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Supplementary Table, Materials and References from Activity of dasatinib against L576P KIT mutant melanoma: Molecular, cellular, and clinical correlates

Point mutations in the KIT receptor tyrosine kinase gene have recently been identified in mucosal, acral lentiginous, and chronically sun-damaged melanomas. We have identified the first human melanoma cell line with an endogenous L576P mutation, the most common KIT mutation in melanoma (∼30-40%). In vitro testing showed that the cell viability of the L576P mutant cell line was not reduced by imatinib, nilotinib, or sorafenib small molecule KIT inhibitors effective in nonmelanoma cells with other KIT mutations. However, the viability of the mutant cells was reduced by dasatinib at concentrations as low as 10 nM (P = 0.004). Molecular modeling studies found that the L576P mutation induces structural changes in KIT that reduce the affinity for imatinib (ΔΔGbind = −2.52 kcal/mol) but not for dasatinib (ΔΔGbind = +0.32 kcal/mol). Two metastatic melanoma patients with the L576P KIT mutation were treated with dasatinib, including one patient previously treated with imatinib. Both patients had marked reduction (>50%) and elimination of tumor F18-fluorodeoxyglucose (FDG)-avidity by positron emission tomography (PET) imaging after dasatinib treatment. These data support the selective inhibitory effect of dasatinib against cells harboring the most common KIT mutation in melanoma, and thus has therapeutic implications for acrallentiginous, chronic sun-damaged, and mucosal melanomas. [Mol Cancer Ther 2009;8(8):2079–85]

In this work, process simulation is used to calculate material and energy balances for several different hydrogen production processes. Process simulation outcomes are then used to estimate three key performance indicators: the energy return of energy invested, the levelized cost of hydrogen and the life cycle assessment. We compared several hydrogen generation processes, each denoted by a unique colour code: (i) green hydrogen, produced by electrolysis of water using electricity from renewable sources, (ii) grid hydrogen, produced by electrolysis using grid electricity, (iii) grey hydrogen, produced from natural gas using steam reforming and (iv) blue hydrogen, like grey one, but coupled with carbon capture and storage. In conclusion, the most sustainable hydrogen production method is the green hydrogen, produced by water electrolysis.

The breast cancer type 1 susceptibility protein (BRCA1) and its partner - the BRCA1-associated RING domain protein 1 (BARD1) - are key players in a plethora of fundamental biological functions including, among others, DNA repair, replication fork protection, cell cycle progression, telomere maintenance, chromatin remodeling, apoptosis and tumor suppression. However, mutations in their encoding genes transform them into dangerous threats, and substantially increase the risk of developing cancer and other malignancies during the lifetime of the affected individuals. Understanding how BRCA1 and BARD1 perform their biological activities therefore not only provides a powerful mean to prevent such fatal occurrences but can also pave the way to the development of new targeted therapeutics. Thus, through this review work we aim at presenting the major efforts focused on the functional characterization and structural insights of BRCA1 and BARD1, per se and in combination with all their principal mediators and regulators, and on the multifaceted roles these proteins play in the maintenance of human genome integrity.

Most of the actual industrial research efforts are aimed at reducing environmental burdens associated with human activities in the context of sustainable development. This trend has become increasingly prevalent in the naval transportation sector shown by a growing number of scientific publications dealing with life cycle as-sessments of maritime-related activities. However, the life cycle assessment framework provides practitioners with a variety of alternatives for conducting the analyses, giving room for defining key factors, such as functional units, system boundaries, and impact assessment methods, among others. This lack of standardization resulted in a wide range of assumptions and findings that are seldom comparable. The goal of this review is providing a systematic literature analysis, focusing on the characteristics of life cycle assessments dealing with the envi-ronmental impacts of various maritime vessel categories. In the first part, a qualitative analysis of the available scientific literature has been performed, providing a bibliometric analysis and a general overview of the char-acteristics of the studies (i.e., life cycle impact assessment methodologies, background data, and software tools used). The outcomes of the bibliometric analysis are then summarized and discussed to understand current practices and future trends in this field, providing the basis for the normalization phase of the results. The second section of the paper offers advice for naval practitioners on how to perform results normalization to produce comparable analyses. Two approaches for normalization have been proposed in the frame of this study: an "horizontal" one, which is based on vessel features and allows a comparison among different vessel typologies, and a "vertical" one that enables to fairly compare vessels of the same category to one another. In addition, each section reports the outcomes of greenhouse gas-related impact categories, which have been subjected to the proposed normalization procedure, along with the order of magnitude of the results for each life cycle phase. The overall work provides an overview of LCA impact results as well as a collection of procedures and recommen-dations for future life cycle assessments based on specific vessel types, in terms of functional unit selection, system boundary definition, impact assessment approach, presentation of the outcomes, and normalization basis.

