Os sistemas biológicos macromoleculares são conhecidos por serem sistemas interagentes. Essas interações são fundamentais para processos como comunicação celular, especificidade de reações enzimáticas e regulação da expressão gênica. Os métodos disponíveis atualmente para estimar a afinidade das interações biomoleculares podem ser divididos, basicamente, em dois grupos: métodos rápidos que estimam a energia livre de ligação através de aproximações de campo de força (por exemplo, docking); e os métodos que são baseados em ensembles de Dinâmica Molecular (DM) para calcular as energias livres de ligação de maneira mais rigorosa, porém, com custo computacional mais elevado. O objetivo deste trabalho é aprimorar e validar um método menos custoso para o cálculo da energia livre de ligação. Para isso, simulações atomísticas de Monte Carlo (MC) dos ligantes no sítio de ligação são usadas para gerar ensembles termodinâmicos. Depois disso, as energias livres de ligação são calculadas usando uma combinação de energias e entropias estimadas através de uma estratégia de aproximação de primeira ordem. Dois algoritmos de amostragem foram avaliados no cálculo de energia de ligação. O primeiro algoritmo amostra graus de liberdade de translação e rotação randômicas do centro de massa do ligante no sítio de ligação, além de variações randômicas nos ângulos de torção envolvendo átomos pesados (não hidrogênio). O segundo amostra graus de liberdade rotacional e translacional do centro de massa, além de deslocamentos atômicos individuais para cada átomo do ligante. Além disso, diferentes modelos para calcular as contribuições polares para interação intermolecular foram utilizados. Comparações entre as energias livres de ligação calculadas com baixo custo computacional e as experimentais disponíveis na literatura para o sistema modelo utilizado, lisozima do vírus T4, mostraram uma correlação considerável (r=0,64 para N=27). Esses dados também apresentaram resultados interessantes quando comparados com outras metodologias, tais como LIE, MM-PBSA e MM-GBSA. Assim, a abordagem utilizada para a determinação das energias de interação mostrou-se eficiente em termos de tempo computacional e para comparação com dados de energia livre de ligação determinados experimentalmente. / Macromolecular biological systems are widely known by its interaction properties. Those interactions play fundamental roles in processes such as cellular communication, specificity of enzymatic reactions and regulation of gene expression. The methods currently available to estimate the affinity of biomolecular interactions can be divided basically into two groups: fast methods that estimate the free energy of binding through force field approximations (e.g., docking); and methods that are based on Molecular Dynamics (DM) ensembles to calculate binding free energies more rigorously, however, with higher computational cost. The objective of this work is to improve and validate a less costly method for calculating binding free energy. For this, atomistic Monte Carlo (MC) simulations of ligands at the binding site are used to generate thermodynamic ensembles. Thereafter, the binding free energies are calculated using a combination of energies and entropy estimated through a first-order approximation strategy. Two sampling algorithms were evaluated in the calculation of the binding energy. The first one samples the degrees of freedom from translation and rotation of the center of mass of the binder at the binding site, as well as random variations in the torsion angles involving heavy atoms (non-hydrogen). The second one samples the rotational and translational degrees of freedom of the ligand center of mass, as well as individual atomic displacements for each atom of the ligand. In addition, different models to calculate the polar contributions for intermolecular interaction were used. Comparisons between the binding free energies calculated with low computational cost and the experimental ones available in the literature for the system used, T4 virus lysozyme, resulted in acceptable correlation values (r=0.64 for N=27). Those data also showed interesting results compared to different methodologies such as LIE, MM-PBSA and MM-GBSA. Therefore, the used approach for determining the binding energies was efficient in terms of computational time and for comparison with free energy data determined experimentally.

