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Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22∗ to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins., Journal of Chemical Theory and Computation, 18 (3), ISSN:1549-9618, ISSN:1549-9626

Intrinsically disordered proteins (IDPs) play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and forcefields. Nevertheless, differences in fine details emerge from varying forcefield/sampling method combinations. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which can be common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field/enhanced sampling method combinations for accurate structural and thermodynamic information in the study of general disordered proteins.

Intrinsically disordered proteins (IDPs) play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and forcefields. Nevertheless, differences in fine details emerge from varying forcefield/sampling method combinations. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which can be common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field/enhanced sampling method combinations for accurate structural and thermodynamic information in the study of general disordered proteins.

Background: The work presented here is focused on the development of a comprehensive theoretical model for the description of drug release from a double - layer bioresorbable suture thread and the therapeutic efficacy of the active compounds delivered in the surrounding tissue. Methods: In particular, the system under investigation is composed of a core of slow-degrading polylactic- acid-co-ε-caprolactone (PLCL), where an antibiotic compound (Vancomycin) is loaded, surrounded by a shell of a fast-degrading polylactic-co-glycolic acid (PLGA) which contains an anesthetic drug (Lidocaine hydrochloride) for the post-surgical pain relief. Results: This system is of potential interest for the combined effects provided by the different active molecules, but the different release and polymer degradation dynamics, as well as their mutual influence, do not allow an intuitive a priori evaluation of device behavior, which can be rationalized through mathematical modeling. The model takes into account the main involved phenomena (polymer degradation and diffusion of the drugs within the device and the tissue, where they are metabolized) and their synergic effects on the overall system behavior. Conclusion: Model results are discussed in order to quantify the impact of the main design parameters on device performances, thanks to the use of phase diagrams (which show drug effect in time and space) whose insights are summarized in order to determine a design space according to the specific needs.

Circulating nucleic acids, such as short interfering RNA (siRNA), regulate many biological processes; however, the mechanism by which these molecules enter the cell is poorly understood. The role of extracellular‐matrix‐derived polymers in binding siRNAs and trafficking them across the plasma membrane is reported. Thermal melting, dynamic light scattering, scanning electron microscopy, and computational analysis indicate that hyaluronic acid can stabilize siRNA via hydrogen bonding and Van der Waals interactions. This stabilization facilitated HA size‐ and concentration‐dependent gene silencing in a CD44‐positive human osteosarcoma cell line (MG‐63) and in human mesenchymal stromal cells (hMSCs). This native HA‐based siRNA transfection represents the first report on an anionic, non‐viral delivery method that resulted in approximately 60 % gene knockdown in both cell types tested, which correlated with a reduction in translation levels. acceptedVersion

The use of methods at molecular scale for the discovery of new potential active ligands, as well as previously unknown binding sites for target proteins, is now an established reality. Literature offers many successful stories of active compounds developed starting from insights obtained in silico and approved by Food and Drug Administration (FDA). One of the most famous examples is raltegravir, a HIV integrase inhibitor, which was developed after the discovery of a previously unknown transient binding area thanks to molecular dynamics simulations. Molecular simulations have the potential to also improve the design and engineering of drug delivery devices, which are still largely based on fundamental conservation equations. Although they can highlight the dominant release mechanism and quantitatively link the release rate to design parameters (size, drug loading, et cetera), their spatial resolution does not allow to fully capture how phenomena at molecular scale influence system behavior. In this scenario, the “computational microscope” offered by simulations at atomic scale can shed light on the impact of molecular interactions on crucial parameters such as release rate and the response of the drug delivery device to external stimuli, providing insights that are difficult or impossible to obtain experimentally. Moreover, the new paradigm brought by nanomedicine further underlined the importance of such computational microscope to study the interactions between nanoparticles and biological components with an unprecedented level of detail. Such knowledge is a fundamental pillar to perform device engineering and to achieve efficient and safe formulations. After a brief theoretical background, this review aims at discussing the potential of molecular simulations for the rational design of drug delivery systems., Journal of Controlled Release, 332, ISSN:0168-3659, ISSN:1873-4995