In view of the low-carbon transformation of the power sector, natural gas-fired power generation is the only technology, among fossil resources, that will continue to provide an important source of flexibility for the power system in the coming years. However, the carbon dioxide emissions produced by the operation of such plants call for carbon capture and storage equipment, whose deployment needs to be assessed and compared with the main renewable technologies: wind power and photovoltaics. This work uses process simulation in order to assess two different carbon capture processes: a traditional one, based on monoethanolamine, and an innovative one, based on hot potassium carbonate. Process simulation is also used for the transportation of carbon dioxide to the sequestration site. Mass and energy balances from the simulations are then used for the calculation of the Energy Return on Energy Invested, the Levelized Cost of Energy and as inputs for the Life Cycle Assessments of both alternative designs. The life cycle analyses of the considered power technologies exhibited higher contributions due to fossil-based power plants towards climate-related impact categories, while renewable sources were revealed to be more burdensome for the exploitation of mineral resources. The calculated Energy Return on Energy Invested for gas-fired power plants with carbon capture and storage is between 5.2 and 12.4, comparable with the values of photovoltaics and wind power. On the other hand, their Levelized Cost of Energy is between 10.2 and 20.0 eurocent per kilowatt-hour, much higher than that of renewables. The conclusion is that, at present, the sustainability of gas-fired power stations equipped with carbon capture and storage should be carefully considered and not taken for granted.

siRNAs are emerging as promising therapeutic agents due to their ability to inhibit specific genes in many diseases. However, these tools require specific vehicles in order to be safely delivered to the targeted site. Among different siRNA delivery systems, self-assembled nanomicelles based on amphiphilic cationic dendrons (ACDs) have recently outperformed nanovectors based on covalent carriers. This chapter describes how isothermal titration calorimetry (ITC) can be exploited as one of the best techniques to investigate the self-assembly process of ACDs. Specifically, ITC can provide, as such or via specific analysis methods, a full thermodynamic characterization of these nanomicelles, including their critical micellar concentration, micelle aggregation number, degree of counterion binding, Gibbs free energy of micellization, and its enthalpic and entropic components.

This chapter reviews the different techniques for analyzing the chemical-physical properties, transfection efficiency, cytotoxicity, and stability of covalent cationic dendrimers (CCDs) and self-assembled cationic dendrons (ACDs) for siRNA delivery in the presence and absence of their nucleic cargos. On the basis of the reported examples, a standard essential set of techniques is described for each step of a siRNA/nanovector (NV) complex characterization process: (1) analysis of the basic chemical-physical properties of the NV per se; (2) characterization of the morphology, size, strength, and stability of the siRNA/NV ensemble; (3) characterization and quantification of the cellular uptake and release of the siRNA fragment; (4) in vitro and (5) in vivo experiments for the evaluation of the corresponding gene silencing activity; and (6) assessment of the intrinsic toxicity of the NV and the siRNA/NV complex.

siRNAs are emerging as promising therapeutic agents due to their ability to inhibit specific genes in many diseases. However, these tools require specific vehicles in order to be safely delivered to the targeted site. Among different siRNA delivery systems, self-assembled nanomicelles based on amphiphilic cationic dendrons (ACDs) have recently outperformed nanovectors based on covalent carriers. This chapter describes how isothermal titration calorimetry (ITC) can be exploited as one of the best techniques to investigate the self-assembly process of ACDs. Specifically, ITC can provide, as such or via specific analysis methods, a full thermodynamic characterization of these nanomicelles, including their critical micellar concentration, micelle aggregation number, degree of counterion binding, Gibbs free energy of micellization, and its enthalpic and entropic components.

Nowadays, computer simulations have been established as a fundamental tool in the design and development of new dendrimer-based nanocarriers for drug and gene delivery. Moreover, the level of detail contained in the information that can be gathered by performing atomistic-scale simulations cannot be obtained with any other available experimental technique. In this chapter we describe the main computational toolbox that can be exploited in the different stages of novel dendritic nanocarrier production-from the initial conception to the stage of biological intermolecular interactions.

A great deal of scientific and economic efforts is currently being focused on nanotechnology, providing ample opportunity for scientific advances and new products for virtually all fields of application. However, substantial hurdles still remain on the road from the conception of a nanomaterial to its everyday use or, in case of nanomedicine, to its adoption in the clinical practice. Some of these include, for instance, (1) the need to bridge existing interdisciplinary gaps in order to exploit all different fields of knowledge in the effective and efficient design, development and testing of new nanomaterials; (2) the necessity to define appropriate standardized methodologies and procedures along the entire nanomaterial production chain (i.e., from cradle to grave), thereby contributing actively in closing the persistent nanomaterial regulatory gap; and (3) the urgency to raise awareness about risks and benefits associated with nanotechnology and nanomaterials both to policy makers and the general public. This chapter will try to briefly review all these points, with a specific eye on nanomaterials for biomedical applications (aka nanomedicines).

