Why Is Arginine the Only Amino Acid That Inhibits Polyglutamine Monomers from Taking on Toxic Conformations?

Polyglutamine (polyQ) diseases are devastating neurodegenerative disorders characterized by abnormal expansion of glutamine repeats within specific proteins. The aggregation of polyQ proteins is a critical pathological hallmark of these diseases. Arginine was identified as a promising inhibitory compound because it prevents polyQ-protein monomers from forming intra- and intermolecular ß-sheet structures and hinders polyQ proteins from aggregating to form oligomers. Such an aggregation inhibitory effect was not observed in other amino acids. However, the underlying molecular mechanism of the aggregation inhibition and the factors that differentiate arginine from other amino acids, in terms of the inhibition of the polyQ-protein aggregation, remain poorly understood. Here, we performed replica-permutation molecular dynamics simulations to elucidate the molecular mechanism by which arginine inhibits the formation of the intramolecular ß-sheet structure of a polyQ monomer. We found that the intramolecular ß-sheet structure with more than four ß-bridges of the polyQ monomer with arginine is more unstable than without any ligand and with lysine. We also found that arginine has 1.6-2.1 times more contact with polyQ than lysine. In addition, we revealed that arginine forms more hydrogen bonds with the main chain of the polyQ monomer than lysine. More hydrogen bonds formed between arginine and polyQ inhibit polyQ from forming the long intramolecular ß-sheet structure. It is known that intramolecular ß-sheet structure enhances intermolecular ß-sheet structure between proteins. These effects are thought to be the reason for the inhibition of polyQ aggregation. This study provides insights into the molecular events underlying arginine's inhibition of polyQ-protein aggregation.

State-of-the-Art Molecular Dynamics Simulation Studies of RNA-Dependent RNA Polymerase of SARS-CoV-2.

Molecular dynamics (MD) simulations are powerful theoretical methods that can reveal biomolecular properties, such as structure, fluctuations, and ligand binding, at the level of atomic detail. In this review article, recent MD simulation studies on these biomolecular properties of the RNA-dependent RNA polymerase (RdRp), which is a multidomain protein, of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are presented. Although the tertiary structures of RdRps in SARS-CoV-2 and SARS-CoV are almost identical, the RNA synthesis activity of RdRp of SARS-CoV is higher than SARS-CoV-2. Recent MD simulations observed a difference in the dynamic properties of the two RdRps, which may cause activity differences. RdRp is also a drug target for Coronavirus disease 2019 (COVID-19). Nucleotide analogs, such as remdesivir and favipiravir, are considered to be taken up by RdRp and inhibit RNA replication. Recent MD simulations revealed the recognition mechanism of RdRp for these drug molecules and adenosine triphosphate (ATP). The ligand-recognition ability of RdRp decreases in the order of remdesivir, favipiravir, and ATP. As a typical recognition process, it was found that several lysine residues of RdRp transfer these ligand molecules to the binding site such as a "bucket brigade." This finding will contribute to understanding the mechanism of the efficient ligand recognition by RdRp. In addition, various simulation studies on the complexes of SARS-CoV-2 RdRp with several nucleotide analogs are reviewed, and the molecular mechanisms by which these compounds inhibit the function of RdRp are discussed. The simulation studies presented in this review will provide useful insights into how nucleotide analogs are recognized by RdRp and inhibit the RNA replication.

"Bucket brigade" using lysine residues in RNA-dependent RNA polymerase of SARS-CoV-2.

The RNA-dependent RNA polymerase (RdRp) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a promising drug target for coronavirus disease 2019 (COVID-19) because it plays the most important role in the replication of the RNA genome. Nucleotide analogs such as remdesivir and favipiravir are thought to interfere with the RNA replication by RdRp. More specifically, they are expected to compete with nucleoside triphosphates, such as ATP. However, the process in which these drug molecules and nucleoside triphosphates are taken up by RdRp remains unknown. In this study, we performed all-atom molecular dynamics simulations to clarify the recognition mechanism of RdRp for these drug molecules and ATP that were at a distance. The ligand recognition ability of RdRp decreased in the order of remdesivir, favipiravir, and ATP. We also identified six recognition paths. Three of them were commonly found in all ligands, and the remaining three paths were ligand-dependent ones. In the common two paths, it was observed that the multiple lysine residues of RdRp carried the ligands to the binding site like a "bucket brigade." In the remaining common path, the ligands directly reached the binding site. Our findings contribute to the understanding of the efficient ligand recognition by RdRp at the atomic level.

