Inverse temperature transition of elastin like motifs in major ampullate dragline silk: MD simulations of short peptides and NMR studies of water dynamics

Abstract

Using deuterium 2D T1-T2 Inverse Laplace Transform (ILT) NMR we have investigated the distribution, population, and dynamics of waters of hydration in major ampullate N. clavipes and A. aurantia silk as a function of temperature. In both samples studied, correlation times much larger than that of free water are measured and in some cases appear to increase with increasing temperature over the range of 5 to 60 °C(corresponding to reduced tumbling). In addition, the experimental data point to a reduction in the population of water localized in the silk with increasing temperature in the range of 20 to 50°C. Molecular dynamics simulations were performed to probe the thermal characteristics of a variety of repeating motifs found in the two silk samples. The repeating motifs GLGSQ, GAAAAAAG, GPGGY, GPGQQ, GPSG, and GPSGPGS found in N. clavipes, GLGSQ, GYGSG, GPGSG, and GPGSQ found in A. aurantia silk were found to exhibit a thermal property observed in short elastin peptides known as the “inverse temperature transition”. This is a well known characteristic exhibited by short peptides consisting of (VPGXG)n motifs (where X is any amino acid other than proline) found in elastin, a protein responsible for the elasticity of vertebrate tissues. In qualitative agreement with experimental measurements of water in the silks, all the peptides studied in simulation show evidence of an increase in sidechain contacts and peptide hydrogen bonds, concomitant with a decrease in radius of gyration and localized water as the temperature is raised from approximately 5 to 60° C.

Characterization of water in hydrated Bombyx mori silk fibroin fiber and films by 2H NMR relaxation and 13C solid state NMR

“…In addition, the reservoir denoted D reflects the bound water molecules located in the inner part of the SF fiber. The presence of such exchangeable water molecules with relatively restricted motion was already reported in studies of water-hydrated elastin, spider silk, and a perfluorinated ionomer system by 2D relaxation, diffusion, and exchange NMR experiments based on inverse Laplace transform methods [27, 29, 30]. Shen et al reported microstructure of SF fiber by transmission electron microscopy, selected are electron diffraction, wide-angle X-ray scattering and low-voltage high-resolution scanning electron microscopy.…”

“…In either the T 1 -T 2 or the T 2 -T 2 exchange measurements we found that the signal intensities and relaxation times did not change significantly with the regularization parameter, although the resolution was observed to reduce. In a previous work [29], we highlight the efficacy of the algorithm used for simulated data (where 5 different reservoirs of known relaxation times and signal intensities were simulated), and found that the ILT results were largely signal to noise dependent. In all measurements presented in this study we reproduced on 2 different samples and replicated across 2 to 3 measurements.…”

Mechanical, structural, and dynamical modifications of cholesterol exposed porcine aortic elastin

“…hydrogen bonding). Lastly, we note that the Inverse Laplace algorithm that we used was tested in a prior work against simulation data (with five reservoirs) and varying the signal to noise ratio (see Figure 4 in 60 ). Briefly, we found that the algorithm did not accurately reproduce the expected T 1 and T 2 times and signal intensities when the signal to noise ratio was poor.…”

Fabrication and Characterization of Recombinant Silk‐Elastin‐Like‐Protein (SELP) Fiber

“…Computational simulation is a helpful tool for initial predictions of material behavior. It can be used to understand how the molecular sequence and ratio of silk‐to‐elastin affect the resulting material, and it can serve as a guide for materials design when considering composition–property relationships …”

“…It can be used to understand how the molecular sequence and ratio of silk-to-elastin affect the resulting material, and it can serve as a guide for materials design when considering composition-property relationships. [43] In this study, we used simulation and experimental results for SELPs at different ratios of silk-to-elastin to learn how to predict material behavior. Three different ratios of silk-toelastin were used throughout the simulation and experimental studies: S1 = ((GVGVP) 4 (GYGVP)(GVGVP) 3 (GAGAGS)) 14 , S2 = ((GVGVP) 4 (GYGVP)(GVGVP) 3 (GAGAGS)(GAGAGS)) 12 , and S4= ((GVGVP) 4…”