Grid structure impact in sparse point representation of derivatives

In the Sparse Point Representation (SPR) method the principle is to retain the function data indicated by significant interpolatory wavelet coefficients, which are defined as interpolation errors by means of an interpolating subdivision scheme. Typically, a SPR grid is coarse in smooth regions, and refined close to irregularities. Furthermore, the computation of partial derivatives of a function from the information of its SPR content is performed in two steps. The first one is a refinement procedure to extend the SPR by the inclusion of new interpolated point values in a security zone. Then, for points in the refined grid, such derivatives are approximated by uniform finite differences, using a step size proportional to each point local scale. If required neighboring stencils are not present in the grid, the corresponding missing point values are approximated from coarser scales using the interpolating subdivision scheme. Using the cubic interpolation subdivision scheme, we demonstrate that such adaptive finite differences can be formulated in terms of a collocation scheme based on the wavelet expansion associated to the SPR. For this purpose, we prove some results concerning the local behavior of such wavelet reconstruction operators, which stand for SPR grids having appropriate structures. This statement implies that the adaptive finite difference scheme and the one using the step size of the finest level produce the same result at SPR grid points. Consequently, in addition to the refinement strategy, our analysis indicates that some care must be taken concerning the grid structure, in order to keep the truncation error under a certain accuracy limit. Illustrating results are presented for 2D Maxwell's equation numerical solutions.

Computational analysis of quinoxalines N,N-Dioxide and ITS Derivates

A quinoxalina e seus derivativos são uma importante classe de compostos heterocíclicos, onde os elementos N, S e O substituem átomos de carbono no anel. A fórmula molecular da quinoxalina é C8H6N2, formada por dois anéis aromáticos, benzeno e pirazina. É rara em estado natural, mas a sua síntese é de fácil execução. Modificações na estrutura da quinoxalina proporcionam uma grande variedade de compostos e actividades, tais como actividades antimicrobiana, antiparasitária, antidiabética, antiproliferativa, anti-inflamatória, anticancerígena, antiglaucoma, antidepressiva apresentando antagonismo do receptor AMPA. Estes compostos também são importantes no campo industrial devido, por exemplo, ao seu poder na inibição da corrosão do metal. A química computacional, ramo natural da química teórica é um método bem desenvolvido, utilizado para representar estruturas moleculares, simulando o seu comportamento com as equações da física quântica e clássica. Existe no mercado uma grande variedade de ferramentas informaticas utilizadas na química computacional, que permitem o cálculo de energias, geometrias, frequências vibracionais, estados de transição, vias de reação, estados excitados e uma variedade de propriedades baseadas em várias funções de onda não correlacionadas e correlacionadas. Nesta medida, a sua aplicação ao estudo das quinoxalinas é importante para a determinação das suas características químicas, permitindo uma análise mais completa, em menos tempo, e com menos custos.

Computational design with flexible backbone sampling for protein remodeling and scaffolding of complex binding sites

Dissertation presented to obtain the Doutoramento (Ph.D.) degree in Biochemistry at the Instituto de Tecnologia Qu mica e Biol ogica da Universidade Nova de Lisboa

Structure-property relationships in polymer nanocomposites

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Development of high specific strength components, with internal cellular structure, for several applications

Dissertação de mestrado em Engenharia Mecânica

Structure-function relationships of the alpha1b-adrenergic receptor.

The alpha1b-adrenergic receptor (AR) is a member of the large superfamily of seven transmembrane domain (TMD) G protein-coupled receptors (GPCR). Combining site-directed mutagenesis of the alpha1b-AR with computational simulations of receptor dynamics, we have explored the conformational changes underlying the process of receptor activation, i.e. the transition between the inactive and active states. Our findings suggest that the structural constraint stabilizing the alpha1b-AR in the inactive form is a network of H-bonding interactions amongst conserved residues forming a polar pocket and R143 of the DRY sequence at the end of TMDIII. We have recently reported that point mutations of D142, of the DRY sequence and of A293 in the distal portion of the third intracellular loop resulted in ligand-independent (constitutive) activation of the alpha1b-AR. These constitutively activating mutations could induce perturbations resulting in the shift of R143 out of the polar pocket. The main role of R143 may be to mediate receptor activation by triggering the exposure of several basic amino acids of the intracellular loops towards the G protein. Our investigation has been extended also to the biochemical events involved in the desensitization process of alpha1b-AR. Our results indicate that immediately following agonist-induced activation, the alpha1b-AR can undergo rapid agonist-induced phosphorylation and desensitization. Different members of the G protein coupled receptor kinase family can play a role in agonist-induced regulation of the alpha1b-AR. In addition, constitutively active alpha1b-AR mutants display different phosphorylation and internalization features. The future goal is to further elucidate the molecular mechanism underlying the complex equilibrium between activation and inactivation of the alpha1b-AR and its regulation by pharmacological substances. These findings can help to elucidate the mechanism of action of various agents displaying properties of agonists or inverse agonists at the adrenergic system.