As xantonas compreendem uma importante classe de heterocíclicos moleculares que possuem um esqueleto dibenzo-gama-pironas, podendo estes serem obtidos tanto por meios sintéticos quanto naturais. Estes constituintes têm sido freqüentemente isolados de plantas medicinais brasileiras e vêm recebendo atenção devido a seus aspectos fitoquímicos e suas propriedades biológicas. No entanto, poucos estudos são dedicados à abordagem estrutural mais aprofundada desses compostos no estado sólido, principalmente com relação a estudos cristalográficos. Uma justificativa para a escassez de trabalhos dessa natureza pode estar relacionada com a dificuldade de obtenção de cristais de qualidade. Com isso, a primeira etapa deste trabalho dedicou-se à obtenção de monocristais dos derivados xantônicos e, posteriormente, realizaram-se as medidas de difração de raios X por monocristal. Após a coleta de dados de difração de raios X, as estruturas cristalinas foram resolvidas e refinadas. Neste trabalho estudaram-se doze estruturas cristalinas de derivados xantônicos oxigenados, sendo que, uma das xantonas tetra-oxigenadas apresentou dois polimorfos. Portanto, onze constituintes quimicamente diferentes estão envolvidos (I-XI). Ressalta-se que das doze estruturas determinadas por difração de raios X apenas uma, III, trata-se de uma redeterminação, as demais foram estudadas pela primeira vez. Através da estrutura refinada estudou-se as geometrias moleculares de cada composto. Em relação aos aspectos intramoleculares, destacam-se as conformações dos anéis e substituintes, além dos efeitos causados pelos mesmos. Assim, observou-se que existe a tendência do sistema de anéis xantônicos apresentar uma conformação planar, e isso foi confirmado por cálculos de otimização de geometria. Na conformação molecular das xantonas 1-hidroxiladas, o efeito de ligação de hidrogênio assistida por ressonância (LHAR) foi exaustivamente estudado. As interações intermoleculares mostraram que a grande maioria das estruturas cristalinas são estabilizadas por ligações de hidrogênio fortes (OH...O) e fracas (CH...O). Além disso, as informações cristalográficas mostraram a existência de interações pi-pi, um importante contato hidrofóbico que contribui para manter o arranjo supramolecular. / Xanthones are a group of heterocyclic molecules having a dibenzo-gama-pyrone skeleton, and can be obtained as a synthetic or natural product. These compounds have often been afforded from Brazilian medicinal plants and have received special attention due to their phytochemical and biological properties. However, this compound class was seldom studied in the solid state, mainly with regard to the crystal structure. The lack of crystallographic studies can be explained due to the difficulties found in the production of single crystals. So, the goal of the first stage of this project was to obtain well shaped single crystals of the xanthones derivatives and then to perform X-ray diffraction measurements. After the data collection, the crystal structures were solved and refined. Here, twelve crystal structures of oxygenated xanthones derivatives were studied, in which one tetra-oxygenated xanthone presented two crystal forms. Hence, there are eleven chemically different constituents (I-XI) involved in the context of the xanthones. It is worth to emphasize that only the structure named III was a redetermination, being the others ones studied by X-ray diffraction for the first time. The molecular geometric parameters of each compound were provided by the refined structure. Despite the intramolecular aspects, the conformations of the rings and the substituents were highlighted, besides the effects caused by them. Usually, in the xanthone rings the preferred conformation is the planar, which was confirmed by theoretical calculations. The effect of the resonance assisted hydrogen bond (RAHB) on the molecular conformation was widely studied in the 1-hydroxylated xanthones derivatives. Finally, the intermolecular interactions and their meaning to the crystal structures stabilization were discussed, revealing that in almost all xanthones, the crystal packing are kept by strong (OH...O) and weak (CH...O) hydrogen bonds. In addition, the crystallographic analysis also pointed out to the presence of interactions pi-pi, an important hydrophobic contact for supramolecular assembly.

Noncovalent interactions play a vital role throughout much of chemistry. The understanding and characterization of these interactions is an area where theoretical chemistry can provide unique insight. While many methods have been developed to study noncovalent interactions, symmetry-adapted perturbation theory (SAPT) stands out as one of the most robust. In addition to providing energetic information about an interaction, it provides insight into the underlying physics of the interaction by decomposing the energy into electrostatics, exchange, induction and dispersion. Therefore, SAPT is capable of not only answering questions about how strongly a complex is bound, but also why it is bound. This proves to be an invaluable tool for the understanding of noncovalent interactions in complex systems. The wavefunction-based formulation of SAPT can provide qualitative results for large systems as well as quantitative results for smaller systems. In order to extend the applicability of this method, approximations to the two-electron integrals must be introduced. At low-order, the introduction of density fitting approximations allows SAPT computations to be performed on systems with up to 220 atoms and 2850 basis functions. Higher-orders of SAPT, which boasts accuracy rivaling the best theoretical methods, can be applied to systems with over 40 atoms. Higher-order SAPT also benefits from approximations that attempt to truncate unneccesary unoccupied orbitals.

