173 research outputs found
Coarse-grained model of adsorption of blood plasma proteins onto nanoparticles
No full textWe present a coarse-grained model for evaluation of interactions of globular proteins with nanoparticles (NPs). The protein molecules are represented by one bead per aminoacid and the nanoparticle by a homogeneous sphere that interacts with the aminoacids via a central force that depends on the nanoparticle size. The proposed methodology is used to predict the adsorption energies for six common human blood plasma proteins on hydrophobic charged or neutral nanoparticles of different sizes as well as the preferred orientation of the molecules upon adsorption. Our approach allows one to rank the proteins by their binding affinity to the nanoparticle, which can be used for predicting the composition of the NP-protein corona. The predicted ranking is in good agreement with known experimental data for proteinadsorption on surfaces.European Commission - Seventh Framework Programme (FP7
Shape-based nanoparticle classification using machine learning
No full textThe accurate classification of nanoparticles (NPs) based on their shapes is crucial for understanding their physical-chemical properties and predict their bioactivity. Nowadays, synthesis method are able to produce a broad range of shapes, such as spheres, cubes and branched NPs and commonly these NP shapes are only described qualitative. This study presents NP descriptors obtained from NPs contours extracted from electron microscopy images. Descriptors such as Fourier descriptors, aspect ratio, and compactness are then used as input for machine learning classifiers. In particular, XGBoost, Random Forest, and neural networks are explored and the their performances are compared and discussed
Low-Resolution Models for the Interaction Dynamics of Coated Gold Nanoparticles with β2-microglobulin
No full textA large number of low-resolution models have been proposed in the last decades to reduce the computational cost of molecular dynamics simulations for bio-nano systems, such as those involving the interactions of proteins with functionalized nanoparticles (NPs). For the proteins, “minimalist” models at the one-bead-per residue (Cα-based) level and with implicit solvent are well established. For the gold NPs, widely explored for biotechnological applications, mesoscale (MS) models treating the NP core with a single spheroidal object are commonly proposed. In this representation, the surface details (coating, roughness, etc.) are lost. These, however, and the specificity of the functionalization, have been shown to have fundamental roles for the interaction with proteins. We presented a mixed-resolution coarse-grained (CG) model for gold NPs in which the surface chemistry is reintroduced as superficial smaller beads. We compared molecular dynamics simulationsoftheamyloid β2-microglobulinrepresentedattheminimalistlevelinteractingwithNPs represented with this model or at the MS level. Our finding highlights the importance of describing the surface of the NP at a finer level as the chemical-physical properties of the surface of the NP are crucial to correctly understand the protein-nanoparticle association
Bionano Interactions: A Key to Mechanistic Understanding of Nanoparticle Toxicity
No full textThe new paradigm in the assessment of toxicity of nanomaterials relies on a mechanistic understanding of the organism’s response to an exposure to foreign materials from the initial, molecular level interactions to signaling and regulatory cascades. Here, we present a methodology to quantify the essential interactions at the bionano interface, which can be used in combination with the adverse outcome pathway analysis to build mechanism-based predictive schemes for toxicity assessments. We introduce a set of new, advanced descriptors of the nanomaterials, which refer to their ability to bind biomolecules and trigger the pathways via the molecular initiating events.European Commission Horizon 2020European Commission - Seventh Framework Programme (FP7
Distinct binding strategies of plasma proteins on gold surfaces: flexibility versus stability in the protein corona formation
No full textWhen in contact with biological matrices, gold nanoparticles (AuNPs) become coated with a protein corona, which governs their biological identity and mediates interactions with cells and tissues. This study explores the adsorption behavior and conformational dynamics of two key plasma proteins, human serum albumin (HSA) and transferrin (TRF), on AuNP surfaces using Brownian Dynamics (BD) and atomistic Molecular Dynamics (MD) simulations. The results reveal multiple binding mechanisms for HSA and TRF on Au (111) surfaces. HSA exhibits significant reorientations during binding, initiated by negatively charged residues and stabilized by hydrophilic amino acids, with its structural rigidity requiring multiple reversible anchoring attempts before achieving more energetically favorable interactions. In contrast, TRF demonstrates rapid and stable binding due to its intrinsic local flexibility, retaining docked orientations with minimal reorientation. While both proteins utilize electrostatic interactions to approach the surface, TRF’s disordered structure enables swift adaptation, whereas HSA’s rigidity supports strong interactions upon relaxation. These findings highlight contrasting binding strategies, with TRF prioritizing speed and flexibility, and HSA exploiting domain rearrangements for sustained stability. Importantly, the results obtained at the all-atom level of resolution are critical for the development of coarse-grained and mesoscale models. The approach in classifying protein orientation enhances our understanding of the protein corona’s shape and morphology and could advance its effective representation in lower-resolution models. The insights gained from these simulations enable us to analyze the different adsorption behavior of TRF and HSA, providing a deeper understanding of how their structural properties influence protein corona formation