The recent emergence of the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent for the coronavirus disease 2019 (COVID-19), is causing a global pandemic that poses enormous challenges to global public health and economies. SARS-CoV-2 host cell entry is mediated by the interaction of the viral transmembrane spike glycoprotein (S-protein) with the angiotensin-converting enzyme 2 gene (ACE2), an essential counter-regulatory carboxypeptidase of the renin-angiotensin hormone system that is a critical regulator of blood volume, systemic vascular resistance, and thus cardiovascular homeostasis. Accordingly, this work reports an atomistic-based, reliable in silico structural and energetic framework of the interactions between the receptor-binding domain of the SARS-CoV-2 S-protein and its host cellular receptor ACE2 that provides qualitative and quantitative insights into the main molecular determinants in virus/receptor recognition. In particular, residues D38, K31, E37, K353, and Y41 on ACE2 and Q498, T500, and R403 on the SARS-CoV-2 S-protein receptor-binding domain are determined as true hot spots, contributing to shaping and determining the stability of the relevant protein-protein interface. Overall, these results could be used to estimate the binding affinity of the viral protein to different allelic variants of ACE2 receptors discovered in COVID-19 patients and for the effective structure-based design and development of neutralizing antibodies, vaccines, and protein/protein inhibitors against this terrible new coronavirus.

Biology is dominated by polyanions (cell membranes, nucleic acids, and polysaccharides just to name a few), and achieving selective recognition between biological polyanions and synthetic systems currently constitutes a major challenge in many biomedical applications, nanovectors-assisted gene delivery being a prime example. This review work summarizes some of our recent efforts in this field; in particular, by using a combined experimental/computation approach, we investigated in detail some critical aspects in self-assembled nanomicelles and two major polyanions—DNA and heparin.

One of the major goals of computational materials science is the rapid and accurate prediction of properties of new materials. In order to design new materials and compositions for specific, high-performance applications, it is essential to rely on predictive tools for the estimation of the desired properties before material preparation, characterization and processing. In the future, new materials and systems will be characterized by progressively higher degrees of complexity, due to the strong relationship between nanotechnology, biotechnology, computer science and cognitive disciplines. However, computer power and simulation algorithms are also quickly evolving, opening new avenues for novel material and system design based on virtual (aka in silico) experiments. Notwithstanding the great advances achieved in the simulation of structural, thermal, mechanical and transport properties of materials at the macroscopic level, the accurate property prediction for complex nanostructured materials remains a critical issue in the material design strategy. This hurdle arises from the strong dependence of the material properties on the underlying nanostructure. Atomistic simulations based on molecular dynamics or Monte Carlo methods allow such structure–property relationships to be derived already for systems of noticeable size and time scales; yet, the study of highly complex systems (e.g., polymer nanocomposites and self-assembled nanomaterials) is still out of current reach at such a fine level of detail. Indeed, the fast advancement of high-performance computing has already expanded these time/scale windows, and the upcoming advent of hexascale and/or quantum-based computers will indeed further contribute to this expansion; yet, the investigation of many critical phenomena will remain inaccessible to atomistic-based simulations. To circumvent this limitation, multiscale simulation techniques have been developed to create a seamless bridge across different time/scale domains (from electronic to continuum methods), thereby providing reliable predictive tools to design engineers. Accordingly, in this review work we present a selection of case studies based on our own experience in multiscale molecular modeling of nanostructured, complex systems of industrial interest. The main goal of this objective is to show how multiscale in silico experiments in molecular systems design and engineering is at the same time theoretically sound and mature enough for its full exploitation.

Breast cancer (BC) is the second leading cause of mortality in females after lung malignant neoplasms. Dedicated, noninvasive diagnostic screening methods for early detection and surveillance (e.g., mammography/echography) have indeed increased the five-year relative survival rate of women with BC from 75% in the 1970s to 91% in the middle 2010s. Sadly, however, the same life expectation for BC patients diagnosed at late stages is still as low as 26%, the leading cause of related mortality being metastasis to lymph nodes, lung, liver, bone, and brain. Therefore, more efficacious BC treatments beyond the current standards of chemotherapy, radiation, and surgery - all of which may damage not only disease cells but also healthy tissuesdare heavily needed. Nanomedicine (NM) is a multidisciplinary arena aiming at the design, synthesis, characterization and application of materials and devices with nanoscale dimensions (1-100 nm). As a rapidly developing field, NM offers concrete opportunities in hu- man cancer theranostics since, contrarily to conventional drugs, nanobased platforms may be designed and tailored for, e.g., overcoming biological barriers, allowing for prolonged blood circulation time, simultaneously exploiting both active tumor targeting and enhanced permeability and retention (EPR) effects, efficient drug delivery, and reduced or eliminated side effects. Approximately 50 cancer NMs approved by the Food and Drug Administration (FDA) are available in the clinics [6,7] and, according to the National Institute of Health (NIH), 243 clinical trials involving NMs in cancer theranostics are currently ongoing. Of these NMs, this chapter will review those targeting BC, briefly discussing the advantages they offer and underlying the challenges this emerging trend in the medical field still must face in paving the road to fulfill the European Union “Beating cancer by 2030” promise.

