Interaction preferences between nucleobase mimetics and amino acids in aqueous solutions
文献信息
Matea Hajnic, Juan I. Osorio, Bojan Zagrovic
Despite the paramount importance of protein–nucleic acid interactions in different cellular processes, our understanding of such interactions at the atomistic level remains incomplete. We have used molecular dynamics (MD) simulations and 15 μs of sampling time to study the behavior of amino acids and amino-acid sidechain analogs in aqueous solutions of different mimetics of naturally occurring nucleobases, including dimethylpyridine (DMP) and unsubstituted purine and pyrimidine rings. By using structural and energetic analysis, we have derived preference scales for the interaction of amino acids and their sidechain analogs with different nucleobase mimetics and have exhaustively compared them with each other. A close correspondence with a standard hydrophobicity measure in the case of the pyrimidine mimetic DMP and purines suggests that the hydrophobic effect is the main defining factor behind such interactions. We analyze our findings in the context of the origin of the genetic code and the recently proposed cognate mRNA–protein complementarity hypothesis. Most importantly, we show that unsubstituted purine and pyrimidine rings alone cannot differentiate between predominantly purine- and pyrimidine-coded amino acids, suggesting that for such specificity to exist, it must primarily reside in ring substituents.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.













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