Everything AlphaFold tells us about protein knots

IF 4.7 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
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Abstract

Recent advances in Machine Learning methods in structural biology opened up new perspectives for protein analysis. Utilizing these methods allows us to go beyond the limitations of empirical research, and take advantage of the vast amount of generated data. We use a complete set of potentially knotted protein models identified in all high-quality predictions from the AlphaFold Database to search for any common trends that describe them. We show that the vast majority of knotted proteins have 31 knot and that the presence of knots is preferred in neither Bacteria, Eukaryota, or Archaea domains. On the contrary, the percentage of knotted proteins in any given proteome is around 0.4%, regardless of the taxonomical group. We also verified that the organism’s living conditions do not impact the number of knotted proteins in its proteome, as previously expected. We did not encounter an organism without a single knotted protein. What is more, we found four universally present families of knotted proteins in Bacteria, consisting of SAM synthase, and TrmD, TrmH, and RsmE methyltransferases.

Abstract Image

AlphaFold 告诉我们关于蛋白质结的一切。
机器学习方法在结构生物学领域的最新进展为蛋白质分析开辟了新的前景。利用这些方法,我们可以超越经验研究的局限性,充分利用大量生成的数据。我们使用从 AlphaFold 数据库的所有高质量预测中识别出的一整套潜在结节蛋白质模型,寻找描述这些模型的任何共同趋势。我们发现,绝大多数打结蛋白质都有 31 个结,而且无论是在细菌、真核细胞还是古细菌领域,打结蛋白质的存在都不是首选。相反,在任何给定的蛋白质组中,打结蛋白质的比例都在 0.4% 左右,与分类群无关。我们还验证了生物体的生活条件不会影响其蛋白质组中打结蛋白质的数量,这与之前的预期一致。我们没有发现一个生物体中没有一个打结蛋白。此外,我们还在细菌中发现了四个普遍存在的结节蛋白家族,包括 SAM 合成酶、TrmD、TrmH 和 RsmE 甲基转移酶。
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来源期刊
Journal of Molecular Biology
Journal of Molecular Biology 生物-生化与分子生物学
CiteScore
11.30
自引率
1.80%
发文量
412
审稿时长
28 days
期刊介绍: Journal of Molecular Biology (JMB) provides high quality, comprehensive and broad coverage in all areas of molecular biology. The journal publishes original scientific research papers that provide mechanistic and functional insights and report a significant advance to the field. The journal encourages the submission of multidisciplinary studies that use complementary experimental and computational approaches to address challenging biological questions. Research areas include but are not limited to: Biomolecular interactions, signaling networks, systems biology; Cell cycle, cell growth, cell differentiation; Cell death, autophagy; Cell signaling and regulation; Chemical biology; Computational biology, in combination with experimental studies; DNA replication, repair, and recombination; Development, regenerative biology, mechanistic and functional studies of stem cells; Epigenetics, chromatin structure and function; Gene expression; Membrane processes, cell surface proteins and cell-cell interactions; Methodological advances, both experimental and theoretical, including databases; Microbiology, virology, and interactions with the host or environment; Microbiota mechanistic and functional studies; Nuclear organization; Post-translational modifications, proteomics; Processing and function of biologically important macromolecules and complexes; Molecular basis of disease; RNA processing, structure and functions of non-coding RNAs, transcription; Sorting, spatiotemporal organization, trafficking; Structural biology; Synthetic biology; Translation, protein folding, chaperones, protein degradation and quality control.
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