The maintenance of genome integrity is essential for any organism survival and for the inheritance of traits to offspring. To the purpose, cells have developed a complex DNA repair system to defend the genetic information against both endogenous and exogenous sources of damage. Accordingly, multiple repair pathways can be aroused from the diverse forms of DNA lesions, which can be effective per se or via crosstalk with others to complete the whole DNA repair process. Deficiencies in DNA healing resulting in faulty repair and/or prolonged DNA damage can lead to genes mutations, chromosome rearrangements, genomic instability, and finally carcinogenesis and/or cancer progression. Although it might seem paradoxical, at the same time such defects in DNA repair pathways may have therapeutic implications for potential clinical practice. Here we provide an overview of the main DNA repair pathways, with special focus on the role played by homologous repair and the RAD51 recombinase protein in the cellular DNA damage response. We next discuss the recombinase structure and function per se and in combination with all its principal mediators and regulators. Finally, we conclude with an analysis of the manifold roles that RAD51 plays in carcinogenesis, cancer progression and anticancer drug resistance, and conclude this work with a survey of the most promising therapeutic strategies aimed at targeting RAD51 in experimental oncology.

Energy, water, and food shortages, along with irreversible environmental damage and climate changes, are bound to happen within a decade if the current course of action is maintained, preparing the "perfect storm" - a chain of interrelated events that could lead to major stress on the global system.Energy plays a central role in the complex balance between humankind and the planet: poor strategies for the energy system will lead to disaster; but immediate, radical action can still mitigate what will otherwise be an unprecedented crisis. Reduction of the carbon intensity at the level of primary energy demand is one of the most impactful strategies. Current actions toward this goal, however, including the Nationally Determined Contributions (i.e., the climate actions pledged by the countries that ratified the Paris Agreements), are far from being adequate, and a much stronger effort is required. In this perspective, we draw inspiration from a visionary scientist of the past century, who pioneered the idea of a society powered by solar energy, and show, by a critical presentation of energy and carbon emission data, how this vision is now coming true. We focus our attention in particular to photovoltaics and analyze the factors that make it one of the key energy sources for the short and for the long term: economical convenience, the opening of very large markets, and the push by key players of the energy system.

This work presents a multi-scale approach to reacting and expanding polyurethane (PU) foams modeling and simulation. The modeling strategy relies on two pillars: an atomistic model (molecular dynamics (MD)/Grand Canonical Monte Carlo (GCMC)) that provides liquid mixture density and reactant solubility and a continuum model (CFD) in which the expansion characteristics of the foam is modeled exploiting the results of the atomistic simulations. The resulting coupled model is validated for two different PU systems applied in four batches with chemical and physical blowing agents. The results demonstrate the efficacy and reliability of the developed model in the simulation of different PU foam properties such as apparent density and temperature evolutions.