The lack of accurate and easily applicable methods for the diagnosis of liver fibrosis, a disease characterized by an accumulation of the extracellular matrix released by activated hepatic stellate cells (HSCs), has been a major limitation for the clinical management of liver diseases. The identification of biomarkers specific to liver microstructure alterations, combined with a non-invasive optical imaging modality, could guide clinicians towards a therapeutic strategy. In this study, structural information of the insulin-like growth factor 2 receptor (IGF2R), an overexpressed protein on activated HSCs, was used for in silico screening of novel IGF2R-specific peptide ligands. Molecular dynamics simulations, followed by computational alanine scanning of the IGF2R/IGF2 complex, led to the identification of a putative peptide sequence containing the most relevant amino acids for the receptor–ligand interaction (IGF2 E12-C21). The Residue Scan tool, implemented in the MOE software, was then used to optimize the binding affinity of this sequence by amino acid mutations. The designed peptides and their associated scrambled sequences were fluorescently labelled and their binding affinity to LX-2 cells (model for activated human HSCs) was tested using flow cytometry and confocal microscopy. In vitro binding was verified for all sequences (KD ≤ 13.2 μM). With respect to the putative binding sequence, most mutations led to an increased affinity. All sequences have shown superior binding compared to their associated scrambled sequences. Using HPLC, all peptides were tested in vitro for their proteolytic resistance and showed a stability of ≥60% intact after 24 h at 37 °C in 50% v/v FBS. In view of their prospective diagnostic application, a comparison of binding affinity was performed in perpetuated and quiescent-like LX-2 cells. Furthermore, the IGF2R expression for different cell phenotypes was analysed by a quantitative mass spectrometric approach. Our peptides showed increased binding to the perpetuated cell state, indicating their good selectivity for the diagnostically relevant phenotype. In summary, the increased binding affinity of our peptides towards perpetuated LX-2 cells, as well as the satisfactory proteolytic stability, proves that the in silico designed sequences offer a new potential strategy for the targeting of hepatic fibrosis., Journal of Materials Chemistry B, 9 (8), ISSN:2050-7518, ISSN:2050-750X

In this work we present a method to investigate the fluid-dynamics of a 3D, real-scale spiral jet mill when caking is occurring. CFD simulations are employed to deeply study the pressure and the velocity fields of the gas phase when the nozzles inlet pressure and the chamber diameter are varied to mimic the condition generated by the aggregates formation during the micronizaton process. The computational model is built replicating the experimental observation consisting in the fact that most of the crusts form on the outer wall of the chamber. Simulations underline that caking causes the deterioration of the classification capabilities of the system if the gas mass flow rate is kept constant at nozzles, allowing larger particles for escaping the system. It is shown that it is possible to mitigate this phenomenon by gradually reducing the gas mass-flow rate to keep constant the nozzles absolute pressure. This keeps unchanged the fluid spin ratio and the classification characteristics when caking is advancing.

Background: The high variability in clinical responses observed in cancer patients highlights the need of a tailored therapeutic approach. A possible modality is to assess drugs sensitivity directly in the patients, by introducing small drug delivering devices in tumor sites for a very short period and then looking at the local anti-tumor effect. Here, we present the design of an innovative drug eluting device and its test with the BTK inhibitor ibrutinib as an example of small molecules. Methods: Mathematical models considered factors related to drug (MW), physical properties, desired concentrations in surrounding tissue, polymers and tissue physical features to identify the optimal polymers and the drug loading for the desired release profile over 24h. In vitro proliferation was measured with the MTT assay, in vivo experiments done in NOD-SCID mice (license TI05/2021), and immunohistochemistry on FFPE xenograft sections stained for Ki67 and cleaved caspase 3 (CASP-3). Results: Device was designed as an arrow-shaped cylinder, with flat end and flatter sections to be filled with the drug-eluting polymers. Prototypes were built in nylon6,6, a biocompatible but stable polymer. Ibrutinib was incorporated in low MW polyester poly-ε-caprolactone (PCL) as biopolymer by solvent casting. Polymeric coating onto devices was done with a dedicated automatic device.Devices loaded with biopolymer and different concentrations of ibrutinib or “empty” biopolymers were first in vitro tested using diffuse large B cell lymphoma (DLBCL) cell lines. Over 72h, devices with drug inhibited proliferation of the ibrutinib-sensitive TMD8 and OCI-Ly10 cell lines, but not of the ibrutinib-resistant SU-DHL-2 and U2932. No effect was seen with devices with ibrutinib-free biopolymers. Devices, empty or loaded with ibrutinib (5μg), were then inserted in xenografts of ibrutinib-sensitive cell line OCI-Ly10 and ibrutinib resistant U2932. After 24h, mice were sacrificed and xenografts analyzed. By Ki67 and CASP-3 a reduced cell proliferation and an increased apoptosis in the region surrounding the device was observed in the ibrutinib-sensitive xenografts, conversely nor reduced cell proliferation nor apoptosis induction were identified in the ibrutinib-resistant xenografts. Conclusions: We have created a prototype of a device that can locally release drugs allowing the evaluation of anti-tumor activity, optimizing cures tailored to single patient. The system can be further developed to include multiple drugs, including e.g. antibodies. Citation Format: Giuseppe Perale, Eugenio Gaudio, Tommaso Casalini, Luca Aresu, Anna Rita De Corso, Filippo Spriano, Chiara Tarantelli, Anastasios Stathis, Andrea Castrovinci, Francesco Bertoni. A novel implantable device to in vivo assess anti-cancer agents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1879.

