Structural and physical basis for the elasticity of elastin.

Elastin function is to endow vertebrate tissues with elasticity so that they can adapt to local mechanical constraints. The hydrophobicity and insolubility of the mature elastin polymer have hampered studies of its molecular organisation and structure-elasticity relationships. Nevertheless, a growing number of studies from a broad range of disciplines have provided invaluable insights, and several structural models of elastin have been proposed. However, many questions remain regarding how the primary sequence of elastin (and the soluble precursor tropoelastin) governs the molecular structure, its organisation into a polymeric network, and the mechanical properties of the resulting material. The elasticity of elastin is known to be largely entropic in origin, a property that is understood to arise from both its disordered molecular structure and its hydrophobic character. Despite a high degree of hydrophobicity, elastin does not form compact, water-excluding domains and remains highly disordered. However, elastin contains both stable and labile secondary structure elements. Current models of elastin structure and function are drawn from data collected on tropoelastin and on elastin-like peptides (ELPs) but at the tissue level, elasticity is only achieved after polymerisation of the mature elastin. In tissues, the reticulation of tropoelastin chains in water defines the polymer elastin that bears elasticity. Similarly, ELPs require polymerisation to become elastic. There is considerable interest in elastin especially in the biomaterials and cosmetic fields where ELPs are widely used. This review aims to provide an up-to-date survey of/perspective on current knowledge about the interplay between elastin structure, solvation, and entropic elasticity.

Differential MMP-14 targeting by biglycan, decorin, fibromodulin, and lumican unraveled by in silico approach.

Small leucine-rich proteoglycans (SLRPs) are major regulators of extracellular matrix assembly and cell signaling. Lumican, a member of the SLRPs family, and its derived peptides were shown to possess antitumor activity by interacting directly with the catalytic domain of MMP-14 leading to the inhibition of its activity. The aim of the present report was to characterize by in silico three-dimensional (3D) modeling the structure and the dynamics of four SLRPs including their core protein and their specific polysaccharide chains to assess their capacity to bind to MMP-14 and to regulate its activity. Molecular docking experiments were performed to identify the specific amino acids of MMP-14 interacting with each of the four SLRPs. The inhibition of each SLRP (100 nM) on MMP-14 activity was measured and the constants of inhibition (Ki) were evaluated. The impact of the number of glycan chains, structures, and dynamics of lumican on the interaction with MMP-14 was assessed by molecular dynamics simulations. Molecular docking analysis showed that all SLRPs bind to MMP-14 through their concave face, but in different regions of the catalytic domain of MMP-14. Each SLRPs inhibited significantly the MMP-14 activity. Finally, molecular dynamics showed the role of glycan chains in interaction with MMP-14 and shielding effect of SLRPs. Altogether, the results demonstrated that each SLRP exhibited inhibition of MMP-14 activity. However, the differential targeting of MMP-14 by the SLRPs was shown to be related not only to the core protein conformation but also to the glycan chain structures and dynamics.

X-ray microtomography reveals a lattice-like network within aortic elastic lamellae.

The arterial wall consists of three concentric layers: intima, media, and adventitia. Beyond their resident cells, these layers are characterized by an extracellular matrix (ECM), which provides both biochemical and mechanical support. Elastin, the major component of arterial ECM, is present in the medial layer and organized in concentric elastic lamellae that confer resilience to the wall. We explored the arterial wall structures from C57Bl6 (control), db/db (diabetic), and ApoE-/- (atherogenic) mice aged 3 months using synchrotron X-ray computed microtomography on fixed and unstained tissues with a large image field (8 mm3 ). This approach combined a good resolution (0.83 µm/voxel), large 3D imaging field. and an excellent signal to noise ratio conferred by phase-contrast imaging. We determined from 2D virtual slices that the thickness of intramural ECM structures was comparable between strains but automated image analysis of the 3D arterial volumes revealed a lattice-like network within concentric elastic lamellae. We hypothesize that this network could play a role in arterial mechanics. This work demonstrates that phase-contrast synchrotron X-ray computed microtomography is a powerful technique which to characterize unstained soft tissues.

Early Alterations of Intra-Mural Elastic Lamellae Revealed by Synchrotron X-ray Micro-CT Exploration of Diabetic Aortas.