The steel industry is currently a major water pollution source, releasing high quantities of chemicals. One of the pollutants is phenol, known for its toxicity even when it is present in low concentrations. Liquid-liquid extraction employing various aromatics and cycloalkanes (i.e., benzene, toluene, cyclohexane, ethylbenzene) and ketones (i.e., methyl isobutyl ketone, cyclohexanone and mesityl oxide) as solvents, is studied in the present paper. A comparison among the seven solvents is performed based on process modelling simulation tools and Life Cycle Assessment (LCA). The simulations of the seven cases under study are conducted at the same wastewater flowrate of 100 tons/h, with a phenol content of 0.2 wt.% and compared using various parameters (i.e., quantity of solvent, steam and power used, quantity of solvent present in the output phenol streams). The simulation results show that the lowest quantity of solvent is registered in the phenol removal which uses cyclohexanone as solvent (e.g., 34,212.40 kg/h), followed by the case which uses mesityl oxide for the liquid-liquid extraction (e.g., 34,759.80 kg/h) and by the case involving cyclohexanone (e.g., 37,490.60 kg/h). The lowest steam consumption is registered also in the case of cyclohexanone usage (e.g., 47.56 GJ/h) while the lowest power consumption corresponds to mesityl oxide usage (e.g., 11.20 MJ/h). The simulation results are then used to perform an environmental analysis, quantified in terms of environmental key performance indicators, embedding several solvents production methods as well as various fuels. Our life cycle assessment leads to the conclusions that the most environmentally friendly design is phenol removal using cyclohexanone as a solvent, whose provision comes from cyclohexane, which in turn is produced from benzene in conjunction with steam production from natural gas. For instance, the lowest global warming potential indicator score is about 342 kg CO2 equivalents per kg of phenol, while the same indicator for the worst solvent, i.e., toluene produced using reforming technology and steam being produced using hard coal as fuel, is almost double (e.g., 341.94 kg CO2 equivalents per kg of phenol vs. 575.30 CO2 equivalents per kg of phenol). Lower values for other impact indicators are also obtained in the phenol removal using cyclohexanone as a solvent with steam being generated form natural gas (e.g., acidification potential indicator is 0.42 kg SO2 equivalents per kg of phenol, eutrophication potential is 4.21 × 10−2 kg PO43- equivalents per kg phenol, ozone depletion potential is 1.13 × 10-9 kg R11 equivalents per kg phenol).

Human Respiratory Syncytial Virus (RSV) is the primary cause of bronchopneumonia in infants and children worldwide. Clinical studies have shown that early treatments of RSV patients with ribavirin improve prognosis, even if the use of this drug is limited due to myelosuppression and toxicity effects. Furthermore, effective vaccines to prevent RSV infection are currently unavailable. Thus, the development of highly effective and specific antiviral drugs for pre-exposure prophylaxis and/or treatment of RSV infections is a compelling need. In the quest of new RSV inhibitors, in this work we evaluated the antiviral activity of a series of variously substituted 5,6-dichloro-1-phenyl-1(2)H-benzo[d][1,2,3]triazole derivatives in cell-based assays. Several 1- and 2-phenyl-benzotriazoles resulted fairly potent (µM concentrations) inhibitors of RSV infection in plaque reduction assays, accompanied by low cytotoxicity in human highly dividing T lymphoid-derived cells and primary cell lines. Contextually, no inhibitory effects were observed against other RNA or DNA viruses assayed, suggesting specific activity against RSV. Further results revealed that the lead compound 10d was active during the early phase of the RSV infection cycle. To understand whether 10d interfered with virus attachment to target cells or virus-cell fusion events, inhibitory activity tests against the RSV mutant strain B1 cp-52 – expressing only the F envelope glycoprotein – and a plasmid-based reporter assay that quantifies the bioactivity of viral entry were also performed. The overall biological results, in conjunction with in silico modeling studies, supported the conclusion that the RSV fusion process could be the target of this new series of compounds.

The fast development of digitalization and computational science is opening new possibilities for a rapid design of new materials. Computational tools coupled with focused experiments can be successfully used for the design of new nanostructured materials in different sectors, particularly in the area of biomedical applications. This paper starts with a general introduction on the future of computational tools for the design of new materials and introduces the paradigm of multiscale molecular modeling. It then continues with the description of the multiscale (i.e., atomistic, mesoscale and finite element calculations) computational recipe for the prediction of novel materials and structures for biomedical applications. Finally, the comparison of in silico and experimental results on selected systems of interest in the area of life sciences is reported and discussed. The quality of the agreement obtained between virtual and real data for such complex systems indeed confirms the validity of computational tools for the design of nanostructured polymer systems for biomedical applications.

Since the sustainability related to materials and processes has become a relevant criterion within the products design procedures, a novel approach to materials choice has been adopted in order to minimize the impacts related to the products life cycle. The selection of innovative materials for specific applications has been adopted by numerous manufacturers belonging to different areas, including marine engine constructors sector which was formerly dominated by metallic alloys. Indeed, the introduction of nano-engineered thermoplastic polymers (NETPs) as the main constituent of marine engine non-structural components, provided an enhancement towards the reduction of cost and weights as well as simplified maintenance and inspection operations. However, the substitution of former material doesn’t come without any drawbacks, since an in-depth investigation on compelling alternatives is mandatory. In this regard, computer multiscale simulations established as a valuable support to identify the influence of several molecular structures on the parameters that most affect the performances required by specific product purposes. In this work, we present a case study for the material substitution of a four-stroke marine engine plastic cylinder head cover, commonly made of aluminium alloys. Accordingly, different NETPs have been computationally evaluated and ranked in order to find the best compromise between mechanical properties and material costs. To reach this goal, a multiscale molecular modelling approach has been adopted in which the results from the atomistic scale have been used as inputs for the simulation of the final product performed with Finite Elements Method (FEM). Finally, in order to have a complete scenario of the replacement of aluminium with the selected NETP, a detailed Life Cycle Assessment related to the different material products has been performed in order to identify the most sustainable product design using a cradle to grave life cycle perspective on openLCA v1.8.0. While performing Life Cycle Inventory, we were able to embed data provided by the actual suppliers and manufacturers, including geographical specific contributions, waste production, energy consumption and processing details. Well-established impact categories have been adopted for Life Cycle Impact Analysis in order to abide by the state-of-the-art of LCA practice. Finally, the main contributions to the whole product life cycle have been identified, highlighting the critical phases with the aim of applying the essential improvement for reducing the product-related impacts.

