Dicer 蛋白是 miRNA 生物合成和细胞内蛋白质表达调节等基本细胞途径中不可或缺的参与者。最近，在多种类型的癌症中都发现了 DICER1 的种系和体细胞突变，这表明 Dicer 突变可以导致癌症进展。除了众所周知的 RNAase III 结构域热点突变外，DICER1 的特点还在于所有功能结构域中存在广泛的变异。大多数具有不确定的意义和未说明的临床效果。此外，癌症基因组测序中不断出现各种新的体细胞DICER1突变。最新的变异效应预测方法利用机器学习算法处理大量数据，产生与生物数据的次优相关性。因此，此类分析应基于每种蛋白质的功能和结构特征，使用基础良好的目标数据集进行，而不是依赖大量无监督数据。结构域是蛋白质的功能和进化单位；对整个蛋白质的分析应该基于通过进化重建对每个结构域进行单独和独立的检查。 Dicer 代表了多域蛋白的标志性例子，我们证实系统发育多域方法有利于 Dicer 变体的临床效果预测。由于 Dicer 被认为在血液恶性肿瘤中具有假定的作用，因此我们使用个体结构域历史的系统发育重建来检查在此类癌症中 RNase III 结构域的众所周知的热点之外发生的 DICER1 变体。检查的替换可能会破坏 Dicer 功能，这一点通过分子动力学模拟得到了证明，其中每个突变都观察到了不同的结构变化。我们的方法可用于研究其他多域蛋白并改善临床效果评估。版权所有 © 2024 Bug、Moiseev、Porozov 和 Petukhova。

The Dicer protein is an indispensable player in such fundamental cell pathways as miRNA biogenesis and regulation of protein expression in a cell. Most recently, both germline and somatic mutations in DICER1 have been identified in diverse types of cancers, which suggests Dicer mutations can lead to cancer progression. In addition to well-known hotspot mutations in RNAase III domains, DICER1 is characterized by a wide spectrum of variants in all the functional domains; most are of uncertain significance and unstated clinical effects. Moreover, various new somatic DICER1 mutations continuously appear in cancer genome sequencing. The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. Consequently, such analysis should be conducted based on the functional and structural characteristics of each protein, using a well-grounded targeted dataset rather than relying on large amounts of unsupervised data. Domains are the functional and evolutionary units of a protein; the analysis of the whole protein should be based on separate and independent examinations of each domain by their evolutionary reconstruction. Dicer represents a hallmark example of a multidomain protein, and we confirmed the phylogenetic multidomain approach being beneficial for the clinical effect prediction of Dicer variants. Because Dicer was suggested to have a putative role in hematological malignancies, we examined variants of DICER1 occurring outside the well-known hotspots of the RNase III domain in this type of cancer using phylogenetic reconstruction of individual domain history. Examined substitutions might disrupt the Dicer function, which was demonstrated by molecular dynamic simulation, where distinct structural alterations were observed for each mutation. Our approach can be utilized to study other multidomain proteins and to improve clinical effect evaluation.Copyright © 2024 Bug, Moiseev, Porozov and Petukhova.