Reentrant Phase Diagram of Network Fluids

We introduce a microscopic model for particles with dissimilar patches which displays an unconventional "pinched'' phase diagram, similar to the one predicted by Tlusty and Safran in the context of dipolar fluids [Science 290, 1328 (2000)]. The model-based on two types of patch interactions, which account, respectively, for chaining and branching of the self-assembled networks-is studied both numerically via Monte Carlo simulations and theoretically via first-order perturbation theory. The dense phase is rich in junctions, while the less-dense phase is rich in chain ends. The model provides a reference system for a deep understanding of the competition between condensation and self-assembly into equilibrium-polymer chains.

Branching points in the low-temperature dipolar hard sphere fluid

In this contribution, we investigate the low-temperature, low-density behaviour of dipolar hard-sphere (DHS) particles, i.e., hard spheres with dipoles embedded in their centre. We aim at describing the DHS fluid in terms of a network of chains and rings (the fundamental clusters) held together by branching points (defects) of different nature. We first introduce a systematic way of classifying inter-cluster connections according to their topology, and then employ this classification to analyse the geometric and thermodynamic properties of each class of defects, as extracted from state-of-the-art equilibrium Monte Carlo simulations. By computing the average density and energetic cost of each defect class, we find that the relevant contribution to inter-cluster interactions is indeed provided by (rare) three-way junctions and by four-way junctions arising from parallel or anti-parallel locally linear aggregates. All other (numerous) defects are either intra-cluster or associated to low cluster-cluster interaction energies, suggesting that these defects do not play a significant part in the thermodynamic description of the self-assembly processes of dipolar hard spheres. (C) 2013 AIP Publishing LLC.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Three-dimensial patchy lattice model: Ring formation and phase separation

We investigate the structural and thermodynamic properties of a model of particles with 2 patches of type A and 10 patches of type B. Particles are placed on the sites of a face centered cubic lattice with the patches oriented along the nearest neighbor directions. The competition between the self- assembly of chains, rings, and networks on the phase diagram is investigated by carrying out a systematic investigation of this class of models, using an extension ofWertheim's theory for associating fluids and Monte Carlo numerical simulations. We varied the ratio r epsilon(AB)/epsilon(AA) of the interaction between patches A and B, epsilon(AB), and between A patches, epsilon(AA) (epsilon(BB) is set to theta) as well as the relative position of the A patches, i.e., the angle. between the (lattice) directions of the A patches. We found that both r and theta (60 degrees, 90 degrees, or 120 degrees) have a profound effect on the phase diagram. In the empty fluid regime (r < 1/2) the phase diagram is reentrant with a closed miscibility loop. The region around the lower critical point exhibits unusual structural and thermodynamic behavior determined by the presence of relatively short rings. The agreement between the results of theory and simulation is excellent for theta = 120 degrees but deteriorates as. decreases, revealing the need for new theoretical approaches to describe the structure and thermodynamics of systems dominated by small rings. (C) 2014 AIP Publishing LLC.

Novel biosensing device for point-of-care applications with plastic antibodies grown on Au-Screen Printed Electrodes

A gold screen printed electrode (Au-SPE) was modified by merging Molecular Imprinting and Self-Assembly Monolayer techniques for fast screening cardiac biomarkers in point-of-care (POC). For this purpose, Myoglobin (Myo) was selected as target analyte and its plastic antibody imprinted over a glutaraldehyde (Glu)/cysteamine (Cys) layer on the gold-surface. The imprinting effect was produced by growing a reticulated polymer of acrylamide (AAM) and N,N′-methylenebisacrylamide (NNMBA) around the Myo template, covalently attached to the biosensing surface. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) studies were carried out in all chemical modification steps to confirm the surface changes in the Au-SPE. The analytical features of the resulting biosensor were studied by different electrochemical techniques, including EIS, square wave voltammetry (SWV) and potentiometry. The limits of detection ranged from 0.13 to 8 μg/mL. Only potentiometry assays showed limits of detection including the cut-off Myo levels. Quantitative information was also produced for Myo concentrations ≥0.2 μg/mL. The linear response of the biosensing device showed an anionic slope of ~70 mV per decade molar concentration up to 0.3 μg/mL. The interference of coexisting species was tested and good selectivity was observed. The biosensor was successfully applied to biological fluids.

