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

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.