Elucidating the Nature of Interactions in Collagen Triple-Helix Wrapping

Elucidating the role of water in collagen self-assembly by isotopically modulating collagen hydration

Water is known to play an important role in collagen self-assembly, but it is still largely unclear how water-collagen interactions influence the assembly process and determine the fibril network properties. Here, we use the H[Formula: see text]O/D[Formula: see text]O isotope effect on the hydrogen-bond strength in water to investigate the role of hydration in collagen self-assembly. We dissolve collagen in H[Formula: see text]O and D[Formula: see text]O and compare the growth kinetics and the structure of the collagen assemblies formed in these water isotopomers. Surprisingly, collagen assembly occurs ten times faster in D[Formula: see text]O than in H[Formula: see text]O, and collagen in D[Formula: see text]O self-assembles into much thinner fibrils, that form a more inhomogeneous and softer network, with a fourfold reduction in elastic modulus when compared to H[Formula: see text]O. Combining spectroscopic measurements with atomistic simulations, we show that collagen in D[Formula: see text]O is less hydrated than in H[Formula: see text]O. This partial dehydration lowers the enthalpic penalty for water removal and reorganization at the collagen-water interface, increasing the self-assembly rate and the number of nucleation centers, leading to thinner fibrils and a softer network. Coarse-grained simulations show that the acceleration in the initial nucleation rate can be reproduced by the enhancement of electrostatic interactions. These results show that water acts as a mediator between collagen monomers, by modulating their interactions so as to optimize the assembly process and, thus, the final network properties. We believe that isotopically modulating the hydration of proteins can be a valuable method to investigate the role of water in protein structural dynamics and protein self-assembly.

Association between N-Terminal Pyrenes Stabilizes the Collagen Triple Helix

Collagen model peptides featuring the fluorophore pyrene at their N-termini have been synthesized, and their thermal denaturation has been examined using circular dichroism (CD) and fluorescence spectroscopies. Flanking the (Pro-Hyp-Gly)7 core of the peptide monomers at positions 1 and/or 23 in the primary sequence, Lys residues were introduced to ensure water solubility. Triple helices derived from such peptides show a broad excimer emission at ∼480 nm, indicative of interaction between the pyrene units. CD experiments show that the fluorophores enhance helix stability primarily through entropic effects. Unfolding temperatures (Tm) increase by up to 7 °C for systems with N-terminal lysine residues and by up to 21 °C for systems in which the first-position Lys is replaced by Ala. Tm values derived from fluorescence measurements (at 50 μM) typically lie within ∼1 °C of those obtained using CD (at 200 μM). Computational modeling in a water continuum using B3LYP-GD3 and M06-2X functionals predicts that face-to-face association of fluorophores can occur while H-bonding within the [(POG)n]3 assembly is retained. Such parallel stacking is consistent with hydrophobically driven stabilization. Labeling collagen peptides with pyrene is a synthetically simple way to promote triple helicity while providing a means to obtain Tm data on relatively dilute samples.

Nanoscale MXene Interlayer and Substrate Adhesion for Lubrication: A Density Functional Theory Study

Understanding the interlayer interaction at the nanoscale in two-dimensional (2D) transition metal carbides and nitrides (MXenes) is important to improve their exfoliation/delamination process and application in (nano)-tribology. The layer-substrate interaction is also essential in (nano)-tribology as effective solid lubricants should be resistant against peeling-off during rubbing. Previous computational studies considered MXenes' interlayer coupling with oversimplified, homogeneous terminations while neglecting the interaction with underlying substrates. In our study, Ti-based MXenes with both homogeneous and mixed terminations are modeled using density functional theory (DFT). An ad hoc modified dispersion correction scheme is used, capable of reproducing the results obtained from a higher level of theory. The nature of the interlayer interactions, comprising van der Waals, dipole-dipole, and hydrogen bonding, is discussed along with the effects of MXene sheet's thickness and C/N ratio. Our results demonstrate that terminations play a major role in regulating MXenes' interlayer and substrate adhesion to iron and iron oxide and, therefore, lubrication, which is also affected by an external load. Using graphene and MoS₂ as established references, we verify that MXenes' tribological performance as solid lubricants can be significantly improved by avoiding -OH and -F terminations, which can be done by controlling terminations via post-synthesis processing.