Electrochemical supercapacitors of conductive polymers and their composites

Dissertação Para Obtenção Do Grau De Mestre Em Bioorgânica

Biomimetic mineralization: encapsulation in calcium carbonate shells

Calcium carbonate biomineralization is a self-assembly process that has been studied to be applied in the biomedical field to encapsulate biomolecules. Advantages of engineering mineral capsules include improved drug loading efficiencies and protection against external environment. However, common production methods result in heterogeneous capsules and subject biomolecules to heat and vibration which cause irreversible damage. To overcome these issues, a microfluidic device was designed, manufactured and tested in terms of selectivity for water and oil to produce a W/O/W emulsion. During the development of this work there was one critical challenge: the selective functionalization in closed microfluidic channels. Wet chemical oxidation of PDMS with 1M NaOH, confirmed by FTIR, followed by adsorption of polyelectrolytes - PDADMAC/PSS - confirmed by UV-Vis and AFM results, render the surface of PDMS hydrophilic. UV-Vis spectroscopy also confirmed that this modification did not affect PDMS optical properties, making possible to monitor fluids and droplets. More important, with this approach PDMS remains hydrophilic over time. However, due to equipment constrains selectivity in microchannels was not achieved. Therefore, emulsion studies took place with conventional methods. Several systems were tried, with promising results achieved with CaCO3 in-situ precipitation, without the use of polymers or magnesium. This mineral stabilizes oil droplets in water, but not in air due to incomplete capsule formation.

Development and application of NMR techniques to study water-in-CO2 microemulsions

Self-assembly is a phenomenon that occurs frequently throughout the universe. In this work, two self-assembling systems were studied: the formation of reverse micelles in isooctane and in supercritical CO2 (scCO2), and the formation of gels in organic solvents. The goal was the physicochemical study of these systems and the development of an NMR methodology to study them. In this work, AOT was used as a model molecule both to comprehensively study a widely researched system water/AOT/isooctane at different water concentrations and to assess its aggregation in supercritical carbon dioxide at different pressures. In order to do so an NMR methodology was devised, in which it was possible to accurately determine hydrodynamic radius of the micelle (in agreement with DLS measurements) using diffusion ordered spectroscopy (DOSY), the micellar stability and its dynamics. This was mostly assessed by 1H NMR relaxation studies, which allowed to determine correlation times and size of correlating water molecules, which are in agreement with the size of the shell that interacts with the micellar layer. The encapsulation of differently-sized carbohydrates was also studied and allowed to understand the dynamics and stability of the aggregates in such conditions. A W/CO2 microemulsion was prepared using AOT and water in scCO2, with ethanol as cosurfactant. The behaviour of the components of the system at different pressures was assessed and it is likely that above 130 bar reverse microemulsions were achieved. The homogeneity of the system was also determined by NMR. The formation of the gel network by two small molecular organogelators in toluene-d8 was studied by DOSY. A methodology using One-shot DOSY to perform the spectra was designed and applied with success. This yielded an understanding about the role of the solvent and gelator in the aggregation process, as an estimation of the time of gelation.

