Institute of Fundamental Technological Research

We perform molecular dynamics simulation on several relevant biological fibrils associated with neurodegenerative diseases such as Aβ40, Aβ42, and α-synuclein systems to obtain a molecular understanding and interpretation of nanomechanical characterization experiments. The computational method is versatile and addresses a new subarea within the mechanical characterization of heterogeneous soft materials. We investigate both the elastic and thermodynamic properties of the biological fibrils in order to substantiate experimental nanomechanical characterization techniques that are quickly developing and reaching dynamic imaging with video rate capabilities. The computational method qualitatively reproduces results of experiments with biological fibrils, validating its use in extrapolation to macroscopic material properties. Our computational techniques can be used for the co-design of new experiments aiming to unveil nanomechanical properties of biological fibrils from a point of view of molecular understanding. Our approach allows a comparison of diverse elastic properties based on different deformations, i.e., tensile (YL), shear (S), and indentation (YT) deformation. From our analysis, we find a significant elastic anisotropy between axial and transverse directions (i.e., YT > YL) for all systems. Interestingly, our results indicate a higher mechanostability of Aβ42 fibrils compared to Aβ40, suggesting a significant correlation between mechanical stability and aggregation propensity (rate) in amyloid systems. That is, the higher the mechanical stability the faster the fibril formation. Finally, we find that α-synuclein fibrils are thermally less stable than β-amyloid fibrils. We anticipate that our molecular-level analysis of the mechanical response under different deformation conditions for the range of fibrils considered here will provide significant insights for the experimental observations.

β-amyloid, atomic force microscopy, mechanical deformation, molecular simulation, proteins, α-synuclein

The elastic network (EN) is a prime model that describes the long-time dynamics of biomolecules. However, the use of harmonic potentials renders this model insufficient for studying large conformational changes of proteins (e.g. stretching of proteins, folding and thermal unfolding). Here, we extend the capabilities of the EN model by using a harmonic approximation described by Lennard-Jones (LJ) interactions for far contacts and native contacts obtained from the standard overlap criterion as in the case of Gō-like models. While our model is validated against the EN model by reproducing the equilibrium properties for a number of proteins, we also show that the model is suitable for the study of large conformation changes by providing various examples. In particular, this is illustrated on the basis of pulling simulations that predict with high accuracy the experimental data on the rupture force of the studied proteins. Furthermore, in the case of DDFLN4 protein, our pulling simulations highlight the advantages of our model with respect to Gō-like approaches, where the latter fail to reproduce previous results obtained by all-atom simulations that predict an additional characteristic peak for this protein. In addition, folding simulations of small peptides yield different folding times for α-helix and β-hairpin, in agreement with experiment, in this way providing further opportunities for the application of our model in studying large conformational changes of proteins. In contrast to the EN model, our model is suitable for both normal mode analysis and molecular dynamics simulation. We anticipate that the proposed model will find applications in a broad range of problems in biology, including, among others, protein folding and thermal unfolding.

Free Energy, protein, elastic network, molecular dynamics, normal mode analysis

The application of coarse-grained (CG) models in biology is essential to access large length and time scales required for the description of many biological processes. The ELNEDIN protein model is based on the well-known MARTINI CG force-field and incorporates additionally harmonic bonds of a certain spring constant within a defined cutoff distance between pairs of residues, in order to preserve the native structure of the protein. In this case, the use of unbreakable harmonic bonds hinders the study of unfolding and folding processes. To overcome this barrier we have replaced the harmonic bonds with Lennard–Jones interactions based on the contact map of the native protein structure as is done in Go̅-like models. This model exhibits very good agreement with all-atom simulations and the ELNEDIN. Moreover, it can capture the structural motion linked to particular catalytic activity in the Man5B protein, in agreement with all-atom simulations. In addition, our model is based on the van der Waals radii, instead of a cutoff distance, which results in a smaller contact map. In conclusion, we anticipate that our model will provide further possibilities for studying biological systems based on the MARTINI CG force-field by using advanced-sampling methods, such as parallel tempering and metadynamics.

Martini force field, protein, molecular simulation, stretching AFM, large conformational changes

Atomic force microscopy (AFM) is a versatile tool to characterise the mechanical properties of biological systems. However, AFM deformations are tiny, which makes impossible the analysis of the mechanical response by experiment. Here, we have employed a simulation protocol to determine the elastic properties of several biopolymers (i.e. biological fibrils). For these systems, the simulation approach is sufficient to provide reliable values for three different types of elastic deformation, i.e. tensile (YL), shear (S), and indentation (YT). Our results enable the comparison of the mechanical properties of these fibrils. In particular, we find a significant elastic anisotropy between axial and transverse directions for all systems. In addition, our methodology is sensitive to molecular packing of the fibrils. Interestingly, our results suggest a significant correlation between mechanical stability and aggregation propensity (rate) in amyloid systems, that is, the higher the mechanical stability the faster the fibril formation takes place.

β-amyloid, α-synuclein, nanoindentation, molecular dynamics, fibril, thermodynamics, nanomechanics, coarse graining

The Elastic Network (EN) is a prime model that describes the long-time dynamics of biomolecules. However, the use of harmonic potentials renders this model insufficient for studying large conformational changes. Here, we propose a model based on the EN, a harmonic approximation described by Lennard-Jones interactions for far contacts, and Go-type native contacts obtained from the standard overlap criterion with the latter describing hydrogen bonds, ionic bridges and hydrophobic/hydrophilic interactions. Our results based on Normal Mode Analysis show excellent agreement with the EN model. Moreover, we apply large forces along the N- and C-termini in order to study a large conformational change (i.e. protein stretching), our pulling simulations reproduce the experimental data on the maximum force of the unfolding of a protein domain. We anticipate that our work will provide new venues for the EN in a broader range of problems in biology, including folding of proteins and protein-docking prediction

Protein, Biomolecules, deformation, AFM, stretching, Normal Modes