Computational techniques are now a complementary tool to experimental activity for a comprehensive characterization of biomedical devices for drug delivery. They allow achieving a mechanistic and fundamental understanding of the systems of interest and rationalizing experimental data. The acquired knowledge can be fruitfully employed to optimize the design of the device, which does not behave as a “black box” anymore, to obtain the desired performances. Starting from the seminal contribution of Prof. Takeru Higuchi with the well-known Higuchi equation in 1961, modeling of drug delivery devices has now embraced not only a wide range of systems but a likewise variety of computational techniques. This chapter aims at providing to the interested reader a brief overview of the available approaches employed in the literature, along with specific examples of applications on system of potential interest for spinal cord injury repair.

The advent of nanomedicine brought a new paradigm in the biomedical field, introducing novel health care solutions based on nanosized carriers. In particular, nanoparticles attracted a lot of interest as devices for drug and vaccine delivery, imaging and diagnostic purposes. By virtue of their size (which ranges from 1 to 1000 nm and thus comparable to molecules of biological interest, like proteins), such nanocarriers exhibit some peculiar features that make nanomedicine a unique discipline. Indeed, nanoparticles can spread all over the body (including cells and organelles) and when injected in body fluids they interact with biological components (such as proteins, carbohydrates, small molecules, etc.). This aspect cannot be underestimated, since it can lead to unpredictable toxic effects as well as substantial deviations from the expected cellular uptake. In addition, nanoparticles must be designed so that they mainly target the area of interest (e.g., cancer), avoiding accumulation and drug release in healthy organs. This chapter aims at answering the following question: how can first principles mathematical modeling deal with the new challenges and issues introduced by nanomedicine?

Two different modeling approaches are applied in this work to the simulation of fluidized bed reactors containing solid particles of Geldart A-B type and operated at typical conditions for polyolefins production. On one side, a fully detailed computational fluid-dynamics (CFD) model is developed, considering a 2D planar geometry and a multi-fluid description with kinetic theory of granular flows. On the other, a conventional three-phase, 1D compartmentalized model (SCM) is also developed, implementing the fluid dynamic description based on popular, semi-empirical relationships available in the literature. Given the huge difference of computational effort associated with the corresponding numerical solutions, our aim is to confirm the reliability of the simplified model by comparison with the results of the detailed CFD model. The results show that the oversimplified compartmentalized approach is capable to predict the solid mixing features established inside the reactor operated in bubbling fluidization regime with good reliability for non-reactive polyethylene particles. Average solid volume fractions are particularly close to the values predicted by the CFD model when monodisperse particles are considered inside the examined range of gas velocity values. A generally good agreement is also found when solids with broad size distribution are analyzed., Macromolecular Reaction Engineering, 16 (6), ISSN:1862-832X, ISSN:1862-8338

Synthetic scaffolds that possess an intrinsic capability to protect and sequester sensitive growth factors is a primary requisite for developing successful tissue engineering strategies. Growth factors such as recombinant human bone morphogenetic protein-2 (rhBMP-2) is highly susceptible to premature degradation and to provide a meaningful clinical outcome require high doses that can cause serious side effects. We discovered a unique strategy to stabilize and sequester rhBMP-2 by enhancing its molecular interactions with hyaluronic acid (HA), an extracellular matrix (ECM) component. We found that by tuning the initial protonation state of carboxylic acid residues of HA in a covalently crosslinked hydrogel modulate BMP-2 release at physiological pH by minimizing the electrostatic repulsion and maximizing the Van der Waals interactions. At neutral pH, BMP-2 release is primarily governed by Fickian diffusion, whereas at acidic pH both diffusion and electrostatic interactions between HA and BMP-2 become important as confirmed by molecular dynamics simulations. Our results were also validated in an in vivo rat ectopic model with rhBMP-2 loaded hydrogels, which demonstrated superior bone formation with acidic hydrogel as compared to the neutral counterpart. We believe this study provides new insight on growth factor stabilization and highlights the therapeutic potential of engineered matrices for rhBMP-2 delivery and may help to curtail the adverse side effects associated with the high dose of the growth factor. De två första författarna delar förstaförfattarskapet.