First-Principles Modeling of Protein/Surface Interactions. Polyglycine Secondary Structure Adsorption on the TiO2 (101) Anatase Surface Adopting a Full Periodic Approach

Computational modeling of protein/surface systems is challenging since the conformational variations of the protein and its interactions with the surface need to be considered at once. Adoption of first-principles methods to this purpose is overwhelming and computationally extremely expensive so that, in many cases, dramatically simplified systems (e.g., small peptides or amino acids) are used at the expenses of modeling nonrealistic systems. In this work, we propose a cost-effective strategy for the modeling of peptide/surface interactions at a full quantum mechanical level, taking the adsorption of polyglycine on the TiO₂ (101) anatase surface as a test case. Our approach is based on applying the periodic boundary conditions for both the surface model and the polyglycine peptide, giving rise to full periodic polyglycine/TiO₂ surface systems. By proceeding this way, the considered complexes are modeled with a drastically reduced number of atoms compared with the finite-analogous systems, modeling the polypeptide structures at the same time in a realistic way. Within our modeling approach, full periodic density functional theory calculations (including implicit solvation effects) and ab initio molecular dynamics (AIMD) simulations at the PBE-D2* theory level have been carried out to investigate the adsorption and relative stability of the different polyglycine structures (i.e., extended primary, β-sheet, and α-helix) on the TiO₂ surface. It has been found that, upon adsorption, secondary structures become partially denatured because the peptide C═O groups form Ti-O═C dative bonds. AIMD simulations have been fundamental to identify these phenomena because thermal and entropic effects are of paramount importance. Irrespective of the simulated environments (gas phase and implicit solvent), adsorption of the α-helix is more favorable than that of the β-sheet because in the former, more Ti-O═C bonds are formed and the adsorbed secondary structure results less distorted with respect to the isolated state. Under the implicit water solvent, additionally, adsorbed β-sheet structures weaken with respect to their isolated states as the H-bonds between the strands are longer due to solvation effects. Accordingly, the results indicate that the preferred conformation upon adsorption is the α-helix over the β-sheet.

Infrared harmonic features of collagen models at B3LYP-D3: From amide bands to the THz region

In this paper, we have studied the vibrational spectral features for the collagen triple helix using a dispersion corrected hybrid density functional theory (DFT-D) approach. The protein is simulated by an infinite extended polymer both in the gas phase and in a water micro-solvated environment. We have adopted proline-rich collagen models in line with the high content of proline in natural collagens. Our scaled harmonic vibrational spectra are in very good agreement with the experiments and allow for the peak assignment of the collagen amide I and III bands, supporting or questioning the experimental interpretation by means of vibrational normal modes analysis. Furthermore, we demonstrated that IR spectroscopy in the THz region can detect the small variations inherent to the triple helix helicity (10/3 over 7/2), thus elucidating the packing state of the collagen. So far, identifying the collagen helicity is only possible by means of crystal x-ray diffraction.

Balancing Cost and Accuracy in Quantum Mechanical Simulations on Collagen Protein Models

Collagen proteins are spread in almost every vertebrate's tissue with mechanical function. The defining feature of this fundamental family of proteins is its well-known collagen triple-helical domain. This helical domain can have different geometries, varying in helical elongation and interstrands contact, as a function of the amino acidic composition. The helical geometrical features play an important role in the interaction of the collagen protein with cell receptors, but for the vast majority of collagen compositions, these geometrical features are unknown. Quantum mechanical (QM) simulations based on the density functional theory (DFT) provide a robust approach to characterize the scenario on the collagen composition-structure relationships. In this work, we analyze the role of the adopted computational method in predicting the collagen structure for two purposes. First, we look for a cost-effective computational approach to apply to a large-scale composition-structure analysis. Second, we attempt to assess the robustness of the predictions by varying the QM methods. Therefore, we have run geometry optimization on periodic models of the collagen protein using a variety of approaches based on the most commonly used DFT functionals (PBE, HSE06, and B3LYP) with and without dispersion correction (D3^ABC). We have coupled these methods with several different basis sets, looking for the highest accuracy/cost ratio. Furthermore, we have studied the performance of the composite HF-3c method and the semiempirical GFN1-xTB method. Our results identify a computational recipe that is potentially capable of predicting collagen structural features in line with DFT simulations, with orders of magnitude reduced computational cost, encouraging further investigations on the topic.

Cost-effective composite methods for large-scale solid-state calculations

Following the development in recent years of progressively more accurate approximations to the exchange-correlation functional, the use of density functional theory (DFT) methods to examine increasingly large and complex systems has grown, in particular for solids and other condensed matter systems. However the cost of these calculations is high, often requiring the use of specialist HPC facilities. As such, for the purpose of large-scale high-throughput screening of material properties, a hierarchy of simplified DFT methods has been proposed that allows rapid electronic structure calculation of large systems, and we have recently extended this scheme to the solid state (sol-3c). Here, we analyze the applicability and scaling of the new sol-3c DFT methods to molecules and crystals composed of light-elements, such as small proteins and model DNA-helices. Furthermore, the calculation of the electronic structure of large to very large porous systems, such as metal-organic frameworks and inorganic nanoparticles, is discussed. The new composite methods have been implemented in the CRYSTAL17 code, which efficiently implements hybrid functionals and enables routine application of the new methods to large-scale calculations of such materials with excellent performance, even with small-scale computing resources.