使用人工智能生成的结构探索蛋白质基因酶的可药化形态空间
bioRxiv : the preprint server for biology
|September 11, 2023
概括
像AlphaFold2这样的AI模型可以预测不活跃状态中的新蛋白激酶结构,这对药物发现至关重要. 降低AlphaFold2中的多个序列对齐深度有助于探索这些多样化的构造,为新的酶向疗法开辟了道路.
科学领域:
- 结构生物学是结构生物学.
- 计算化学是一种计算化学.
- 药物发现 药物发现
背景情况:
- 蛋白激酶在细胞功能中起着至关重要的作用,是药物开发的关键标.
- 药物发现受到缺乏实验确定基因酶在非活性构造中的结构的阻碍.
- 由DFG和aC-Helix等动机调节的酶构造状态影响药物结合和治疗结果.
结论:
- 在AlphaFold2中降低MSA深度可以更广泛地探索酶构造空间.
- 这种方法可以识别新的,潜在的药物可用酶构造.
- 这些发现为发现针对具有挑战性的酶蛋白的治疗方法提供了新的策略.
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