Liposomal delivery is a well-established approach to increase the therapeutic index of drugs, mainly in the field of cancer chemotherapy. Here, we report the preparation and characterization of a new liposomal formulation of a derivative of lomeguatrib, a potent O6-methylguanine-DNA methyltransferase (MGMT) inactivator. The drug had been tested in clinical trials to revert chemoresistance, but was associated with a low therapeutic index. A series of lomeguatrib conjugates with distinct alkyl chain lengths - i.e. C12, C14, C16, and C18 - was synthesized, and the MGMT depleting activity as well as cytotoxicity were determined on relevant mouse and human glioma cell lines. Drug-containing liposomes were prepared and characterized in terms of loading and in vitro release kinetics. The lipophilic lomeguatrib conjugates did not exert cytotoxic effects at 5 μM in the mouse glioma cell line and exhibited a similar MGMT depleting activity pattern as lomeguatrib. Overall, drug loading could be improved by up to 50-fold with the lipophilic conjugates, and the slowest leakage was achieved with the C18 derivative. The present data show the applicability of lipophilic lomeguatrib derivatization for incorporation into liposomes, and identify the C18 derivative as the lead compound for in vivo studies.

Polymeric nanoparticles, which by virtue of their size (1–1000 nm) are able to penetrate even into cells, are attracting increasing interest in the emerging field of nanomedicine, as devices for, e.g., drugs or vaccines delivery. Because of the involved dimensional scale in the nanoparticle/cell membrane interactions, modeling approaches at molecular level are the natural choice in order to understand the impact of nanoparticle formulation on cellular uptake mechanisms. In this work, the passive permeation across cell membrane of oligomers made of two employed polymers in the biomedical field [poly-D,L-lactic acid (PDLA) and poly(3-hydroxydecanoate) (P3HD)] is investigated at fundamental atomic scale through molecular dynamics simulations. The free energy profile related to membrane crossing is computed adopting umbrella sampling. Passive permeation is also investigated using a coarse-grained model with MARTINI force field, adopting well-tempered metadynamics. Simulation results showed that P3HD permeation is favored with respect to PDLA by virtue of its higher hydrophobicity. The free energy profiles obtained at full atomistic and coarse-grained scale are in good agreement each for P3HD, while only a qualitative agreement was obtained for PDLA. Results suggest that a reparameterization of non-bonded interactions of the adopted MARTINI beads for the oligomer is needed in order to obtain a better agreement with more accurate simulations at atomic scale.

Injection of nanoparticles (NP) into the bloodstream leads to the formation of a so-called “nano–bio” interface where dynamic interactions between nanoparticle surfaces and blood components take place. A common consequence is the formation of the protein corona, that is, a network of adsorbed proteins that can strongly alter the surface properties of the nanoparticle. The protein corona and the resulting structural changes experienced by adsorbed proteins can lead to substantial deviations from the expected cellular uptake as well as biological responses such as NP aggregation and NP-induced protein fibrillation, NP interference with enzymatic activity, or the exposure of new antigenic epitopes. Achieving a detailed understanding of the nano–bio interface is still challenging due to the synergistic effects of several influencing factors like pH, ionic strength, and hydrophobic effects, to name just a few. Because of the multiscale complexity of the system, modeling approaches at a molecular level represent the ideal choice for a detailed understanding of the driving forces and, in particular, the early events at the nano–bio interface. This review aims at exploring and discussing the opportunities and perspectives offered by molecular modeling in this field through selected examples from literature.

Polylactic acid (PLA)-based polymers are ubiquitous in the biomedical field thanks to their combination of attractive peculiarities: biocompatibility (degradation products do not elicit critical responses and are easily metabolized by the body), hydrolytic degradation in situ, tailorable properties, and well-established processing technologies. This led to the development of several applications, such as bone fixation screws, bioresorbable suture threads, and stent coating, just to name a few. Nanomedicine could not be unconcerned by PLA-based materials as well, where their use for the synthesis of nanocarriers for the targeted delivery of hydrophobic drugs emerged as a new promising application. The purpose of the here presented review is two-fold: on one side, it aims at providing a broad overview of PLA-based materials and their properties, which allow them gaining a leading role in the biomedical field; on the other side, it offers a specific focus on their recent use in nanomedicine, highlighting opportunities and perspectives.

