Coevolution‐derived native and non‐native contacts determine the emergence of a novel fold in a universally conserved family of transcription factors

By Pablo Galaz-Davison, Diego U. Ferreiro, César A. Ramírez-Sarmiento. 2022

12 citations recorded by the source corpus.

The NusG protein family is structurally and functionally conserved in all domains of life. Its members directly bind RNA polymerases and regulate transcription processivity and termination. RfaH, a divergent sub‐family in its evolutionary history, is known for displaying distinct features than those in NusG proteins, which allows them to regulate the expression of virulence factors in enterobacteria in a DNA sequence‐dependent manner. A striking feature is its structural interconversion between an active fold, which is the canonical NusG three‐dimensional structure, and an autoinhibited fold, which is distinctively novel. How this novel fold is encoded within RfaH sequence to encode a metamorphic protein remains elusive. In this work, we used publicly available genomic RfaH protein sequences to construct a complete multiple sequence alignment, which was further augmented with metagenomic sequences and curated by predicting their secondary structure propensities using JPred. Coevolving pairs of residues were calculated from these sequences using plmDCA and GREMLIN, which allowed us to detect the enrichment of key metamorphic contacts after sequence filtering. Finally, we combined our coevolutionary predictions with molecular dynamics to demonstrate that these interactions are sufficient to predict the structures of both native folds, where coevolutionary‐derived non‐native contacts may play a key role in achieving the compact RfaH novel fold. All in all, emergent coevolutionary signals found within RfaH sequences encode the autoinhibited and active folds of this protein, shedding light on the key interactions responsible for the action of this metamorphic protein.

Subfields: Genetics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Lucy J. Colwell
2. Hannah K. Wayment-Steele
3. Sergey Ovchinnikov
4. Dorothee Kern
5. Anne-Florence Bitbol

In Molecular Biology

1. Lucy J. Colwell
2. Sergey Ovchinnikov
3. Dorothee Kern
4. Hannah K. Wayment-Steele
5. Anne-Florence Bitbol
6. Jinbo Xu
7. David Baker
8. David T. Jones

Citations in the corpus

• Predicting multiple conformations via sequence clustering and AlphaFold2 (2023, neutral): “Methods proposed to deconvolve sets of states when previous knowledge about one or more states is known include ablating residues corresponding to contacts of a known dominant state 18 and supplementing the original MSA with proteins that are known to occupy a rarer state 19 .”
• Prediction of multiple conformational states by combining sequence clustering with AlphaFold2 (2022, background): “Methods proposed to deconvolve signal when prior knowledge about one or more states is known include ablating signal from a known dominant state 25 and supplementing the original multiple sequence alignment (MSA) with proteins known to occupy a rarer state 26 .”