Dissecting the Critical Factors for Thermodynamic Stability of Modular Proteins Using Molecular Modeling Approach

<div><p>Repeat proteins have recently attracted much attention as alternative scaffolds to immunoglobulin antibodies due to their unique structural and biophysical features. In particular, repeat proteins show high stability against temperature and chaotic agents. Despite many studies, structural features for the stability of repeat proteins remain poorly understood. Here we present an interesting result from <i>in silico</i> analyses pursuing the factors which affect the stability of repeat proteins. Previously developed repebody structure based on variable lymphocytes receptors (VLRs) which consists of leucine-rich repeat (LRR) modules was used as initial structure for the present study. We constructed extra six repebody structures with varying numbers of repeat modules and those structures were used for molecular dynamics simulations. For the structures, the intramolecular interactions including backbone H-bonds, van der Waals energy, and hydrophobicity were investigated and then the radius of gyration, solvent-accessible surface area, ratio of secondary structure, and hydration free energy were also calculated to find out the relationship between the number of LRR modules and stability of the protein. Our results show that the intramolecular interactions lead to more compact structure and smaller surface area of the repebodies, which are critical for the stability of repeat proteins. The other features were also well compatible with the experimental results. Based on our observations, the repebody-5 was proposed as the best structure from the all repebodies in structure optimization process. The present study successfully demonstrated that our computer-based molecular modeling approach can significantly contribute to the experiment-based protein engineering challenge.</p></div

Comparison of free energies of hydration for all seven repebodies.

<p>Relative <i>ΔG_hyd</i>, Relative free energy of hydration, is total energy divided by number of residues.</p

RMSD values of repebodies with different numbers of LRR module under simulated annealing (A) and conventional procedure (B).

<p>Comparison of B-factors between crystal and simulated annealing (C) or conventional MD (D) structures. (E) B-factor contour maps on the surface of repebody-5 based on different simulation methods. Predicted B-factor values based on simulated RMSF were obtained by using the conversion formula: B-factor = (8π²/3)RMSF²<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098243#pone.0098243-McCammon1" target="_blank">[32]</a>.</p

Comparison of structural properties in all the repebody ensembles.

<p>Time dependent changes of the secondary structures with relative number of coils (A) and structure (B). (C) Time dependence of the relative gyration (<i>R</i>g) for the protein atoms during the simulation time. (D) Contour map of the probability density of relative <i>R</i>g as a function of relative number of structure. The most populated conformation for each repebody is highlighted by circle on the map and displayed by ribbon representations. Overlapped region of repebody-5 and 6 in the bottom of the map is separated and displayed into right panel.</p

Correlation between concentration of urea C_m and SASA.

<p>C_m, concentration of urea.</p

Correlation between melting temperature <i>T</i>_m and intramolecular interaction properties including number of backbone H-bond, energies, and hydrophobicity.

<p><i>T</i>_m, melting temperature; Coul. Recip., long range coulomb energy in reciprocal space; LJ, Lennard-Jones energy.</p>a<p>Hydrophobicity of buried hydrophobic residues.</p

Relative short rang LJ energy values for selection of optimized VLR module protein.

<p>Relative short rang LJ energy values for selection of optimized VLR module protein.</p