Chitosan is a natural polymer revealing an increased potential to be used in different biomedical applications, including drug delivery systems, and tissue engineering. It implies the evaluation of the organism response to the biomaterial implantation. Low-molecular degradation products, the chito-oligomers, are resulting mainly from the influence of enzymes, which are found in the organism fluids. Within this study, we have performed the computational assessment of pharmacological profiles and toxicological effects on human health of small chito-oligomers with distinct molecular weights, deacetylation degrees, and acetylation patterns. Our approach is based on the fact that regulatory agencies and researchers in the drug development field rely on the use of modeling to predict biological effects and to guide decision making. To be considered as valid for regulatory purposes, every model that is used for predictions should be associated with a defined toxicological endpoint and has appropriate robustness and predictivity. Within this context, we have used FAF-Drugs4, SwissADME, and PreADMET tools to predict the oral bioavailability of chito-oligomers and SwissADME, PreADMET, and admetSAR2.0 tools to predict their pharmacokinetic profiles. The organs and genomic toxicities have been assessed using admetSAR2.0 and PreADMET tools but specific computational facilities have been also used for predicting different toxicological endpoints: Pred-Skin for skin sensitization, CarcinoPred-EL for carcinogenicity, Pred-hERG for cardiotoxicity, ENDOCRINE DISRUPTOME for endocrine disruption potential and Toxtree for carcinogenicity and mutagenicity. Our computational assessment showed that investigated chito-oligomers reflect promising pharmacological profiles and limited toxicological effects on humans, regardless of molecular weight, deacetylation degree, and acetylation pattern. According to our results, there is a possible inhibition of the organic anion transporting peptides OATP1B1 and/or OATP1B3, a weak potential of cardiotoxicity, a minor probability of affecting the androgen receptor, and phospholipidosis. Consequently, these results may be used to guide or to complement the existing in vitro and in vivo toxicity tests, to optimize biomaterials properties and to contribute to the selection of prototypes for nanocarriers.

Because of their inherent biocompatibility and tailorable network design, hydrogels meet an increasing interest as biomaterials for the fabrication of controlled drug delivery devices. In this regard, mathematical modeling can highlight release mechanisms and governing phenomena, thus gaining a key role as complementary tool for experimental activity. Starting from the seminal contribution given by Flory–Rehner equation back in 1943 for the determination of matrix structural properties, over more than 70 years, hydrogel modeling has not only taken advantage of new theories and the increasing computational power, but also of the methods offered by computational chemistry, which provide details at the fundamental molecular level. Simulation techniques such as molecular dynamics act as a “computational microscope” and allow for obtaining a new and deeper understanding of the specific interactions between the solute and the polymer, opening new exciting possibilities for an in silico network design at the molecular scale. Moreover, system modeling constitutes an essential step within the “safety by design” paradigm that is becoming one of the new regulatory standard requirements also in the field-controlled release devices. This review aims at providing a summary of the most frequently used modeling approaches (molecular dynamics, coarse-grained models, Brownian dynamics, dissipative particle dynamics, Monte Carlo simulations, and mass conservation equations), which are here classified according to the characteristic length scale. The outcomes and the opportunities of each approach are compared and discussed with selected examples from literature., Gels, 5 (2), ISSN:2310-2861

Different approaches to modeling the gas phase polymerization of ethylene that have been considered in the literature are reviewed. It is shown that while simple, well-mixed models can give an adequate representation of the average performance of a given polymerization reactor, they do not allow one to analyze certain modeling problems such as the existence of temperature gradients or particle segregation, nor can they be used to treat operational modes such as condensed cooling where there can be up to three different phases in different parts of the reactor. For this, more complex models are required. These can take the form of compartmentalized models or even models based on computation fluid dynamics. However, long computational times can be required to fully exploit these models. Furthermore, significant progress needs to be made if one needs to address important phenomena such as agglomeration or particle attrition during polymerization. ISSN:1862-832X ISSN:1862-8338

In the last decades bioresorbable and biodegradable polymers have gained a very good reputation both in research and in industry thanks to their unique characteristics. They are, indeed, able to ensure high performances and biocompatibility, at the same time avoiding post-healing surgical interventions for devices removal. In the medical device industrial use of such biopolymers, it is widely known that product formulation and manufacturing need to follow specific procedures in order to ensure both proper mechanical properties and desired degradation profile. Moreover, also the sterilization method is crucial and its impact on physical properties is generally underestimated. In this work we focused our attention on the effect of different terminal sterilization methods on two commercially available poly(L-lactide-co-ε-caprolactone) with equivalent chemical composition (70% PLA and 30% PCL) and relatively similar initial molecular weight, but different chains arrangement and crystallinity. Results obtained show that crystallinity plays a key role, helping in preserving the narrow distribution of chains and, as a consequence, defined physical properties. These statements can be used as guidelines for a better choice of the most adequate biodegradable polymers in the production of resorbable medical devices.

