Biomolecular Adsorption on Nanomaterials: Combining Molecular Simulations with Machine Learning.

Adsorption free energies of 32 small biomolecules (amino acids side chains, fragments of lipids, and sugar molecules) on 33 different nanomaterials, computed by the molecular dynamics - metadynamics methodology, have been analyzed using statistical machine learning approaches. Multiple unsupervised learning algorithms (principal component analysis, agglomerative clustering, and K-means) as well as supervised linear and nonlinear regression algorithms (linear regression, AdaBoost ensemble learning, artificial neural network) have been applied. As a result, a small set of biomolecules has been identified, knowledge of adsorption free energies of which to a specific nanomaterial can be used to predict, within the developed machine learning model, adsorption free energies of other biomolecules. Furthermore, the methodology of grouping of nanomaterials according to their interactions with biomolecules has been presented.

Ab Initio Derived Classical Force Field for Molecular Dynamics Simulations of ZnO Surfaces in Biological Environment.

Zinc oxide nanostructures are used in an ever increasing line of applications in technology and biomedical fields. This requires a detailed understanding of the phenomena that occur at the surface particularly in aqueous environments and in contact with biomolecules. In this work, we used ab initio molecular dynamics (AIMD) simulations to determine structural details of ZnO surfaces in water and to develop a general and transferable classical force field for hydrated ZnO surfaces. AIMD simulations show that water molecules dissociate near unmodified ZnO surfaces, forming hydroxyl groups at about 65% of the surface Zn atoms and protonating 3-coordinated surface oxygen atoms, while the rest of the surface Zn atoms bind molecularly adsorbed waters. Several force field atom types for ZnO surface atoms were identified by analysis of the specific connectivities of atoms. The analysis of the electron density was then used to determine partial charges and Lennard-Jones parameters for the identified force field atom types. The obtained force field was validated by comparison with AIMD results and with available experimental data on adsorption and immersion enthalpies, as well as adsorption free energies of several amino acids in methanol. The developed force field can be used for modeling of ZnO in aqueous and other fluid environments and in interaction with biomolecules.

Axons Embedded in a Tissue May Withstand Larger Deformations Than Isolated Axons Before Mechanoporation Occurs.

Diffuse axonal injury (DAI) is the pathological consequence of traumatic brain injury (TBI) that most of all requires a multiscale approach in order to be, first, understood and then possibly prevented. While in fact the mechanical insult usually happens at the head (or macro) level, the consequences affect structures at the cellular (or microlevel). The quest for axonal injury tolerances has so far been addressed both with experimental and computational approaches. On one hand, the experimental approach presents challenges connected to both temporal and spatial resolution in the identification of a clear axonal injury trigger after the application of a mechanical load. On the other hand, computational approaches usually consider axons as homogeneous entities and therefore are unable to make inferences about their viability, which is thought to depend on subcellular damages. Here, we propose a computational multiscale approach to investigate the onset of axonal injury in two typical experimental scenarios. We simulated single-cell and tissue stretch injury using a composite finite element axonal model in isolation and embedded in a matrix, respectively. Inferences on axonal damage are based on the comparison between axolemma strains and previously established mechanoporation thresholds. Our results show that, axons embedded in a tissue could withstand higher deformations than isolated axons before mechanoporation occurred and this is exacerbated by the increase in strain rate from 1/s to 10/s.

Atomistic Perspective on Biomolecular Adsorption on Functionalized Carbon Nanomaterials under Ambient Conditions.

The use of carbon-based nanomaterials is tremendously increasing in various areas of technological, bioengineering, and biomedical applications. The functionality of carbon-based nanomaterials can be further broadened via chemical functionalization of carbon nanomaterial surfaces. On the other hand, concern is rising on possible adverse effects when nanomaterials are taken up by biological organisms. In order to contribute into understanding of interactions of carbon-based nanomaterials with biological matter, we have investigated adsorption of small biomolecules on nanomaterials using enhanced sampling molecular dynamics. The biomolecules included amino acid side chain analogues, fragments of lipids, and sugar monomers. The adsorption behavior on unstructured amorphous carbon, pristine graphene and its derivatives (such as few-layer graphene, graphene oxide, and reduced graphene oxide) as well as pristine carbon nanotubes, and those functionalized with OH-, COOH-, COO-, NH2-, and NH3+ groups was investigated with respect to surface concentration. An adsorption profile, that is, the free energy as a function of distance from the nanomaterial surfaces, was determined for each molecule and surface using the Metadynamics approach. The results were analyzed in terms of chemical specificity, surface charge, and surface concentration. It was shown that although morphology of the nanomaterial has a limited effect on the adsorption properties, functionalization of the surface by various molecular groups can drastically change the adsorption behavior that can be used in the design of nanosurfaces with highly selective adsorption properties and safe for human health and environment.