Fibroblast growth factors (FGFs) lack signal sequences, and are exported through endoplasmic reticulum (ER)-Golgi-independent non-classical routes. FGFs work as modulators of various cellular activities like mitosis, differentiation, survival etc. Among the FGF family, which comprises of 23 different heparin proteins, human FGF-1 (hFGF-1), a potent angiogenic factors are one of the targets in cancer inhibition, as they are involved in blood vessel formation in tissues. There has been intensive research directed at the development of drugs that could effectively inhibit angiogenesis. In this context, the purpose of this study is to fully understand the molecular principles essential to determine probability of inhibition of hFGF-1 signaling transduction by imatinib. Imatinib, a 2-phenyl amino pyrimidine derivative is a tyrosine kinase inhibitor with antineoplastic activity. Imatinib binds to the intracellular pocket located within tyrosine kinases and inhibit the downstream cell proliferation events, but the exact molecular mechanism is still elusive. In this study, expression of hFGF-1 in recombinant E. coli was carried out, and the expressed protein was purified using heparin affinity column chromatography. The structural interactions governing imatinib-hFGF-1 interaction was studied by monitoring its stability, conformation and binding affinity by equilibrium unfolding using steady state fluorescence and proteolytic digestion assay. These data show that imatinib binds to hFGF-1 and enhances its thermal stability and solvent accessibility. In addition, biacore analysis was carried out to determine the binding affinity of imatinib to hFGF-1.

As xantonas compreendem uma importante classe de heterocíclicos moleculares que possuem um esqueleto dibenzo-gama-pironas, podendo estes serem obtidos tanto por meios sintéticos quanto naturais. Estes constituintes têm sido freqüentemente isolados de plantas medicinais brasileiras e vêm recebendo atenção devido a seus aspectos fitoquímicos e suas propriedades biológicas. No entanto, poucos estudos são dedicados à abordagem estrutural mais aprofundada desses compostos no estado sólido, principalmente com relação a estudos cristalográficos. Uma justificativa para a escassez de trabalhos dessa natureza pode estar relacionada com a dificuldade de obtenção de cristais de qualidade. Com isso, a primeira etapa deste trabalho dedicou-se à obtenção de monocristais dos derivados xantônicos e, posteriormente, realizaram-se as medidas de difração de raios X por monocristal. Após a coleta de dados de difração de raios X, as estruturas cristalinas foram resolvidas e refinadas. Neste trabalho estudaram-se doze estruturas cristalinas de derivados xantônicos oxigenados, sendo que, uma das xantonas tetra-oxigenadas apresentou dois polimorfos. Portanto, onze constituintes quimicamente diferentes estão envolvidos (I-XI). Ressalta-se que das doze estruturas determinadas por difração de raios X apenas uma, III, trata-se de uma redeterminação, as demais foram estudadas pela primeira vez. Através da estrutura refinada estudou-se as geometrias moleculares de cada composto. Em relação aos aspectos intramoleculares, destacam-se as conformações dos anéis e substituintes, além dos efeitos causados pelos mesmos. Assim, observou-se que existe a tendência do sistema de anéis xantônicos apresentar uma conformação planar, e isso foi confirmado por cálculos de otimização de geometria. Na conformação molecular das xantonas 1-hidroxiladas, o efeito de ligação de hidrogênio assistida por ressonância (LHAR) foi exaustivamente estudado. As interações intermoleculares mostraram que a grande maioria das estruturas cristalinas são estabilizadas por ligações de hidrogênio fortes (OH...O) e fracas (CH...O). Além disso, as informações cristalográficas mostraram a existência de interações pi-pi, um importante contato hidrofóbico que contribui para manter o arranjo supramolecular. / Xanthones are a group of heterocyclic molecules having a dibenzo-gama-pyrone skeleton, and can be obtained as a synthetic or natural product. These compounds have often been afforded from Brazilian medicinal plants and have received special attention due to their phytochemical and biological properties. However, this compound class was seldom studied in the solid state, mainly with regard to the crystal structure. The lack of crystallographic studies can be explained due to the difficulties found in the production of single crystals. So, the goal of the first stage of this project was to obtain well shaped single crystals of the xanthones derivatives and then to perform X-ray diffraction measurements. After the data collection, the crystal structures were solved and refined. Here, twelve crystal structures of oxygenated xanthones derivatives were studied, in which one tetra-oxygenated xanthone presented two crystal forms. Hence, there are eleven chemically different constituents (I-XI) involved in the context of the xanthones. It is worth to emphasize that only the structure named III was a redetermination, being the others ones studied by X-ray diffraction for the first time. The molecular geometric parameters of each compound were provided by the refined structure. Despite the intramolecular aspects, the conformations of the rings and the substituents were highlighted, besides the effects caused by them. Usually, in the xanthone rings the preferred conformation is the planar, which was confirmed by theoretical calculations. The effect of the resonance assisted hydrogen bond (RAHB) on the molecular conformation was widely studied in the 1-hydroxylated xanthones derivatives. Finally, the intermolecular interactions and their meaning to the crystal structures stabilization were discussed, revealing that in almost all xanthones, the crystal packing are kept by strong (OH...O) and weak (CH...O) hydrogen bonds. In addition, the crystallographic analysis also pointed out to the presence of interactions pi-pi, an important hydrophobic contact for supramolecular assembly.