Although bone has a high potential to regenerate itself after damage and injury, the efficacious repair of large bone defects resulting from resection, trauma or non-union fractures still requires the implantation of bone grafts. Materials science, in conjunction with biotechnology, can satisfy these needs by developing artificial bones, synthetic substitutes and organ implants. In particular, recent advances in materials science have provided several innovations, underlying the increasing importance of biomaterials in this field. To address the increasing need for improved bone substitutes, tissue engineering seeks to create synthetic, three-dimensional scaffolds made from organic or inorganic materials, incorporating drugs and growth factors, to induce new bone tissue formation. This review emphasizes recent progress in materials science that allows reliable scaffolds to be synthesized for targeted drug delivery in bone regeneration, also with respect to past directions no longer considered promising. A general overview concerning modeling approaches suitable for the discussed systems is also provided., Pharmaceutics, 10 (3)

In this work we quantified the role of electrostatic interactions in the self-assembly of a model amphiphilic peptide (RADA 16-I) into fibrillar structures by a combination of size exclusion chromatography and molecular simulations. For the peptide under investigation, it is found that a net charge of +0.75 represents the ideal condition to promote the formation of regular amyloid fibrils. Lower net charges favor the formation of amorphous precipitates, while larger net charges destabilize the fibrillar aggregates and promote a reversible dissociation of monomers from the ends of the fibrils. By quantifying the dependence of the equilibrium constant of this reversible reaction on the pH value and the peptide net charge, we show that electrostatic interactions contribute largely to the free energy of fibril formation. The addition of both salt and a charged destabilizer (guanidinium hydrochloride) at moderate concentration (0.3-1 M) shifts the monomer-fibril equilibrium toward the fibrillar state. Whereas the first effect can be explained by charge screening of electrostatic repulsion only, the promotion of fibril formation in the presence of guanidinium hydrochloride is also attributed to modifications of the peptide conformation. The results of this work indicate that the global peptide net charge is a key property that correlates well with the fibril stability, although the peptide conformation and the surface charge distribution also contribute to the aggregation propensity.

The use of molecular markers for inflammation in the gastrointestinal tract could empower optical imaging modalities for early diagnosis and eventually personalized timely treatments. A major hurdle to the widespread use of functional fluorescence imaging is the absence of suitable contrast agents, in particular to be administered via the oral route due to the usual proteolytic susceptibility of the biomarkers. By designing a retro-inverso peptide, starting from a previously described sequence specific for N-cadherin, we achieved resistance to gastrointestinal degradation and even slightly improved specificity towards the target, both in ex vivo and in vivo experimental colitis. Simulations at fundamental molecular level suggested that the introduced retro-inverso modifications did not affect the folding of the peptide, leaving its ability to interact with the binding pocket of the monomeric N-cadherin unaltered, even when fluorescently labeled. Possible further derivatization of this sequence could be envisaged to further extend the potential of the designed retro-inverso peptide as diagnostic or theranostic agent for the oral route.

This chapter represents a brief introduction to the available approaches aimed at modeling the degradation of bioresorbable polymers. The mechanism behind degradation kinetics, which is due to hydrolysis, and the main factors affecting degradation rate are explained. Then, the computational methods offered by the literature to quantitatively describe the degradation of bioresorbable polymers are addressed.

Interfering with the activity of β-secretase to reduce the production of Aβ peptides is a conceivable therapeutic strategy for Alzheimer’s disease. However, the development of efficient yet safe inhibitors is hampered by secondary effects, usually linked to the indiscriminate inhibition of other substrates’ processing by the targeted enzyme. Based on the spatial compartmentalization of the cleavage of the amyloid precursor protein by β-secretase, we hypothesized that by exploiting the endocytosis receptor low-density lipoprotein receptor-related protein it would be possible to direct an otherwise cell-impermeable inhibitor to the endosomes of neurons, boosting the drug’s efficacy and importantly, sparing the off-target effects. We used the transport peptide Angiopep to build an endocytosis-competent conjugate and found that although the peptide facilitated the inhibitor’s internalization into neurons and delivered it to the endosomes, the delivery was not efficient enough to potently reduce β-secretase activity at the cellular level. This is likely connected to the finding that in the cell lines we used, Angiopep’s internalization was not mediated by its presumed receptor to a significant extent. Additionally, Angiopep exploited different internalization mechanisms when applied alone or when conjugated to the inhibitor, highlighting the impact that drug conjugation can have on transport peptides., Scientific Reports, 6, ISSN:2045-2322

