关键词: Chemical proteomics Mechanism of action Native compounds Pharmacology Target validation

Mesh : Drug Discovery Peptide Hydrolases Proteolysis Neural Cell Adhesion Molecules

来  源:   DOI:10.1016/j.bioorg.2023.106828

Abstract:
In drug discovery and development, the direct target identification of bioactive small molecules plays a significant role for understanding the mechanism of action, predicting the side effects, and rationally designing more potent compounds. However, due to the complicated regulatory processes in a cell together with thousands of biomacromolecules, target identification is always the major obstacle. New methods and technologies are continuously invented to tackle this problem. Nevertheless, the mainly used tools possess several disadvantages. High synthetic skills are typically required to laboriously synthesize a probe for protein enrichment. To detect the ligand-protein interaction by analyzing proteins\' responses to proteolytic or thermal treatment, costly and precise instruments are always necessary. Therefore, convenient and practical techniques are urgently needed. Over the past decades, a strategy using native compounds without the requirement of chemical modification, also termed Native-compound-Coupled Affinity Matrix (NCAM), is developing continuously. Two practical tactics based on \"label-free\" compounds have been invented and used, that is Photo-cross-linked Small-molecule Affinity Matrix (PSAM) and Native-compound-Coupled CNBr-activated Beads (NCCB). Presently, we will elucidate the characteristics, coupling mechanism, advantages and disadvantages, and future prospect of NCAM in specific target identification and validation.
摘要:
在药物发现和开发中,生物活性小分子的直接靶标识别对于理解其作用机制具有重要作用,预测副作用,合理设计更有效的化合物。然而,由于细胞中复杂的调节过程以及成千上万的生物大分子,目标识别始终是主要障碍。不断发明新的方法和技术来解决这个问题。然而,主要使用的工具有几个缺点。通常需要高合成技能来费力地合成用于蛋白质富集的探针。通过分析蛋白质对蛋白水解或热处理的反应来检测配体-蛋白质相互作用,昂贵和精确的仪器总是必要的。因此,迫切需要方便和实用的技术。在过去的几十年里,使用天然化合物而不需要化学修饰的策略,也称为天然化合物耦合亲和矩阵(NCAM),正在不断发展。已经发明和使用了两种基于“无标签”化合物的实用策略,即光交联的小分子亲和基质(PSAM)和天然化合物偶联的CNBr活化的珠(NCCB)。目前,我们将阐明其特征,耦合机构,优点和缺点,以及NCAM在特定目标识别和验证中的未来前景。
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