Diabetes is a major concern of our society as it affects one person out of 11 around the world. Elastic fiber alterations due to diabetes increase the stiffness of large arteries, but the structural effects of these alterations are poorly known. To address this issue, we used synchrotron X-ray microcomputed tomography with in-line phase contrast to image in three dimensions C57Bl6J (control) and db/db (diabetic) mice with a resolution of 650 nm/voxel and a field size of 1.3 mm3. Having previously shown in younger WT and db/db mouse cohorts that elastic lamellae contain an internal supporting lattice, here we show that in older db/db mice the elastic lamellae lose this scaffold. We coupled this label-free method with automated image analysis to demonstrate that the elastic lamellae from the arterial wall are structurally altered and become 11% smoother (286,665 measurements). This alteration suggests a link between the loss of the 3D lattice-like network and the waviness of the elastic lamellae. Therefore, waviness measurement appears to be a measurable elasticity indicator and the 3D lattice-like network appears to be at the origin of the existence of this waviness. Both could be suitable indicators of the overall elasticity of the aorta.

Effects of changes in glycan composition on glycoprotein dynamics: example of N-glycans on insulin receptor.

Glycosylation is among the most common post-translational modifications in proteins, although it is observed in only about 10% of all the protein structures in protein data bank (PDB). Modifications of sugar composition in glycoproteins profoundly impact the overall physiology of the organism. One such example is the development of insulin resistance, which has been attributed to the removal of sialic acid residues from N-glycans of insulin receptor (IR) from various experimental studies. How such modifications affect the glycan-glycoprotein dynamics, and ultimately their function is not clearly understood to date. In this study, we performed molecular dynamics simulations of glycans in different environments. We studied the effects of removal of sialic acid on the glycan, as well as on the dynamics of leucine-rich repeat L1 domain of the IR ectodomain. We observed perturbations in L1 domain dynamics as a result of the removal of sialic acid. The perturbations include an increase in the flexibility of insulin-binding residues, which may affect insulin binding with IR. These changes are accompanied by perturbations in glycan-protein interactions and perturbation of long-range allosteric dynamics. Our observations will further aid in understanding the role of sugars in maintaining homeostasis and how changes in glycan composition may lead to perturbations in homeostasis, ultimately leading to conditions such as insulin resistance.

LIMONADA: A database dedicated to the simulation of biological membranes.

Cellular membranes are composed of a wide diversity of lipid species in varying proportions and these compositions are representative of the organism, cellular type and organelle to which they belong. Because models of these molecular systems simulated by MD steadily gain in size and complexity, they are increasingly representative of specific compositions and behaviors of biological membranes. Due to the number of lipid species involved, of force fields and topologies and because of the complexity of membrane objects that have been simulated, LIMONADA has been developed as an open database allowing to handle the various aspects of lipid membrane simulation. LIMONADA presents published membrane patches with their simulation files and the cellular membrane it models. Their compositions are then detailed based on the lipid identification from LIPID MAPS database plus the lipid topologies and the force field used. LIMONADA is freely accessible on the web at https://limonada.univ-reims.fr/.

Blending Ferulic Acid Derivatives and Polylactic Acid into Biobased and Transparent Elastomeric Materials with Shape Memory Properties.

Thanks to its remarkable properties such as sustainability, compostability, biocompatibility, and transparency, poly-l-lactic acid (PLA) would be a suitable replacement for oil-based polymers should it not suffer from low flexibility and poor toughness, restricting its use to rigid plastic by excluding elastomeric applications. Indeed, there are few fully biobased and biodegradable transparent elastomers-PLA-based or not-currently available. In the last decades, many strategies have been investigated to soften PLA and enhance its toughness and elongation at break by using plasticizers, oligomers, or polymers. This work shows how a ferulic acid-derived biobased additive (BDF) blends with a common rigid and brittle commercial grade of polylactic acid to provide a transparent non-covalently cross-linked elastomeric material with shape memory behavior exhibiting an elongation at break of 434% (vs 6% for pristine PLA). Through a structure-activity relationship analysis conducted with BDF analogues and a modeling study, we propose a mechanism based on π-π stacking to account for the elastomeric properties. Blending ferulic acid derivatives with polylactic acid generates a new family of fully sustainable transparent elastomeric materials with functional properties such as shape memory.

Umbrella Visualization: A method of analysis dedicated to glycan flexibility with UnityMol.

N-glycosylation is a post-translational modification heavily impacting protein functions. Some alterations of glycosylation, such as sialic acid hydrolysis, are related to protein dysfunction. Because of their high flexibility and the many reactive groups of the glycan chains, studying glycans with in vitro methods is a challenging task. Molecular dynamics is a useful tool and probably the only one in biology able to overcome this problem and gives access to conformational information through exhaustive sampling. To better decipher the impact of N-glycans, the analysis and visualization of their influence over time on protein structure is a prerequisite. We developed the Umbrella Visualization, a graphical method that assigns the glycan intrinsic flexibility during a molecular dynamics trajectory. The density plot generated by this method brought relevant informations regarding glycans dynamics and flexibility, but needs further development in order to integrate an accurate description of the protein topology and its interactions. We propose here to transform this analysis method into a visualization mode in UnityMol. UnityMol is a molecular editor, viewer and prototyping platform, coded in C#. The new representation of glycan chains presented in this study takes into account both the main positions adopted by each antenna of a glycan and their statistical relevance. By displaying the collected data on the protein surface, one is then able to investigate the protein/glycan interactions.

