Michael Smith Laboratories, Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Biomolecules. 2023 Mar 13;13(3):527. doi: 10.3390/biom13030527.
Research in the field of biochemistry and cellular biology has entered a new phase due to the discovery of phase separation driving the formation of biomolecular condensates, or membraneless organelles, in cells. The implications of this novel principle of cellular organization are vast and can be applied at multiple scales, spawning exciting research questions in numerous directions. Of fundamental importance are the molecular mechanisms that underly biomolecular condensate formation within cells and whether insights gained into these mechanisms provide a gateway for accurate predictions of protein phase behavior. Within the last six years, a significant number of predictors for protein phase separation and condensate localization have emerged. Herein, we compare a collection of state-of-the-art predictors on different tasks related to protein phase behavior. We show that the tested methods achieve high AUCs in the identification of biomolecular condensate drivers and scaffolds, as well as in the identification of proteins able to phase separate in vitro. However, our benchmark tests reveal that their performance is poorer when used to predict protein segments that are involved in phase separation or to classify amino acid substitutions as phase-separation-promoting or -inhibiting mutations. Our results suggest that the phenomenological approach used by most predictors is insufficient to fully grasp the complexity of the phenomenon within biological contexts and make reliable predictions related to protein phase behavior at the residue level.
由于发现相分离驱动生物分子凝聚物(或无膜细胞器)在细胞中的形成,生物化学和细胞生物学领域的研究进入了一个新阶段。这一新型细胞组织原则的意义非常广泛,可以在多个尺度上应用,在众多方向上引发了令人兴奋的研究问题。至关重要的是,细胞内生物分子凝聚物形成的分子机制,以及对这些机制的深入了解是否为蛋白质相行为的准确预测提供了一个途径。在过去的六年中,已经出现了大量用于预测蛋白质相分离和凝聚物定位的预测器。在此,我们比较了一系列不同任务相关的最先进的预测器,这些任务与蛋白质相行为有关。我们表明,所测试的方法在识别生物分子凝聚物的驱动因子和支架,以及识别能够在体外相分离的蛋白质方面,都能达到高 AUC。然而,我们的基准测试表明,当用于预测参与相分离的蛋白质片段,或分类氨基酸取代为促进或抑制相分离的突变时,它们的性能较差。我们的结果表明,大多数预测器所使用的现象学方法不足以完全理解生物背景下该现象的复杂性,并且无法在残基水平上对蛋白质相行为进行可靠的预测。