A number of new F-triazolequinolones (FTQs) and alkoxy-triazolequinolones (ATQs) were designed, synthesized and evaluated for their activity against Mycobacterium tuberculosis H37Rv. Five out of 21 compounds exhibited interesting minimum inhibitory concentration (MIC) values (6.6-57.9 microM), ATQs generally being more potent than FTQs. Two ATQs, 21a and 30a, were endowed with the best anti-Mtb potency (MIC = 6.9 and 6.6 microM, respectively), and were not cytotoxic in a Vero cell line. Tested for activity against M. tuberculosis DNA gyrase in a DNA supercoiling activity assay, 21a and 30a showed IC50 values (27-28 microM) comparable to that of ciprofloxacin (10.6 microM). 21a was next selected for screening against several Mtb strains obtained from clinical isolates, including multi-drug-resistant (MDR) variants. Importantly, this compound was effective in all cases, with very promising MIC values (4 microM) in the case of some isoniazid/rifampicin-resistant Mtb strains. Finally, computer-based simulations revealed that the binding mode of 21a in the Mtb gyrase cleavage core complexed with DNA and the relevant network of intermolecular interactions are utterly similar to those described for ciprofloxacin, yielding a molecular rationale for the comparable anti-mycobacterial and DNA gyrase inhibition activity of this quinolone.

No abstract avaialble for this Chapter.

This review work reports a collection of coupled experimental/computational results taken from our own experience in the field of self-assembled dendrimers for heparin binding. These studies present and discuss both the potentiality played by this hybrid methodology to the design, synthesis, and development of possible protamine replacers for heparin anticoagulant activity reversal in biomedical applications, and the obstacles this field has still to overcome before these molecules can be translated into nanomedicines available in clinical settings.

Acrylic acid, one of the most important monomers, has a wide range of uses e.g. in the paints adhesives, textile finishing, leather processing or super absorbents. The production process from propylene is well known and used at industrial scale in the USA, Europe, and Asia. The present paper focuses on the evaluation of the environmental impact of the acrylic acid production process from propylene. Steam is a major raw material in the process under study, consequently different paths to obtain steam are investigated. The process was simulated using commercial software (Aspen Plus, PROII). A productivity capacity of 50,000 tones/year of acrylic acid has been considered. The environmental assessment, evaluated using Life Cycle Analysis method, depends on the material and energy balances generated by simulations. The present work uses a cradle-to-grave approach. The functional unit, to which all the environmental results for the cases under study are reported, is one tone of acrylic acid produced. The boundaries of the system cover: i) acrylic acid production; ii) upstream processes for example catalyst and molten salt production; steam production using various fuels (e.g. natural gas, anthracite, lignite, heavy fuel oil, light fuel oil and biomass) and iii) downstream processes for example: acrylic acid and acetic acid transport to other chemical plants for further processing. The CML (An LCA method developed by the Center of Environmental Science of Leiden University) 2001 impact assessment method was used for comparison between different case studies. The best value for Global Warming Potential (GWP) e.g. 1094.5 kg CO2-Equiv./tone is obtained when biomass is used to generate the steam required by the process. For other indicators such as Acidification Potential (AP), Photochemical Oxidation Potential (PCOP) and Eutrophication Potential (EP), the best value is obtained when steam is generated from natural gas. A sensitivity analysis of the environmental impact categories using the different combination of natural gas and biomass was also investigated. The study investigates also the association of the post-combustion amine-based carbon capture technologies with the conventional acrylic acid production process. Such association decreases the value of some environmental impact categories (e.g. GWP) while other impact categories are increasing e.g. AP, Human Toxicity Potential (HTP), Terrestrial Ecotoxicity Potential (TETP).

