可解释的原子预测和功能分析的 conformational 集团和在蛋白质基因酶使用AlphaFold2 适应随机序列扫描和局部丧概况的allosteric 状态
bioRxiv : the preprint server for biology
|March 18, 2024
概括
阿尔法Fold2 (AF2) 难以预测蛋白质构造组合. 将AF2与丧映射进行调整,可以准确地预测ABL激酶状态,揭示了模拟人口较少,能量丧的构造的局限性.
科学领域:
- 结构生物学 结构生物学
- 计算生物学 计算生物学
- 生物物理学的生物物理.
背景情况:
- AlphaFold2 (AF2) 彻底改变了单个蛋白质结构的预测.
- 在建模动态蛋白质构造和性状态方面,AF2存在局限性.
- 已知ABL激酶的活性和非活性构造对AF2构成挑战.
研究的目的:
- 适应AlphaFold2 (AF2) 方法来预测蛋白质构成组合.
- 为了研究ABL激酶的全性状态和功能构造的预测.
- 了解蛋白质丧与AF2预测准确性之间的关系.
主要方法:
- 使用多重序列对齐 (MSA) 的亚样本采用AF2.
- 雇员 SPEACH_AF 在MSA上进行氨酸扫描.
- 引入随机的全序列突变扫描与MSA亚样本相结合.
- 应用了局部丧映射来分析预测的结构状态.
主要成果:
- 调整后的AF2方法准确地预测了ABL激酶活性和中间结构以及形状组合.
- 局部丧映射提供了AF2预测和局限性的可解释性特征.
- 大型,高度丧的残留集群是低人口,不活跃的ABL形式的特征.
- 确定了对形状转变至关重要的能量挫败的地点,作为AF2的挑战性目标.
结论:
- AF2 适应与挫折映射相结合,可以准确预测 ABL 激酶构造组合.
- 该研究强调了局部丧模式与AF2模拟人口稀少,动态状态的能力之间的基本联系.
- 提供了对当前基于AF2的方法的好处和局限性的洞察力,用于构造组合建模.
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