AMIDE v2: High-Throughput Screening Based on AutoDock-GPU and Improved Workflow Leading to Better Performance and Reliability.

Molecular docking is widely used in computed drug discovery and biological target identification, but getting fast results can be tedious and often requires supercomputing solutions. AMIDE stands for AutoMated Inverse Docking Engine. It was initially developed in 2014 to perform inverse docking on High Performance Computing. AMIDE version 2 brings substantial speed-up improvement by using AutoDock-GPU and by pulling a total revision of programming workflow, leading to better performances, easier use, bug corrections, parallelization improvements and PC/HPC compatibility. In addition to inverse docking, AMIDE is now an optimized tool capable of high throughput inverse screening. For instance, AMIDE version 2 allows acceleration of the docking up to 12.4 times for 100 runs of AutoDock compared to version 1, without significant changes in docking poses. The reverse docking of a ligand on 87 proteins takes only 23 min on 1 GPU (Graphics Processing Unit), while version 1 required 300 cores to reach the same execution time. Moreover, we have shown an exponential acceleration of the computation time as a function of the number of GPUs used, allowing a significant reduction of the duration of the inverse docking process on large datasets.

Structural Analysis of Nonapeptides Derived from Elastin.

Elastin-derived peptides are released from the extracellular matrix remodeling by numerous proteases and seem to regulate many biological processes, notably cancer progression. The canonical elastin peptide is VGVAPG, which harbors the XGXXPG consensus pattern, allowing interaction with the elastin receptor complex located at the surface of cells. Besides these elastokines, another class of peptides has been identified. This group of bioactive elastin peptides presents the XGXPGXGXG consensus sequence, but the reason for their bioactivity remains unexplained. To better understand their nature and structure-function relationships, herein we searched the current databases for this nonapeptide motif and observed that the XGXPGXGXG elastin peptides define a specific group of tandemly repeated patterns. Further, we focused on four tandemly repeated human elastin nonapeptides, i.e., AGIPGLGVG, VGVPGLGVG, AGVPGLGVG, and AGVPGFGAG. These peptides were analyzed by means of optical spectroscopies and molecular dynamics. Ultraviolet-circular dichroism and Raman spectra are consistent with a mixture of ß-turn, ß-strand, and random-chain secondary elements in aqueous media. Quantitative analysis of their conformations suggested that turns corresponded to half of the total population of structural elements, whereas the remaining half were equally distributed between ß-strand and unordered chains. These distributions were confirmed by molecular dynamics simulations. Altogether, our data suggest that these highly dynamic peptides harbor a type II ß-turn located in their central part. We hypothesize that this structural element could explain their specific bioactivity.

Structure, Dynamics, and Photophysical Properties of a Series of [Pt(NH2R)4]-[PtX4] Complexes.

Theoretical investigations of the structural, dynamics, and photophysical properties of Magnus' green salt complex and its derivatives obtained with different substituent were carried out at different levels of theory with a particular focus on the structure and the dynamics of the complex in the ground state and the excited state. The present work illustrates the results of both the quantum mechanics formulation of the time dependent density functional theory (TDDFT) (LR-TDDFT-QM) and TDDFT based Born-Oppenheimer molecular dynamics (LR-TDDFT-BOMD) within the linear response theory. The appropriate choice of the functional within the LR-TDDFT-QM approach appears to be of major importance to get relatively satisfactory results for the photophysical properties and the absorption spectra of such type of complexes. These effects were characterized through the polarization of the basis set function. Regarding our current knowledge of the properties of Magnus' salts, LR-TDDFT-QM and LR-TDDFT-BOMD were performed on a series of complexes of the type [Pt(NH2R)4]-[PtX4], with R denoting an alkyl group and X is a halogen. The effects of the low and medium range Pt-Pt distance upon the absorption wavelength were explored. Available data in the literature of the electronic structure of such material correlated to our results indicate that, the substituent has a double effect both on the shapes and position of the absorption bands. A perceptive shift of the absorption wavelengths is observed, a consequence of the structure and dynamics of the complex in the ground state. The distortion observed in the Pt-Pt distance is found to be a direct consequence of the rotational motion of groups of atoms. By association of the different theoretical approaches, several interesting properties in the ground state and the excited state were determined.