Low-generation viologen-phosphorous dendrimers (VPDs) can be exploited as novel therapeutic agents, since they efficiently inhibit aggregation of amyloid-β into fibrils and are active against several strains of microorganisms. Human serum albumin (HSA), the most abundant plasma protein, is playing an increasing role as drug carrier in the clinical setting. Therefore, with the aim of exploiting HSA as a potential carrier for VPDs, in this work we performed a preliminary investigation of the interaction of six different VPDs 1–6 with HSA using a combined computational/experimental approach. First, different modeling techniques were employed to i) determine the dendrimer binding site on the HSA surface; ii) derive the free energy change ΔGb involved in each dendrimer/HSA complex formation; iii) analyze in details all molecular determinants contributing to ΔGb, and iv) evaluate the eventual HSA structural variations induced by dendrimer binding. All modeling predictions were next validated using a series of experimental techniques, including isothermal titration calorimetry (ITC), circular dichroism (CD), and fluorescence quenching and decay. In aggregate, the results from this study allowed us to rank the affinity of the different viologen-phosphorous dendrimers 1–6 towards HSA and to formulate a molecular-based rationale for the differential binding thermodynamics of the resulting dendrimer/HSA complexes. According to our data, HSA can successfully and selectively bind VPDs 1–6, dendrimer 4 being the best cargo for this endogenous protein nanocarrier.

Stereoisomeric 2,5-diazabicyclo[2.2.2]octanes 14 and 15 were prepared in a chiral-pool synthesis starting from (S)- or (R)-aspartate. The key step in the synthesis was a Dieckmann-analogous cyclization of (dioxopiperazinyl)acetates 8, which involved trapping of the intermediate hemiketal anion with Me3SiCl. The σ1 affinity was tested using membrane preparations from animal (guinea pig) and human origin. The binding of bicyclic compounds was analyzed by molecular dynamics simulations based on a 3D homology model of the σ1 receptor. The good correlation between Ki values observed in the σ1 assays and calculated free binding energy, coupled with the identification of four crucial ligand/receptor interactions, allowed the formulation of structure-affinity relationships. In an in vitro antitumor assay with seven human tumor cell lines, the bicyclic compounds inhibited selectively the growth of the cell line A427, which is due to induction of apoptosis. In this assay, the compounds behave like the known σ1 receptor antagonist haloperidol.

We present a combined theoretical/experimental study to investigate the effect of selective solvent vapor annealing treatment on the obtainment of highly ordered morphologies of symmetric poly(styrene-b-methyl methacrylate) diblock copolymer (PS-b-PMMA DBC) films loaded with compatibilized magnetic (Fe3O4) nanoparticles (NPs). Different amounts of NPs were considered (1, 2, and 5 wt %) to study the effect of the inorganic content on the final properties of Fe3O4/PS-b-PMMA films. A precise control of the DBC nanostructure could be obtained by very simple and cost-effective fabrication steps, compatible with current industrial processes. Moreover, the modified NPs could be selectively placed into the PMMA domains of the DBC up to NP concentration of 5 wt % while preserving the corresponding DBC lamellar morphology.

Heparin is a sulfated glycan widely used as anticoagulant in medicine. Mallard Blue (MalB), a small cationic dye developed in our laboratories, is able to detect heparin in serum and plasma in a dose-response manner, with performance superior to its direct competitors. However, many aspects of MalB/heparin binding still remain to be explored which, once solved, may foster the clinical use of MalB. Among these, the characterization of the energetics that drives the MalB/heparin binding process, the competition for MalB binding by other polyanions (e.g., negatively-charged surfactant micelles), and the interaction of MalB with serum proteins are of particular interest. This work fills this gap by means of a combination of experimental investigations (UV-visible spectroscopy and isothermal titration calorimetry), and computational approaches based on molecular dynamics (MD) simulation techniques. In combination, the results obtained show that MalB efficiently binds to both heparin and SDS, with the binding being enthalpic in nature; yet, SDS is able to extract MalB from its complex with heparin when the surfactant is in its self-assembled form, the driving force underlying SDS-induced MalB/heparin de-complexation being entropic in nature as the two enthalpies of binding effectively cancel each other out. Once bound to SDS, the dye remains electrostatically bound to the micellar surface and does not penetrate the micelle palisade layer, as verified by steered molecular dynamics/umbrella sampling simulations. Finally, the affinity of MalB for human serum albumin (HSA), the most abundant plasma protein, is found to be lower than that for heparin, confirming the ability of the dye to work in complex physiological environments.

International audience; [This corrects the article DOI: 10.18632/oncotarget.20469.].

The need for effective and efficient design and production of sophisticated materials with advanced performances on a competitive time scale is strongly driving the integration of material modeling and simulation techniques into material selection decision processes. Specifically, for complex structural materials such as polymer-based nanocomposites (PNCs), there is a strong industrial demand for chemistry/physics-based models and modeling workflows able to predict relevant material properties in an accurate and reliable way. Under this perspective, in this work we describe the application of multiscale molecular modeling techniques for the choice of PNC materials for aerospace applications. The results are obtained in the framework of the European project Multi-scale Composite Material Selection Platform with a Seamless Integration of Materials Models and Multidisciplinary Design Framework (COMPOSELECTOR), funded by the European Commission within the H2020 call Advancing the integration of materials modeling in business processes to enhance effective industrial decision making and increase competitiveness.

