Evidence map›Paper›PMID 41096778›Full record

ArticleInternational journal of molecular sciences2025

Investigation of the Substrate Selection Mechanism of Poly (A) Polymerase Based on Molecular Dynamics Simulations and Markov State Model.

Yongxin Jiang, Xueyan Duan, Jingxian Zheng, Fuyan Cao, Linlin Zeng, Weiwei Han

Abstract read
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Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yongxin JiangKey Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.
Xueyan DuanKey Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.
Jingxian ZhengKey Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.
Fuyan CaoKey Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.
Linlin ZengKey Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.ORCID 0000-0002-8653-9909
Weiwei HanKey Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.ORCID 0000-0002-1931-9316

Funding

National Natural Science Foundation of China No.32471313
6 · The paper itself

Abstract

RNA polymerases are essential enzymes that catalyze DNA transcription into RNA, vital for protein synthesis, gene expression regulation, and cellular responses. Non-template-dependent RNA polymerases, which synthesize RNA without a template, are valuable in biological research due to their flexibility in producing RNA without predefined sequences. However, their substrate polymerization mechanisms are not well understood. This study examines Poly (A) polymerase (PAP), a nucleotide transferase superfamily member, to explore its substrate selectivity using computational methods. Previous research shows PAP's polymerization efficiency for nucleoside triphosphates (NTPs) ranks ATP > GTP > CTP > UTP, though the reasons remain unclear. Using 500 ns Gaussian accelerated molecular dynamics simulations, stability analysis, secondary structure analysis, MM-PBSA calculations, and Markov state modeling, we investigate PAP's differential polymerization efficiencies. Results show that ATP binding enhances PAP's structural flexibility and increases solvent-accessible surface area, likely strengthening protein-substrate or protein-solvent interactions and affinity. In contrast, polymerization of other NTPs leads to a more open conformation of PAP's two domains, facilitating substrate dissociation from the active site. Additionally, ATP binding induces a conformational shift in residues 225-230 of the active site from a loop to an α-helix, enhancing regional rigidity and protein stability. Both ATP and GTP form additional π-π stacking interactions with PAP, further stabilizing the protein structure. This theoretical study of PAP polymerase's substrate selectivity mechanisms aims to clarify the molecular basis of substrate recognition and selectivity in its catalytic reactions. These findings offer valuable insights for the targeted engineering and optimization of polymerases and provide robust theoretical support for developing novel polymerases for applications in drug discovery and related fields.

Indexed as

Molecular Dynamics SimulationPolynucleotide AdenylyltransferaseAdenosine TriphosphateCatalytic DomainMarkov ChainsProtein BindingProtein ConformationSubstrate SpecificityAdenosine TriphosphatePolynucleotide Adenylyltransferasegaussian accelerated molecular dynamics simulationmarkov state modelmolecular dockingRNA polymerasesubstrate selectivity

Identifiers

PMID41096778
PMCPMC12524461

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.