利用人工智能蛋白质扩散发现 PD-1 靶向抗体

IF 2.7 4区 医学 Q3 ONCOLOGY
Colby T Ford
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引用次数: 0

摘要

程序性细胞死亡蛋白 1(PD-1,CD279)是许多肿瘤疾病的重要治疗靶点。这种检查点蛋白能抑制 T 淋巴细胞攻击体内其他细胞,因此阻断它能改善免疫系统对肿瘤细胞的清除。目前已有多种抗 PD-1 抗体获得 FDA 批准,包括 nivolumab(百时美施贵宝公司的 Opdivo®)和 pembrolizumab(默克公司的 Keytruda®),但人们仍在不断努力发现新的、更好的检查点抑制剂疗法。在本研究中,我们介绍了多种抗 PD-1 抗体片段,这些片段是利用蛋白质扩散计算得出的,并通过我们的可扩展硅学管道进行了评估。在此,我们介绍了九种合成 Fv 结构,这些结构具有理想的预测结合性能,适合对其抗 PD-1 活性进行进一步的经验测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T lymphocytes from attacking other cells in the body and thus blocking it improves the clearance of tumor cells by the immune system. While there are already multiple FDA-approved anti-PD-1 antibodies, including nivolumab (Opdivo® from Bristol-Myers Squibb) and pembrolizumab (Keytruda® from Merck), there are ongoing efforts to discover new and improved checkpoint inhibitor therapeutics. In this study, we present multiple anti-PD-1 antibody fragments that were derived computationally using protein diffusion and evaluated through our scalable, in silico pipeline. Here we present nine synthetic Fv structures that are suitable for further empirical testing of their anti-PD-1 activity due to desirable predicted binding performance.

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来源期刊
CiteScore
4.40
自引率
0.00%
发文量
202
审稿时长
2 months
期刊介绍: Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.
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