Exploring the Dual Interaction of Natural Rhamnolipids with Plant and Fungal Biomimetic Plasma Membranes through Biophysical Studies.

Rhamnolipids (RLs) are potential biocontrol agents for crop culture protection. Their mode of action has been proposed as dual, combining plant protection activation and antifungal activities. The present work focuses on the interaction of natural RLs with plant and fungi membrane models at the molecular scale. Representative models were constructed and the interaction with RLs was studied by Fourier transform infrared (FTIR) and deuterium nuclear magnetic resonance (²H NMR) spectroscopic measurements. Molecular dynamic (MD) simulations were performed to investigate RL insertion in lipid bilayers. Our results showed that the RLs fit into the membrane models and were located near the lipid phosphate group of the phospholipid bilayers, nearby phospholipid glycerol backbones. The results obtained with plant plasma membrane models suggest that the insertion of RLs inside the lipid bilayer did not significantly affect lipid dynamics. Oppositely, a clear fluidity increase of fungi membrane models was observed. This effect was related to the presence and the specific structure of ergosterol. The nature of the phytosterols could also influence the RL effect on plant plasma membrane destabilization. Subtle changes in lipid dynamics could then be linked with plant defense induction and the more drastic effects associated with fungal membrane destabilization.

Privileged hydration sites in aromatic side chains: effect on conformational equilibrium.

Water interaction with peptide chains is one of the key structure stabilizing factors in an aqueous environment. Because of its strong polar character, water can bind to both anionic and cationic sites via electrostatic interactions. It can also act as a hydrogen-bond donor or acceptor according to its interactions with different polar groups in the backbone and side chains of peptides and proteins. Based on density functional theory calculations, the present report aims at illustrating the most energetically favorable interaction sites of aromatic side chains of phenylalanine, tyrosine, tryptophan, and histidine (neutral and protonated species) with surrounding water molecules. It was shown that beyond the strong interactions occurring between water and the aromatic ring acceptor/donor sites, such as O-H, N-H and -N[double bond, length as m-dash] groups, weaker interactions with π-electron clouds should also be considered. The latter type of binding, hereafter referred to as Hwπ interaction, involves one of the water hydrogen atoms (Hw) pointing toward the aromatic ring. Upon comparison between the theoretical data obtained from a purely implicit hydration model, i.e. a polarized solvent continuum, and those collected from a mixture of implicit and explicit hydration models, it has been shown that the explicit water molecule binding to aromatic rings affects the relative energies of the rotamers generated by the two side chain torsion angles (χ1 and χ2).

Tuning self-assembly in elastin-derived peptides.

Elastin-derived peptides are gaining increasing interest as potential biomaterials. Previous studies have demonstrated that short elastin-derived peptides are able to self-assemble into fibrils as the entire elastin protein. The motif responsible for that is the XGGZG motif at least three-fold repeated. In this work we have synthesized and studied, at molecular and supramolecular levels, four pentadecapeptides obtained by switching the X and Z residue with leucine and/or valine. We found that the four peptides formed different supramolecular structures corresponding to specific molecular conformations. Our results show that not only the residue type but also the exact position occupied by the residue in the motif is crucial in driving the self-aggregation. The aim of this work is to provide the basis for designing elastin-derived peptides with tunable supramolecular architecture.

Interaction between the elastin peptide VGVAPG and human elastin binding protein.

The elastin binding protein (EBP), a spliced variant of lysosomal ß-galactosidase, is the primary receptor of elastin peptides that have been linked to emphysema, aneurysm and cancer progression. The sequences recognized by EBP share the XGXXPG consensus pattern found in numerous matrix proteins, notably in elastin where the VGVAPG motif is repeated. To delineate the elastin binding site of human EBP, we built a homology model of this protein and docked VGVAPG on its surface. Analysis of this model suggested that Gln-97 and Asp-98 were required for interaction with VGVAPG because they contribute to the definition of a pocket thought to represent the elastin binding site of EBP. Additionally, we proposed that Leu-103, Arg-107, and Glu-137 were essential residues because they could interact with VGVAPG itself. Site-directed mutagenesis experiments at these key positions validated our model. This work therefore provides the first structural data concerning the interaction of the VGVAPG with its cognate receptor. The present structural data should now allow the development of EBP-specific antagonists.

From complex data to clear insights: visualizing molecular dynamics trajectories.

Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.