The diffusion and aggregation of sodium fluorescein in aqueous solutions was investigated adopting density functional theory (DFT) and molecular dynamics (MD) simulations. First, DFT calculations in implicit water were used to determine minimum energy structure and atomic charges of the solute, which were then used as input for explicit water MD simulations. The self-diffusion coefficient of sodium fluorescein was calculated using the Einstein equation, computing the mean square displacement from 24 ns trajectories. The calculated diffusion coefficient, 0.42 · 10(-5) cm(2) s(-1), is in good agreement with literature experimental data. The simulations confirmed the tendency of fluorescein to form dimers. In order to achieve a deeper understanding of aggregation phenomena, the dimer geometry was investigated through DFT calculations both in vacuo and in implicit water using different functionals and solvation theories. The results showed that dimerization does not occur in vacuo, as charge repulsion dominates, and that the minimum energy dimer structure is symmetric and stabilized by edge-to-face π-π interactions. The interaction energy was computed both at the DFT level and through MD simulations using Umbrella Sampling. The free interaction energy calculated with the WHAM and Umbrella Integration protocol, -1.3 kcal/mol, is in good agreement with experimental data, while the value determined using DFT calculations is significantly smaller and depends largely from the chosen functional and the computational methodology used to determine the solute-solvent boundary surface.

Structural characterization of poly-l-lactic acid (P(L)LA) and poly(glycolic acid) (PGA) oligomers containing three units was carried out with an atomistic approach. Oligomer structures were first optimized through quantum chemical calculations, using density functional theory (DFT); rotational barriers concerning dihedral angles along the chain were then investigated. Diffusion coefficients of l-lactic acid and glycolic acid in pure water were estimated through molecular dynamic (MD) simulations. Monomer structures were obtained with quantum chemical computation in implicit water using DFT method; atomic charges were fitted with Restrained Electrostatic Potentials (RESP) formalism, starting from electrostatic potentials calculated with quantum chemistry. MD simulations were carried out in explicit water, in order to take into account solvent presence.

In this study hydrogels synthesized from agarose and carbomer 974P macromers were selected for their potential application in spinal cord injury (SCI) repair strategies following their ability to carry cells and drugs. Indeed, in drug delivery applications, one of the most important issues to be addressed concerns hydrogel ability to provide a finely controlled delivery of loaded drugs, together with a coherent degradation kinetic. Nevertheless, solute effects on drug delivery system are often neglected in the large body of literature, focusing only on the characterization of unloaded matrices. For this reason, in this work, hydrogels were loaded with a chromophoric salt able to mimic, in terms of steric hindrance, many steroids commonly used in SCI repair, and its effects were investigated both from a structural and a rheological point of view, considering the pH-sensitivity of the material. Additionally, degradation chemistry was assessed by means of infrared bond response (FT-IR) and mass loss.

Agar-Carbomer (branched poly (acrylic acid)) hydrogel, an injectable bio-resorbable scaffold with a controlled nanostructure specifically designed for neural cell housing, was developed together with a new protocol for building three dimensional biohybrid cell/hydrogel systems. In order to overcome classic structural analysis inconveniences due to the high water amount, which affects instruments results and reliability, agar-Carbomer hydrogels were synthesized by microwave-assisted block copolymerization together with La 3+ salts. Propylene glycol, glycerol and buffered saline solution were used as cross-linking agents and solvent, respectively. Biomaterial properties were not affected by the presence of lanthanum, and were checked via swelling and rheological analysis. Moreover, the presence of La 3+ within the polymeric network was characterized by thermogravimetric analysis, environmental scanning electron microscopy and Fourier transformed infrared spectroscopy. The results showed that the rare earth presented uniform distribution in the hydrogel network due to the formation of chemical bonds after polymerization without being modified its luminescence emission spectrum that allowed hydrogel detection. These results made the obtained host-guest system a useful tool for analytical research studies concerning regenerative medical applications that could also be potentially taken up with in vivo experiments.

