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本质上有障碍的区域和功能障碍热点在人类基因组中的影响
Sonet Daniel Thomas1, Aparna Rajan1, Althaf Mahin1
1Centre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
这项研究引入了一种新的深度学习方法,用于预测人体激酶中的内在失序区域 (IDR),识别了1039个功能热点. 这有助于对激酶调节和潜在药物点的理解.
科学领域:
- 生物化学和分子生物学
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 酸化对于信号传递至关重要,由与内在无序区域 (IDR) 相互作用的蛋白激酶调节.
- 准确预测IDR仍然是一个挑战,尽管有许多计算方法.
- IDRs在基质特异性和重新校准细胞环境方面发挥着关键作用.
研究的目的:
- 开发一种标准化,以激酶为中心的计算方法,用于预测人类基因组中的IDR.
- 描述这些IDR的分布,保存和功能意义.
- 为了解酶调节和药物重用提供资源.
主要方法:
- 利用长期短期记忆深度学习框架进行IDR预测.
- 分类IDR段并分析它们相对于酶域的分布.
- 计算了人类酶家族的保护指数,并进行了生物物理分析.
主要成果:
- 在人类基因组中实现了IDR的高预测性能 (AUC=0.97).
- 确定了1039个功能障碍区域热点,这些热点与形状变化和酸化部位有关.
- 在137个人体酶家族中发现了保留和可变的疾病模式.
结论:
- 开发的框架提供了人体基因组中IDRs的全面功能特征.
- 已识别的IDR热点提供了关于激酶调节,基质特异性和潜在药物点的见解.
- 公开访问的网络服务器 (https://ciods.in/kindisorder) 作为研究人员的宝贵资源.
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