Many critical processes in the cell involve direct binding between RNAs and proteins, making it imperative to fully understand the physicochemical principles behind such interactions at the atomistic level. Here, we use molecular dynamics simulations and 15 μs of sampling to study the behavior of amino acids and amino acid sidechain analogs in high-concentration aqueous solutions of standard RNA nucleobases. Structural and energetic analysis of simulated systems allows us to derive interaction propensity scales for different amino acid/nucleobase combinations. The derived scales closely match and greatly extend the available experimental data, providing a comprehensive foundation for studying RNA–protein interactions in different contexts. By using these scales, we demonstrate a statistically significant connection between nucleobase composition of human mRNA coding sequences and nucleobase interaction propensities of their cognate protein sequences. For example, pyrimidine density profiles of mRNAs match uracil-propensity profiles of their cognate proteins with a median Pearson correlation coefficient of R = −0.70. Our results provide support for the recently proposed hypotheses that mRNAs and their cognate proteins may be physicochemically complementary to each other and bind, especially if unstructured, with the complementarity level being negatively influenced by mRNA adenine content. Finally, we utilize the derived scales to refine the complementarity hypothesis and closely examine its physicochemical underpinnings.

A central intermediate in purine catabolism, the inosine nucleobase hypoxanthine is also one of the most abundant modified nucleobases in RNA and plays key roles in the regulation of gene expression and determination of cell fate. It is known that hypoxanthine acts as guanine when interacting with other nucleobases and base pairs most favorably with cytosine. However, its preferences when it comes to interactions with amino acids remain unknown. Here we present for the first time the absolute binding free energies and the associated interaction modes between hypoxanthine and all standard, non-glycyl/non-prolyl amino acid side chain analogs as derived from molecular dynamics simulations and umbrella sampling in high- and low-dielectric environments. We illustrate the biological relevance of the derived affinities by providing a quantitative explanation for the specificity of hypoxanthine-guanine phosphoribosyltransferase, a key enzyme in the purine salvage pathway. Our results demonstrate that in its affinities for protein side chains, hypoxanthine closely matches guanine, much more so than its precursor adenine.