In this work, ring-opening polymerization and reversible addition-fragmentation chain transfer polymerization (RAFT) have been employed for the production of block copolymers where the backbone is brushed with poly(ethylene glycol) (PEG) and polyester chains. Because of their amphiphilic properties, they are able to self-assemble in water, forming micelles. Molecular dynamics simulations have been accomplished to study the behavior of the copolymer single chain in water, and the self-assembly properties have been characterized and correlated to the copolymer structure in terms of critical micellar concentration and particle size. As a proof of their flexibility, these materials have been employed for the production of polymer–lipid hybrid nanoparticles with tunable dimensions (from 120 to 260 nm) adopted for the controlled release of anticancer compounds (paclitaxel and curcumin). © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 43084.

The present work is focused on the development and the validation of a mechanistic model describing the degradation of drug-loaded polylactic-co-glycolic acid microparticles and the drug release process from such devices. Microparticles' degradation is described through mass conservation equations; the application of population balances allows a detailed description of the hydrolysis kinetics, which also takes into account the autocatalytic behavior that characterizes bulk eroding polymers. Drug release considers both drug dissolution and the diffusion of dissolved active principle through the polymeric matrix. The diffusion of oligomers, water, and drug is assumed to follow Fickian behavior; the use of effective diffusion coefficients takes into account the diffusivity increase due to polymer hydrolysis. The model leads to a system of partial differential equations, solved by means of the method of lines. The model predictions satisfactorily match with different sets of literature data, indicating that the model presented here, despite its simplicity, is able to describe the key phenomena governing the device behavior.

In this work, a well-known single-particle model (the multigrain model) is applied to simulate size growth and morphology evolution of polyethylene particles obtained through a slurry phase, catalytic polymerization in semibatch reactor. The model explicitly accounts for diffusion limitations within the polymer particle and between the particle and the solvent, as well as void fraction variations due to the particle growth. Catalyst behavior is described assuming a two-site model, a good compromise between accuracy and simplicity, along with a conventional kinetic scheme, whose kinetic parameters are determined by fitting the model predictions to the experimental data. Polymer molecular weight is evaluated from population balances, solved through the method of moments. The semibatch reactor is modeled by means of fundamental mass conservation equations. Simulations show that the proposed model is able to describe not only the polymer properties of interest but also the evolution of the average particle size, thus providing a comprehensive overview of the system behavior. The model is further validated through regression-free simulation of additional sets of experimental data, including materials with a bimodal molar mass distribution: the good agreement also found in this case confirms the robustness of the model and the estimated parameter values.

Poly(methyl methacrylate) (PMMA) nanoparticles (NPs) were prepared by emulsion free radical polymerization. NPs with controlled dimension, as monitored by dynamic light scattering (DLS) and transmission electron microscopy (TEM), were produced by changing experimental parameters, such as the amount of emulsifier and the monomer feeding mode (batch or semi-batch). Then, different sized NPs (60, 80 and 130nm) were loaded in polysaccharide-polyacrylic acid based hydrogels, cross-linked by covalent ester bonds between polyacrylic acid (PAA) and agarose chains, with different pore sizes (30, 60, 90nm). The characteristics of the resulting composite hydrogel-NPs system were firstly studied in terms of rheological properties and ability to release Rhodamine B that presents steric hindrance similar to many neuroprotective agents used in spinal cord injury (SCI) repair. Then, diffusion-controlled release of different sized NPs from different entangled hydrogels was investigated in vitro and correlated with NPs diameter and hydrogel mean mesh size, showing different hindrances to the diffusion pathways. Release experiments and diffusion studies, rationalized by mathematical modeling and verified in vivo, allowed to build a material library able to satisfy different medical drug delivery needs.

In drug eluting stent technologies, an increased demand for better control, higher reliability, and enhanced performances of drug delivery systems emerged in the last years and thus offered the opportunity to introduce model-based approaches aimed to overcome the remarkable limits of trial-and-error methods. In this context a mathematical model was studied, based on detailed conservation equations and taking into account the main physical-chemical mechanisms involved in polymeric coating degradation, drug release, and restenosis inhibition. It allowed highlighting the interdependence between factors affecting each of these phenomena and, in particular, the influence of stent design parameters on drug antirestenotic efficacy. Therefore, the here-proposed model is aimed to simulate the diffusional release, for both in vitro and the in vivo conditions: results were verified against various literature data, confirming the reliability of the parameter estimation procedure. The hierarchical structure of this model also allows easily modifying the set of equations describing restenosis evolution to enhance model reliability and taking advantage of the deep understanding of physiological mechanisms governing the different stages of smooth muscle cell growth and proliferation. In addition, thanks to its simplicity and to the very low system requirements and central processing unit (CPU) time, our model allows obtaining immediate views of system behavior.