Elucidating Axonal Injuries Through Molecular Modelling of Myelin Sheaths and Nodes of Ranvier.

Around half of the traumatic brain injuries are thought to be axonal damage. Disruption of the cellular membranes, or alternatively cytoskeletal damage has been suggested as possible injury trigger. Here, we have used molecular models to have a better insight on the structural and mechanical properties of axon sub-cellular components. We modelled myelin sheath and node of Ranvier as lipid bilayers at a coarse grained level. We built ex-novo a model for the myelin. Lipid composition and lipid saturation were based on the available experimental data. The model contains 17 different types of lipids, distributed asymmetrically between two leaflets. Molecular dynamics simulations were performed to characterize the myelin and node-of-Ranvier bilayers at equilibrium and under deformation and compared to previous axolemma simulations. We found that the myelin bilayer has a slightly higher area compressibility modulus and higher rupture strain than node of Ranvier. Compared to the axolemma in unmyelinated axon, mechanoporation occurs at 50% higher strain in the myelin and at 23% lower strain in the node of Ranvier in myelinated axon. Combining the results with finite element simulations of the axon, we hypothesizes that myelin does not rupture at the thresholds proposed in the literature for axonal injury while rupture may occur at the node of Ranvier. The findings contribute to increases our knowledge of axonal sub-cellular components and help to understand better the mechanism behind axonal brain injury.

Localized Axolemma Deformations Suggest Mechanoporation as Axonal Injury Trigger.

Traumatic brain injuries are a leading cause of morbidity and mortality worldwide. With almost 50% of traumatic brain injuries being related to axonal damage, understanding the nature of cellular level impairment is crucial. Experimental observations have so far led to the formulation of conflicting theories regarding the cellular primary injury mechanism. Disruption of the axolemma, or alternatively cytoskeletal damage has been suggested mainly as injury trigger. However, mechanoporation thresholds of generic membranes seem not to overlap with the axonal injury deformation range and microtubules appear too stiff and too weakly connected to undergo mechanical breaking. Here, we aim to shed a light on the mechanism of primary axonal injury, bridging finite element and molecular dynamics simulations. Despite the necessary level of approximation, our models can accurately describe the mechanical behavior of the unmyelinated axon and its membrane. More importantly, they give access to quantities that would be inaccessible with an experimental approach. We show that in a typical injury scenario, the axonal cortex sustains deformations large enough to entail pore formation in the adjoining lipid bilayer. The observed axonal deformation of 10-12% agree well with the thresholds proposed in the literature for axonal injury and, above all, allow us to provide quantitative evidences that do not exclude pore formation in the membrane as a result of trauma. Our findings bring to an increased knowledge of axonal injury mechanism that will have positive implications for the prevention and treatment of brain injuries.

Role of lipid composition on the structural and mechanical features of axonal membranes: a molecular simulation study.

The integrity of cellular membranes is critical for the functionality of axons. Failure of the axonal membranes (plasma membrane and/or myelin sheath) can be the origin of neurological diseases. The two membranes differ in the content of sphingomyelin and galactosylceramide lipids. We investigate the relation between lipid content and bilayer structural-mechanical properties, to better understand the dependency of membrane properties on lipid composition. A sphingomyelin/phospholipid/cholesterol bilayer is used to mimic a plasma membrane and a galactosylceramide/phospholipid/cholesterol bilayer to mimic a myelin sheath. Molecular dynamics simulations are performed at atomistic and coarse-grained levels to characterize the bilayers at equilibrium and under deformation. For comparison, simulations of phospholipid and phospholipid/cholesterol bilayers are also performed. The results clearly show that the bilayer biomechanical and structural features depend on the lipid composition, independent of the molecular models. Both galactosylceramide or sphingomyelin lipids increase the order of aliphatic tails and resistance to water penetration. Having 30% galactosylceramide increases the bilayers stiffness. Galactosylceramide lipids pack together via sugar-sugar interactions and hydrogen-bond phosphocholine with a correlated increase of bilayer thickness. Our findings provide a molecular insight on role of lipid content in natural membranes.