Decoding Collagen Triple Helix Stability by Means of Hybrid DFT Simulations

Abstract

Collagen is a protein family defined by a triple helix motif, which comprises roughly one-third of the total human protein content. Decoding the reasons underlying the stability of the collagen triple helix is of both fundamental and applicative relevance, for instance, to guide collagen protein engineering. In principle, full quantum mechanical approaches based on density functional theory (DFT) are ideal to study the subtle physico-chemical features of collagen. Unfortunately, the huge size of the protein prevents the straightforward application of DFT to realistic collagen protein models. In this paper, we propose a new realistic model of the collagen protein based on a periodic approach. The protein model exploits the intrinsic symmetry of the collagen triple helix, dramatically lowering the cost of the simulations. This allows using accurate hybrid DFT simulations (B3LYP-D/TZP) for systematic studies of the collagen protein features. We have tested the proposed model/level-of-theory combination to analyze the well-known proline-conformation/collagen-stability relationship. For this purpose, we have performed an extensive conformational analysis of proline ring within the protein, clarifying some of the reasons linking specific ring conformations to helix positions. Throughout our data analysis, we have also obtained "for free" the collagen inter-strand binding energy. Simulation results demonstrate that London dispersion interactions play the dominant role in the whole helix stability. The good agreement with the experimental data validates the use of the proposed model/level-of-theory to assist the active field of collagen-like peptide synthesis.

The effects of glycine to alanine mutations on the structure of GPO collagen model peptides

“…[37][38][39][40][41][42][43][44] The mean first passage time for this transition from our modelling is in the nanosecond range as well. Furthermore, recent work using density functional approximations 48 gave a difference between endo and exo as roughly 0.6 kcal/mol, which we calculated for a specific example as around 0.2 to 0.3 kcal/mol. Previous work combing experimental techniques with global optimisation techniques 35 shows a range of energy difference between the conformations from close to 0.0 to 0.5 kcal/mol.…”

“…The Y-position hydroxyproline adopts an exo-configuration, 7,34 which stabilises the collagen structure. [45][46][47][48] In contrast, the proline in the X position is more dynamic, and shows transitions between endoand exoconfiguration on a nanosecond time scale. [37][38][39][40][41][42][43][44] The mean first passage time for this transition from our modelling is in the nanosecond range as well.…”

Elucidating the Nature of Interactions in Collagen Triple-Helix Wrapping

“…As shown in Figure , we have used a periodic model, in which the chosen motif is repeated infinitely. The advantages and details of this particular choice to represent collagen compared to finite models have been recently discussed in ref .…”

“…With regard to the composition, we have simulated homotrimeric collagens, in which each strand is made of the repetition of the Gly-Pro-Pro triplet. We chose this composition because it resembles the most diffuse one in collagens, i.e., Gly-Pro-Hyp, but it is simpler to handle (see ref for further details and a precise description of the models). As we want to compare the reasons for the relative energy stability, Δ E (COL) C , between different collagen wrappings, ultimately controlled by the α values, we define the following relationship: where E (COL α ) C is the BSSE-corrected (“C” apex) energy of a fully relaxed collagen triple helix (COL α ) with triplet rotation equal to α minus the energy E (COL 60.0° ) C of the COL with α = 60.0° set as a reference state.…”

Modeling phosphorene and $$\hbox {MoS}_{2}$$ interacting with iron: lubricating effects compared to graphene

“…We took into account London dispersion forces by adopting the D2 scheme [29], using the value for the s 6 scaling factor suggested in the original paper ( s 6 = 0.75). This type of dispersion scheme gave very good results for computing not only organic [30][31][32][33][34] but also inorganic materials properties [35,36]. Recent investigations indicate that more modern dispersion correction schemes are also appropriate for simulating the chemisorption of 2D material on metal and ceramic surfaces [37,38].…”