Synthesis and characterization of C3-symmetric 1,3,5 - Benzenetricarboxamide derived supramolecular systems

The aim of this work was to study the self-assembly process of C3-symmetric molecules. To accomplish this objective 1,3,5 – benzentricarboxamides (BTA) derivatives were obtained. Five C3-symmetric molecules were synthesized in moderate to good yields (39-72%) using azo-benzene, aniline, benzylamine, tryptophan and tyrosine. The aggregation behavior of the BTA derivatives was probed with 1H-NMR spectroscopy, 1H-1H 2D Nuclear Overhauser Effect Spectroscopy (NOESY) and Diffusion Ordered Spectroscopy (DOSY). These experiments allowed to study the influence of H-bonding groups, aromatic rings, unsaturated bonds and the overall geometry in the molecular self-assembly associated with the different structural patterns present on these molecules. The stacking and large molecule behavior where observed in BTA 1, aniline derivative, BTA 4, tyrosine derivative or BTA 5, tryptophan derivative, with several of those discussed functional groups such as unsaturated bonds and H-bonding groups. BTA 5 was used in a few preliminary interaction studies with glucose and ammonium chloride showing interaction with the ammonium ion.

Lithium-doped silk fibroin films for application in electrochromic devices

Silk fibroin (SF) is a commonly available natural biopolymer produced in specialized glands of arthropods, with a long history of use in textile production and also in health cares. The exceptional intrinsic properties of these fibers, such as self-assembly, machinability, biocompatibility, biodegradation or non-toxicity, offer a wide range of exciting opportunities [1]. It has long been recognized that silk can be a rich source of inspiration for designing new materials with tailored properties, enhanced performance and high added value for targeted applications, opening exciting new prospects in the domain of materials science and related technological fields, including bio-friendly integration, miniaturization and multifunctionalization. In recent years it has been demonstrated that fibroin is an excellent material for active components in optics and photonics devices. Progress in new technological fields such as optics, photonics and electronics are emerging [2,3]. The incorporation of polymer electrolytes as components of various devices (advanced batteries, smart windows, displays and supercapacitors) offers significant advantages with respect to traditional electrolytes, including enhanced reliability and improved safety. SF films are particularly attractive in this context. They have near-perfect transparency across the VIS range, surface flatness (together with outstanding mechanical robustness), ability to replicate patterned substrates and their thickness may be easily tailored from a few nanometers to hundreds of micrometers through spin-casting of a silk solution into subtract. Moreover, fibroin can be added to other biocomponents or salts in order to modify the biomaterial properties leading to optimized and total different functions. Preliminary tests performed with a prototype electrochromic device (ECD) incorporating SF films doped with lithium triflate and lithium tetrafluoroborate (LiTFSI and LiBF4, respectively) as electrolyte and WO3 as cathodic electrochromic layer, are extremely encouraging. Aiming to evaluate the performance of the ion conducting SF membranes doped with LiTFSI and LiBF4 (SF-Li), small ECDs with glass/ITO/WO3/SF-Li/CeO2-TiO2/ITO/glass configuration were assembled and characterized. The device exhibited, after 4500 cycles, the insertion of charge at -3.0 V reached –1.1 mC.cm-2 in 15 s. After 4500 cycles the window glass-staining, glass/ITO/WO3/Fibrin-Li salts electrolyte/CeO2-TiO2/ITO/glass configuration was reversible and featured a T  8 % at λ = 686 nm

Biomimetic supramolecular designs for the controlled release of growth factors in bone regeneration

The extracellular matrix (ECM) of tissues is an assembly of insoluble macromolecules that specifically interact with soluble bioactive molecules and regulate their distribution and availability to cells. Recapitulating this ability has been an important target in controlled growth factor delivery strategies for tissue regeneration and requires the design of multifunctional carriers. This review describes the integration of supramolecular interactions on the design of delivery strategies that encompass self-assembling and engineered affinity components to construct advanced biomimetic carriers for growth factor delivery. Several glycan- and peptide-based self-assemblies reported in the literature are highlighted and commented upon. These examples demonstrate how molecular design and chemistry are successfully employed to create versatile multifunctional molecules which self-assemble/disassemble in a precisely predicted manner, thus controlling compartmentalization, transport and delivery. Finally, we discuss whether recent advances in the design and preparation of supramolecular delivery systems have been sufficient to drive real translation towards a clinical impact. 

