Journal of Computer Chemistry, Japan
Online ISSN : 1347-3824
Print ISSN : 1347-1767
ISSN-L : 1347-1767
Letters
Theoretical Analysis of the Aggregation-Inhibition Effect of Arginine on Polyglutamine Protein by the Generalized-Ensemble Method
Shoichi TANIMOTOHisashi OKUMURA
Author information
JOURNAL FREE ACCESS FULL-TEXT HTML

2023 Volume 22 Issue 2 Pages 18-20

Details
Abstract

The aggregation of polyglutamine (polyQ) proteins, which have the abnormal expansion of glutamine repeats, is a critical pathological hallmark of polyQ diseases. Experimental studies have shown an amino acid arginine uniquely inhibits the polyQ-protein aggregation. We performed replica-permutation molecular dynamics simulations to clarify the inhibitory effects of arginine on the polyQ-protein aggregation. We found arginine makes more contact with the polyQ protein than lysine, and this tendency of arginine likely inhibits the polyQ-protein aggregation.

1 Introduction

The polyglutamine (polyQ) diseases are a collection of at least nine inherited neurodegenerative diseases, including Huntington's disease, six types of spinocerebellar ataxias, spinal and bulbar muscular atrophy, and dentatorubral-pallidoluysian atrophy [1,2,3]. These diseases share a common cause: a genetic mutation resulting in an abnormal expansion of a CAG trinucleotide repeat (> 35–40 repeats), translating into a long polyQ stretch in the associated protein. The polyQ proteins with the long polyQ stretch are misfolded to form monomers and oligomers with intra- and intermolecular β-sheet structures, eventually forming insoluble aggregates. These aggregates are considered to accumulate in neurons and cause neurodegeneration [4].

To treat polyQ diseases, it is necessary to inhibit polyQ-protein aggregation. Recently, experimental studies have identified an amino acid arginine as a promising aggregation inhibitor [5, 6]. Arginine inhibits polyQ proteins from forming intra- and intermolecular β-sheet structures and prevents polyQ proteins from aggregating to form oligomers. Furthermore, this aggregation-inhibitory effect was not observed in other amino acids and was unique to arginine [5, 6]. In this study, we performed replica-permutation molecular dynamics (RPMD) simulations [7] to clarify the molecular mechanism by which arginine inhibits the formation of the intramolecular β-sheet structure of the polyQ protein.

2 Computational details

An extended conformation without any secondary structure of a polyQ monomer with 36 repeated glutamines was used as the initial conformation. We performed the RPMD simulations [7] of two systems: the systems of the polyQ monomer with 100 mM zwitterionic arginine (polyQ+Arg) and the polyQ monomer with 100 mM zwitterionic lysine (polyQ+Lys). All RPMD simulations were performed using the Generalized-Ensemble Molecular Biophysics program developed by one of the authors (H. O.) [8]. We applied the Amber parm14SB force field [9] to the polyQ monomer. We used the force field by Horn [10] for the zwitterionic ligands (arginine and lysine). The TIP3P rigid-body model [11] was used for the water molecules. Forty-eight replicas were used in the RPMD simulations. The temperatures were distributed from 300.0 to 500.0 K. Each RPMD simulation was performed for 550 ns per replica, meaning 26.4 μs in total for each system. The first 50 ns was regarded as the initial equilibration, and the following 500 ns was used for the later analysis. The bootstrap method [12] was employed to estimate the errors of physical quantities.

3 Results and discussion

We calculated the average number of ligands in contact with the polyQ monomer (Figure 1). In this study, we regarded an intermolecular contact was formed between the polyQ monomer and the ligand when the closest distance between heavy atoms (all atoms except for hydrogen atoms) of the polyQ monomer and the ligand was less than 4.0 Å. Figure 1 clearly shows the average number of ligands in contact with the polyQ monomer is higher for arginine than lysine. This result suggests arginine can exist more in the vicinity of the polyQ monomer than lysine. It means arginine interferes with the interactions among polyQ monomers. Typical snapshots in the polyQ+Arg and polyQ+Lys systems are shown in Figure 2. As shown in Figure 2 (a), the polyQ monomer in the polyQ+Lys system formed intramolecular β-strands, although somewhat disturbed. On the other hand, the secondary structures of the polyQ monomer in the polyQ+Arg system were almost completely disrupted, and more arginines surrounded the polyQ monomer than lysines, as shown in Figure 2 (a) and Figure 2 (b). These results suggest arginine binds to polyQ monomers more than lysine and prevents polyQ monomers from aggregation.

Figure 1.

 The average number of ligands in contact with the polyQ monomer.

Figure 2.

 Snapshots of the polyQ monomer in the (a) polyQ+Arg and (b) polyQ+Lys systems. Several ligands existing in the vicinity of the polyQ monomer are also shown. The polyQ monomer is represented as a ribbon model and the ligands are represented as a stick model.

4 Conclusion

We performed the RPMD simulations of the systems of the polyQ monomer with zwitterionic arginine and the polyQ monomer with zwitterionic lysine to clarify the inhibitory effects of arginine on the polyQ-protein aggregation. We found arginine makes more contact with the polyQ monomer. This result suggests arginine exists more in the vicinity of polyQ monomers than other amino acids. Arginine, thus, prevents polyQ monomers from forming intramolecular β-sheet structures and intermolecular β-sheet structures with other polyQ monomers, thereby inhibiting the polyQ-protein aggregation. Previous studies have shown the intramolecular β-hairpin structure promotes the formation of the intermolecular β-sheet structure [13,14,15]; therefore, we will analyze the formation of the intramolecular β-hairpin.

Acknowledgments

This work used supercomputers at the Research Center for Computational Science, Okazaki Research Facilities, National Institutes of Natural Sciences (Projects 21-IMS-C172 and 22-IMS-C186). This work was carried out under the General Cooperative Research 1 (2021-ISMCRP-1009 and 2022-ISMCRP-1002) of the Institute of Statistical Mathematics (ISM).

This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Numbers JP21K15059 and JP22J01617.

References
 
© 2023 Society of Computer Chemistry, Japan
feedback
Top