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Ribonuclease T2 represents a distinct circularly permutated version of the BECR RNases.

Huan LiTheresa SchneiderYongjun TanDapeng Zhang
Published in: Protein science : a publication of the Protein Society (2022)
Detection of homologous relationships among proteins and understanding their mechanisms of diversification are major topics in the fields of protein science, bioinformatics, and phylogenetics. Recent developments in sequence/profile-based and structural similarity-based methods have greatly facilitated the unification and classification of many protein families into superfamilies or folds, yet many proteins remain unclassified in current protein databases. As one of the three earliest identified RNases in biology, Ribonuclease T2, also known as RNase I in E. coli, RNase Rh in fungi, or S-RNase in plant, is thought to be an ancient RNase family due to its widespread distribution and distinct structure. In this study, we present evidence that RNase T2 represents a circularly permutated version of the BECR (Barnase-EndoU-Colicin E5/D-RelE) fold RNases. This subtle relationship cannot be detected by traditional methods such as sequence/profile-based comparisons, structure-similarity searches, and circular permutation detections. However, we were able to identify the structural similarity using rational reconstruction of a theoretical RNase T2 ancestor via a reverse circular permutation process, followed by structural modeling using AlphaFold2, and structural comparisons. This relationship is further supported by the fact that RNase T2 and other typical BECR RNases, namely Colicin D, RNase A, and BrnT, share similar catalytic site configurations, all involving an analogous set of conserved residues on the α0 helix and the β4 strand of the BECR fold. This study revealed a hidden root of RNase T2 in bacterial toxin systems and demonstrated that reconstruction and modeling of ancestral topology is an effective strategy to identify remote relationship between proteins. This article is protected by copyright. All rights reserved.
Keyphrases
  • escherichia coli
  • protein protein
  • public health
  • machine learning
  • transcription factor
  • single cell
  • binding protein
  • small molecule
  • psychometric properties