Brain structure in asymptomatic FMR1 premutation carriers at risk for fragile X-associated tremor/ataxia syndrome.

Fragile X-associated tremor/ataxia syndrome (FXTAS), a late-onset movement disorder affecting FMR1 premutation carriers, is associated with cerebral and cerebellar lesions. The aim of this study was to test whether computational anatomy can detect similar patterns in asymptomatic FMR1 premutation carriers (mean age 46.7 years) with qualitatively normal -appearing grey and white matter on brain MRI. We used a multimodal imaging protocol to characterize brain anatomy by automated assessment of gray matter volume and white matter properties. Structural changes in the hippocampus and in the cerebellar motor network with decreased gray matter volume in lobule VI and white matter alterations of the corresponding afferent projections through the middle cerebellar peduncles are demonstrated. Diffuse subcortical white matter changes in both hemispheres, without corresponding gray matter alterations, are only identified through age × group interactions. We interpret the hippocampal fimbria and cerebellar changes as early alterations with a possible neurodevelopmental origin. In contrast, progression of the diffuse cerebral hemispheric white matter changes suggests a neurodegenerative process, leading to late-onset lesions, which may mark the imminent onset of FXTAS.

Paraphrasing : scope and typology : a computational approach

This PhD project aims to study paraphrasing, initially understood as the different ways in which the same content is expressed linguistically. We will go into that concept in depth trying to define and delimit its scope more accurately. In that sense, we also aim to discover which kind of structures and phenomena it covers. Although there exist some paraphrasing typologies, the great majority of them only apply to English, and focus on lexical and syntactic transformations. Our intention is to go further into this subject and propose a paraphrasing typology for Spanish and Catalan combining lexical, syntactic, semantic and pragmatic knowledge. We apply a bottom-up methodology trying to collect evidence of this phenomenon from the data. For this purpose, we are initially using the Spanish Wikipedia as our corpus. The internal structure of this encyclopedia makes it a good resource for extracting paraphrasing examples for our investigation. This empirical approach will be complemented with the use of linguistic knowledge, and by comparing and contrasting our results to previously proposed paraphrasing typologies in order to enlarge the possible paraphrasing forms found in our corpus. The fact that the same content can be expressed in many different ways presents a major challenge for Natural Language Processing (NLP) applications. Thus, research on paraphrasing has recently been attracting increasing attention in the fields of NLP and Computational Linguistics. The results obtained in this investigation would be of great interest in many of these applications.

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2K(b) system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method.

Computational and Biological Evaluation of N-octadecyl-N'-propylsulfamide, a Selective PPARα Agonist Structurally Related to N-acylethanolamines.

To further understand the pharmacological properties of N-oleoylethanolamine (OEA), a naturally occurring lipid that activates peroxisome proliferator-activated receptor alpha (PPARα), we designed sulfamoyl analogs based on its structure. Among the compounds tested, N-octadecyl-N'-propylsulfamide (CC7) was selected for functional comparison with OEA. The performed studies include the following computational and biological approaches: 1) molecular docking analyses; 2) molecular biology studies with PPARα; 3) pharmacological studies on feeding behavior and visceral analgesia. For the docking studies, we compared OEA and CC7 data with crystallization data obtained with the reference PPARα agonist GW409544. OEA and CC7 interacted with the ligand-binding domain of PPARα in a similar manner to GW409544. Both compounds produced similar transcriptional activation by in vitro assays, including the GST pull-down assay and reporter gene analysis. In addition, CC7 and OEA induced the mRNA expression of CPT1a in HpeG2 cells through PPARα and the induction was avoided with PPARα-specific siRNA. In vivo studies in rats showed that OEA and CC7 had anorectic and antiobesity activity and induced both lipopenia and decreases in hepatic fat content. However, different effects were observed when measuring visceral pain; OEA produced visceral analgesia whereas CC7 showed no effects. These results suggest that OEA activity on the PPARα receptor (e.g., lipid metabolism and feeding behavior) may be dissociated from other actions at alternative targets (e.g., pain) because other non cannabimimetic ligands that interact with PPARα, such as CC7, do not reproduce the full spectrum of the pharmacological activity of OEA. These results provide new opportunities for the development of specific PPARα-activating drugs focused on sulfamide derivatives with a long alkyl chain for the treatment of metabolic dysfunction.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Computational anatomy for studying use-dependant brain plasticity.