Protein-based nanodevices for therapeutic applications

Tese de Doutoramento em Biologia Molecular e Ambiental (área de especialização em Biologia Celular e Saúde).

Exploring silk based biomaterials functionalized with antimicrobial peptides to prevent surgical site infections

Surgical site infections (SSI) often occur after invasive surgery, which is as a serious health problem, making it important to develop new biomaterials to prevent infections. Spider silk is a natural biomaterial with excellent biocompatibility, low immunogenicity and controllable biodegradability. Through recombinant DNA technology, spider silk-based materials can be bioengineered and functionalized with antimicrobial (AM) peptides 1. The aim of this study is to develop new materials by combining spider silk chimeric proteins with AM properties and silk fibroin extracted from Bombyx mori cocoons to prevent microbial infection. Here, spider silk domains derived from the dragline sequence of the spider Nephila clavipes (6 mer and 15 mer) were fused with the AM peptides Hepcidin and Human Neutrophil peptide 1 (HNP1). The spider silk domain maintained its self-assembly features allowing the formation of beta-sheets to lock in structures without any chemical cross-linking. The AM properties of the developed chimeric proteins showed that 6 mer + HNP1 protein had a broad microbicidal activity against pathogens. The 6 mer + HNP-1 protein was then assembled with different percentages of silk fibroin into multifunctional films. In vitro cell studies with a human fibroblasts cell line (MRC5) showed nontoxic and cytocompatible behavior of the films. The positive cellular response, together with structural properties, suggests that this new fusion protein plus silk fibroin may be good candidates as multifunctional materials to prevent SSI.

Preparació i caracterització de materials mesoporosos en sistemes tensioactius

Estudi elaborat a partir d’una estada a la Universitat Nacional de Yokohama des de maig fins a mitjans de juny del 2006. S'ha estudiat el comportament fàssic i la preparació de sílica mesoporosa pels nous tensioactius fluorats d'estructura C8F17SO2(C3H7)N(C2H4O)nH (abreujat C8F17(EO)n. El tensioactiu C8F17(EO)n forma micel•les allargades i cristalls líquids en aigua, i per tant pot ser adequat per a la preparació de materials mesoporosos. Sílica mesoestructurada es va preparar pel mètode de precipitació per autoagregació cooperativa. Un estudi sistemàtic es va realitzar, investigant la influència de les concentracions de tensioactiu i precursor (TEOS), l’efecte del pH i de la longitud de cadena de poliòxid d’etilè. Els materials es van caracteritzar per raigs X a angle petit (SAXS), sorció de nitrògen i TEM. Els materials obtinguts presenten diàmetres de por petits i parets de por gruixudes. A més, aquests materials posseeixen altes superfícies específiques, que s’han obtingut emprant concentracions de tensioactiu petites, produint parets de por robustes sense microporositat significativa. La superfície específica es manté durant el procés de calcinació, malgrat un petit encongiment degut a l’entrecreuament de la sílica. Els materials de sílica obtinguts han mostrat ser significativament més robustos que altres materials similars descrits a la bibliografia, com la sílica MCM-41.

UniPathway: a resource for the exploration and annotation of metabolic pathways.

UniPathway (http://www.unipathway.org) is a fully manually curated resource for the representation and annotation of metabolic pathways. UniPathway provides explicit representations of enzyme-catalyzed and spontaneous chemical reactions, as well as a hierarchical representation of metabolic pathways. This hierarchy uses linear subpathways as the basic building block for the assembly of larger and more complex pathways, including species-specific pathway variants. All of the pathway data in UniPathway has been extensively cross-linked to existing pathway resources such as KEGG and MetaCyc, as well as sequence resources such as the UniProt KnowledgeBase (UniProtKB), for which UniPathway provides a controlled vocabulary for pathway annotation. We introduce here the basic concepts underlying the UniPathway resource, with the aim of allowing users to fully exploit the information provided by UniPathway.