Academic administration and management scenarios on the semantic web
No full textThis paper describes scenarios developed as part of the Ed-Scene project which aims to provide intelligent services to the academic stakeholders (teachers, students, administrators, employers) by semantically managing learning resources in order to provide a value-added semantics layer where semantic annotation, query and reasoning can be carried out to support management requirements in Ed-Scene scenarios, such as teaching module allocation among lecturers, interpretation of students’ transcripts in career advice
Academic Program Administration via Semantic Web – A Case Study
No full textGenerally, administrative systems in an academic environment are disjoint and support independent queries. The objective in this work is to semantically connect these independent systems to provide support to queries run on the integrated platform. The proposed framework, by enriching educational material in the legacy systems, provides a value-added semantics layer where activities such as annotation, query and reasoning can be carried out to support management requirements. We discuss the development of this ontology framework with a case study of UAE University program administration to show how semantic web technologies can be used by administration to develop student profiles for better academic program management
Role of contact inhibition of locomotion and junctional mechanics in epithelial collective responses to injury
No full textEpithelial tissues form physically integrated barriers against the external environment protecting organs from infection and invasion. Within each tissue, epithelial cells respond to different challenges that can potentially compromise tissue integrity. In particular, cells collectively respond to injuries by reorganizing their cell-cell junctions and migrating directionally towards the sites of damage. Notwithstanding, the mechanisms that drive collective responses in epithelial aggregates remain poorly understood. In this work, we develop a minimal mechanistic model that is able to capture the essential features of epithelial collective responses to injuries. We show that a model that integrates the mechanics of cells at the cell-cell and cell-substrate interfaces as well as contact inhibition of locomotion (CIL) correctly predicts two key properties of epithelial response to injury as: (1) local relaxation of the tissue and (2) collective reorganization involving the extension of cryptic lamellipodia that extend, on average, up to 3 cell diameters from the site of injury and morphometric changes in the basal regions. Our model also suggests that active responses (like the actomyosin purse string and softening of cell-cell junctions) are needed to drive morphometric changes in the apical region. Therefore, our results highlight the importance of the crosstalk between junctional biomechanics, cell substrate adhesion, and CIL, as well as active responses, in guiding the collective rearrangements that are required to preserve the epithelial barrier in response to injury.European Commission - European Regional Development FundHigher Education AuthorityIrish Research CouncilNational Health and Medical Research Council of AustraliaAustralian Research CouncilAustralian Cancer Research Foundatio
Effects of flexibility in coarse-grained models for bovine serum albumin and immunoglobulin G
No full textWe construct a coarse-grained, structure-based, low-resolution, 6-bead flexible model of bovine serum albumin (BSA, PDB: 4F5S), which is a popular example of a globular protein in biophysical research. The model is obtained via direct Boltzmann inversion using all-atom simulations of a single molecule, and its particular form is selected from a large pool of 6-bead coarse-grained models using two suitable metrics that quantify the agreement in the distribution of collective coordinates between all-atom and coarse-grained Brownian dynamics simulations of solutions in the dilute limit. For immunoglobulin G (IgG), a similar structure-based 12-bead model has been introduced in the literature [Chaudhri et al., J. Phys. Chem. B 116, 8045 (2012)] and is employed here to compare findings for the compact BSA molecule and the more anisotropic IgG molecule. We define several modified coarse-grained models of BSA and IgG, which differ in their internal constraints and thus account for a variation of flexibility. We study denser solutions of the coarse-grained models with purely repulsive molecules (achievable by suitable salt conditions) and address the effect of packing and flexibility on dynamic and static behavior. Translational and rotational self-diffusivity is enhanced for more elastic models. Finally, we discuss a number of effective sphere sizes for the BSA molecule, which can be defined from its static and dynamic properties. Here, it is found that the effective sphere diameters lie between 4.9 and 6.1 nm, corresponding to a relative spread of about ±10% around a mean of 5.5 nm
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