Dynamic properties of SARS-CoV and SARS-CoV-2 RNA-dependent RNA polymerases studied by molecular dynamics simulations.

One of the promising drug targets against COVID-19 is an RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The tertiary structures of the SARS-CoV-2 and SARS-CoV RdRps are almost the same. However, the RNA-synthesizing activity of the SARS-CoV RdRp is higher than that of the SARS-CoV-2 RdRp. We performed molecular dynamics simulations and found differences in their dynamic properties. In the SARS-CoV RdRp, motifs A-G, which form the active site, are up to 63% closer to each other. We also observed cooperative domain motion in the SARS-CoV RdRp. Such dynamic differences may cause the activity differences between the two RdRps.

A computational method to simulate global conformational changes of proteins induced by cosolvent.

A computational method to investigate the global conformational change of a protein is proposed by combining the linear response path following (LRPF) method and three-dimensional reference interaction site model (3D-RISM) theory, which is referred to as the LRPF/3D-RISM method. The proposed method makes it possible to efficiently simulate protein conformational changes caused by either solutions of varying concentrations or the presence of cosolvent species by taking advantage of the LRPF and 3D-RISM. The proposed method is applied to the urea-induced denaturation of ubiquitin. The LRPF/3D-RISM trajectories successfully simulate the early stage of the denaturation process within the simulation time of 300 ns, whereas no significant structural change is observed even in the 1 µs standard MD simulation. The obtained LRPF/3D-RISM trajectories reproduce the mechanism of the urea denaturation of ubiquitin reported in previous studies, and demonstrate the high efficiency of the method.

Effect of Molecular Orientational Correlations on Solvation Free Energy Computed by Reference Interaction Site Model Theory.

The effect of molecular orientational correlations on the solvation free energy (SFE) of one-dimensional and three-dimensional reference interaction site models (1D- and 3D-RISM) is investigated. The repulsive bridge correction (RBC) and the partial wave (PW) expansion are representative approaches for accounting for the orientational correlation partially lacking in original 1D- and 3D-RISM. The SFEs of 1D- and 3D-RISM for a set of small organic molecules are compared with the simulation results. Accordingly, the SFE expressions, based on RBC and PW, provide more accurate results than those of the uncorrected HNC or KH SFE expressions, which indicates that accounting for molecular orientational dependencies significantly contributes to the improvement of the SFE. The SFE component analysis indicates that the nonpolar component mainly contributes to the correction. The dependence of the error in the RISM SFE on the number of solute sites is examined. In addition, we discuss the differences between 1D- and 3D-RISM through the effect of these corrections.

The ion dependence of carbohydrate binding of CBM36: an MD and 3D-RISM study.

The molecular recognition process of the carbohydrate-binding module family 36 (CBM36) was examined theoretically. The mechanism of xylan binding by CBM36 and the role of Ca(2+) were investigated by the combined use of molecular dynamics simulations and the 3D reference interaction site model method. The CBM36 showed affinity for xylan after Ca(2+) binding, but not after Mg(2+) binding. Free-energy component analysis of the xylan-binding process revealed that the major factor for xylan-binding affinity is the electrostatic interaction between the Ca(2+) and the hydroxyl oxygens of xylan. The van der Waals interaction between the hydrophobic side chain of CBM36 and the glucopyranose ring of xylan also contributes to the stabilization of the xylan-binding state. Dehydration on the formation of the complex has the opposite effect on these interactions. The affinity of CBM36 for xylan results from a balance of the interactions between the binding ion and solvents, hydrophilic residues around xylan, and the hydroxyl oxygens of xylan. When CBM binds Ca(2+), these interactions are well balanced; in contrast, when CBM binds Mg(2+), the dehydration penalty is excessively large.