Bovine viral diarrhea virus (BVDV) infection is still a plague that causes important livestock pandemics. Despite the availability of vaccines against BVDV, and the implementation of massive eradication or control programs, this virus still constitutes a serious agronomic burden. Therefore, the alternative approach to combat Pestivirus infections, based on the development of antiviral agents that specifically inhibit the replication of these viruses, is of preeminent actuality and importance. Capitalizing from a long-standing experience in antiviral drug design and development, in this work we present and characterize a series of small molecules based on the 9-aminoacridine scaffold that exhibit potent anti-BVDV activity coupled with low cytotoxicity. The relevant viral protein target – the RNA-dependent RNA polymerase – the binding mode, and the mechanism of action of these new antivirals have been determined by a combination of in vitro (i.e., enzymatic inhibition, isothermal titration calorimetry and site-directed mutagenesis assays) and computational experiments. The overall results obtained confirm that these acridine-based derivatives are promising compounds in the treatment of BVDV infections and, based on the reported structure-activity relationship, can be selected as a starting point for the design of a new generation of improved, safe and selective anti-BVDV agents.

We propose a framework for the preliminary screening of chemical process designs according to sustainability criteria. Through the implementation of each flowsheet in a process simulator, several indicators based on sustainability pillars, i.e. economy, society, and environment, are calculated and then analyzed employing data envelopment analysis (DEA) in order to select the most efficient designs considering multiple criteria simultaneously. Suboptimal alternatives are further investigated by adopting a retrofit analysis, aiming to identify the parameters that most contribute to the final indicators scores, and therefore highlighting the major sources of deviation from optimal conditions. We applied this framework on a case study based on various patents regarding the production of pioglitazone hydrochloride in order to validate the capabilities of our methodology. Our approach, which embeds process simulation, sustainability indicators, and DEA within the same procedure, will support practitioners during the sustainability assessment of promising process designs, removing the inefficient ones

The fast development of digitalisation and computational sciences is opening new possibilities for the rapid design of new materials. Computational tools coupled with focused experiments can be successfully used for the design of new nanostructured materials in different sectors, including membrane engineering. Accordingly, in this chapter, we present the application of a multiscale molecular simulation protocol for predicting gas transport properties in polymeric nanocomposite membranes constituted by titania (TiO2) nanoparticles dispersed in thermoplastic polyurethanes (TPUs). The chapter starts with a general introduction on the future of computational tools for the design of new materials and introduces the underlying paradigm of multiscale molecular modelling. It then continues with the description of a multiscale (i.e., atomistic, mesoscale, and finite element calculations) computational recipe developed ad hoc for the prediction of gas permeation and diffusion in TPU/TiO2 nanocomposite membranes. Finally, a comparison of the in silico and experimental results on these systems is reported and discussed. The quality of the agreement obtained between virtual and real data for such complex systems indeed confirms the validity of such computational tools for the design and transport property prediction of nanocomposite membranes for gas treatment.

This chapter presents the three-dimensional (3D) model of the Sigma1 receptor protein as obtained from homology modeling techniques. We show the applicability of this structure to docking-based virtual screening and discuss combined in silico/in vitro mutagenesis studies performed to validate the structural features of the Sigma1 receptor model and to qualify/quantify the prominent role of specific amino acid residues in ligand binding. The validation of the virtual 3D Sigma1 receptor model and its reliable applicability to docking-based virtual screening is of significance for rational ligand design, even in light of the recently reported crystal structure for the Sigma1 receptor.

Enteroviruses are among the most common and important human pathogens for which there are no specific antiviral agents approved by the US Food and Drug Administration so far. Particularly, coxsackievirus infections have a worldwide distribution and can cause many important diseases. We here report the synthesis of new 14 quinoxaline derivatives and the evaluation of their cytotoxicity and antiviral activity against representatives of ssRNA, dsRNA and dsDNA viruses. Promisingly, three compounds showed a very potent and selective antiviral activity against coxsackievirus B5, with EC50 in the sub-micromolar range (0.3 - 0.06 μM). A combination of experimental techniques (i.e. virucidal activity, time of drug addition and adsorption assays) and in silico modeling studies were further performed, aiming to understand the mode of action of the most active, selective and not cytotoxic compound, the ethyl 4-[(2,3-dimethoxyquinoxalin-6-yl)methylthio]benzoate (6).

Spirocyclic thiophene derivatives represent promising σ