In silico validation of hyaluronic acid - drug conjugates based targeted drug delivery for the treatment of COVID-19.

The impact of COVID-19 urges scientists to develop targeted drug delivery to manage Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral infections with a fast recovery rate. The aim of the study is to develop Hyaluronic Acid (HA) drug conjugates of viral drugs to target two important enzymes (Mpro and PLpro) of SARS-CoV-2. Three antiviral drugs, namely Dexamethasone (DEX), Favipiravir (FAV), and Remdesivir (REM), were chosen for HA conjugation due to their reactive functional groups. Free forms of drugs (DEX, FAV, REM) and HA drug conjugates (HA-DEX, HA-FAV, HA-REM, HA-RHA, HA-RHE) were validated against Mpro (PDB ID 6LU7) and PLpro (PDB 7LLZ), which play an essential role in the replication and reproduction of the SARS-CoV-2 virus. The results of the present study revealed that HA-drug conjugates possess higher binding affinity and the best docking score towards the Mpro and PLpro target proteins of SARS-CoV-2 than their free forms of drugs. ADMET screening resulted that HA-drug conjugates exhibited better pharmacokinetic profiles than their pure forms of drugs. Further, molecular dynamic simulation studies, essential dynamics and free energy landscape analyses show that HA antiviral drug conjugates possess good trajectories and energy status, with the PLpro target protein (PDB 7LLZ) of SARS-CoV-2 through long-distance (500 ns) simulation screening. The research work recorded the best drug candidate for Cell-Targeted Drug Delivery (CTDD) for SARS-CoV-2-infected cells through hyaluronic acid conjugates of antiviral drugs.Communicated by Ramaswamy H. Sarma.

Unraveling the inhibitory mechanism of adenylyl cyclase 8E: New insights into regulatory pathways of cAMP signal integration.

Adenylyl Cyclase 8E (AC8E), which lacks part of M1 transmembrane domain, has been previously shown to dimerize with AC3 and down-regulate its activity, but the molecular mechanism of this inhibitory effect has remained elusive. Here, we first show that AC8E also inhibits AC2 and AC6, highlighting the functional importance of this novel regulatory mechanism in the cAMP signaling pathway across AC families. We then completed the partial structure of Bos taurus AC9 using combinations of comparative modeling and fold recognition methods, and used this as a template to build the first full 3D-models of AC8 and AC8E. These models evidenced that the lack of M1 transmembrane domain of AC8E shifts the N-terminal domain, which impacts the orientation of the helical domains, thus affecting the catalytic site. This was confirmed in living cells with cAMP imaging, where we showed that the N-terminal domain is required for reducing cAMP production. Our data also show that AC8E prevents the translocation of other ACs towards the plasma membrane, further reducing the cAMP responsiveness to extracellular signals. This newly discovered dual inhibitory mechanism provides an additional level of regulation of cAMP-dependent signals integration.

Sialic acids cleavage induced by elastin-derived peptides impairs the interaction between insulin and its receptor in adipocytes 3T3-L1.

The insulin receptor (IR) plays an important role in insulin signal transduction, the defect of which is believed to be the root cause of type 2 diabetes. In 3T3-L1 adipocytes as in other cell types, the mature IR is a heterotetrameric cell surface glycoprotein composed of two α subunits and two ß subunits. Our objective in our study, is to understand how the desialylation of N-glycan chains, induced by elastin-derived peptides, plays a major role in the function of the IR. Using the 3T3-L1 adipocyte line, we show that removal of the sialic acid from N-glycan chains (N893 and N908), induced by the elastin receptor complex (ERC) and elastin derived-peptides (EDPs), leads to a decrease in the autophosphorylation activity of the insulin receptor. We demonstrate by molecular dynamics approaches that the absence of sialic acids on one of these two sites is sufficient to generate local and general modifications of the structure of the IR. Biochemical approaches highlight a decrease in the interaction between insulin and its receptor when ERC sialidase activity is induced by EDPs. Therefore, desialylation by EDPs is synonymous with a decrease of IR sensitivity in adipocytes and could thus be a potential source of insulin resistance associated with diabetic conditions.

Modelling and Simulations of Extracellular Glycoproteins.

While the knowledge of protein structure and function has seen vast advances in previous decades, the understanding of how their posttranslational modifications, such as glycosylations, influence their structure and function remains poor. However, advances in in silico methodologies to study glycosylations in recent past have enabled us to study this and understand the role of glycosylations in protein structure and function in ways that would not be possible by conventional experimental methods. In this chapter, we will demonstrate how to leverage these methodologies to study glycoproteins and their structural and dynamic properties using molecular modelling techniques.