dynamics simulations to reveal the dynamical antigen recognition mechanisms of the TRBC antibodies.
T细胞受体β链恒定区（TRBC）是一类很有前景的癌症靶点，由两种高度同源的蛋白质TRBC1和TRBC2组成。开发针对TRBC1或TRBC2的靶向抗体疗法有望根除恶性T细胞并保留一半的正常T细胞。最近，几种抗体工程策略已被用于调节抗体对TRBC1和TRBC2的特异性。在此，我们使用分子模拟和人工智能方法来量化具有各种突变的抗体对TRBC1和TRBC2的亲和力差异。通过人工智能辅助的FEP计算验证了现有突变体的亲和力。我们还进行了长时间的分子动力学模拟，以揭示TRBC抗体的动态抗原识别机制。