In this article we provide a comprehensive literature review on the in vivo assessment of use-dependant brain structure changes in humans using magnetic resonance imaging (MRI) and computational anatomy. We highlight the recent findings in this field that allow the uncovering of the basic principles behind brain plasticity in light of the existing theoretical models at various scales of observation. Given the current lack of in-depth understanding of the neurobiological basis of brain structure changes we emphasize the necessity of a paradigm shift in the investigation and interpretation of use-dependent brain plasticity. Novel quantitative MRI acquisition techniques provide access to brain tissue microstructural properties (e.g., myelin, iron, and water content) in-vivo, thereby allowing unprecedented specific insights into the mechanisms underlying brain plasticity. These quantitative MRI techniques require novel methods for image processing and analysis of longitudinal data allowing for straightforward interpretation and causality inferences.

Brain structure in movement disorders: a neuroimaging perspective.

Purpose of review: An overview of recent advances in structural neuroimaging and their impact on movement disorders research is presented. Recent findings: Novel developments in computational neuroanatomy and improvements in magnetic resonance image quality have brought further insight into the pathophysiology of movement disorders. Sophisticated automated techniques allow for sensitive and reliable in-vivo differentiation of phenotype/genotype related traits and their interaction even at presymptomatic stages of disease. Summary: Voxel-based morphometry consistently demonstrates well defined patterns of brain structure changes in movement disorders. Advanced stages of idiopathic Parkinson's disease are characterized by grey matter volume decreases in basal ganglia. Depending on the presence of cognitive impairment, volume changes are reported in widespread cortical and limbic areas. Atypical Parkinsonian syndromes still pose a challenge for accurate morphometry-based classification, especially in early stages of disease progression. Essential tremor has been mainly associated with thalamic and cerebellar changes. Studies on preclinical Huntington's disease show progressive loss of tissue in the caudate and cortical thinning related to distinct motor and cognitive phenotypes. Basal ganglia volume in primary dystonia reveals an interaction between genotype and phenotype such that brain structure changes are modulated by the presence of symptoms under the influence of genetic factors. Tics in Tourette's syndrome correlate with brain structure changes in limbic, motor and associative fronto-striato-parietal circuits. Computational neuroanatomy provides useful tools for in-vivo assessment of brain structure in movement disorders, allowing for accurate classification in early clinical stages as well as for monitoring therapy effects and/or disease progression.

Mutational and computational analysis of the alpha(1b)-adrenergic receptor. Involvement of basic and hydrophobic residues in receptor activation and G protein coupling.

To investigate their role in receptor coupling to G(q), we mutated all basic amino acids and some conserved hydrophobic residues of the cytosolic surface of the alpha(1b)-adrenergic receptor (AR). The wild type and mutated receptors were expressed in COS-7 cells and characterized for their ligand binding properties and ability to increase inositol phosphate accumulation. The experimental results have been interpreted in the context of both an ab initio model of the alpha(1b)-AR and of a new homology model built on the recently solved crystal structure of rhodopsin. Among the twenty-three basic amino acids mutated only mutations of three, Arg(254) and Lys(258) in the third intracellular loop and Lys(291) at the cytosolic extension of helix 6, markedly impaired the receptor-mediated inositol phosphate production. Additionally, mutations of two conserved hydrophobic residues, Val(147) and Leu(151) in the second intracellular loop had significant effects on receptor function. The functional analysis of the receptor mutants in conjunction with the predictions of molecular modeling supports the hypothesis that Arg(254), Lys(258), as well as Leu(151) are directly involved in receptor-G protein interaction and/or receptor-mediated activation of the G protein. In contrast, the residues belonging to the cytosolic extensions of helices 3 and 6 play a predominant role in the activation process of the alpha(1b)-AR. These findings contribute to the delineation of the molecular determinants of the alpha(1b)-AR/G(q) interface.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.