In the present work, molecular dynamics simulations were used to evaluate the molecular interactions in prepolymerization mixtures, as occurring during production of molecularly imprinted polymers. The systems simulated were produced based on earlier studies for reference of results. Four systems were simulated in order to investigate the effect on molecular interactions based upon the choice of porogen (acetonitrile or chloroform) and proton transfers. The systems consisted of phenylalanine anilide as template, methacrylic acid as functional monomer, ethylene glycol dimethacrylate as crosslinker and 2,2’-azobis-(2-methylpropionitrile) as radical initiator, with either acetonitrile or chloroform as porogen. Trajectories from the simulations were evaluated through radial distribution function analysis, grid density analysis and hydrogen bond analysis to investigate molecular interactions and complex formations in the simulated complete prepolymerization mixtures. Focus was on functional monomer-template, crosslinker-template and template-template complex formations. The results showed that the porogen influences molecular interactions in complete prepolymerization mixtures. Formation of higher order complexes was confirmed in all of the systems involving all of the investigated molecular species in the prepolymerization mixtures. The results could also confirm the presence of previously observed complexes between functional monomer and template (2:1 and 1:1 stoichiometry) and the prevalence of template dimerization, as well as a high involvement of crosslinker in complex formation.

Molecular interactions enable us to understand the complexity of the human living system and how it can be exploited or malfunction to cause disease. The biomedical literature presents detailed knowledge of molecular functions and therefore represents a valuable reservoir of data for studying disease. However, extracting this data efficiently is difficult as it is spread over millions of publications in text that is not machine-readable. In this thesis we investigate how text mining can be used to automatically extract data for molecular interactions and their context relevant to disease. We focus on two globally relevant classes of diseases of which manifest from contrasting mechanisms: pain-related diseases and diseases caused by pathogenic organisms. Using HIV-1 as a case study, we first show that text mining can be used to partially recreate a large, manually curated database of HIV-1-human molecular interactions derived from the literature. We highlight both weaknesses in the quality of the data produced by the text-mining approach and strengths in it being able to extract this data rapidly, identifying instances missed in the manual curation and its potential as a support tool. We then expand on this approach by showing how an entirely new database of protein interactions relevant to pain can be created efficiently and accurately using text mining to generate the data and manual curation to validate the data quality. The following chapter then presents an analysis of 1,002 unique pain-related protein-protein interactions derived from this database, showing that it is of greater relevance to pain research than databases of pain interactions created from other common starting points. We highlight its value by, for example, identifying new drug repurposing opportunities and exploring differences in specific pain diseases using the contextual detail afforded by the text mining. Finally, we expand further on our approach to extracting molecular interactions from the literature, by showing how interactions between human proteins and pathogens can be curated across pathogenic organisms. We demonstrate how these techniques can be used to expand our knowledge of human pathogen related interaction data already stored in public databases, by identifying 42 new HIV-1-human molecular interactions, 108 new interactions between pathogen species and human proteins and 33 new human proteins that were found to interact with pathogens. Together, the results show that contexualised text mining, when supported by manual curation, can be used to extract molecular interactions for contrasting disease types in an efficient and accurate manner.

Bioactive compounds, such as curcumin, lutein, coenzyme Q10, β-carotene, cholecalciferol, astaxanthin, and β-sitosterol, have antioxidant and anti-inflammatory properties that promote health, but their low solubility, fast metabolism, and degradation have made it difficult to fully harness their potential. Encapsulation techniques, such as nano and microencapsulation using food-based biopolymers, have been employed to address these challenges. However, research efforts in protein-based delivery have mainly focused on encapsulation without considering structural, physicochemical, and matrix compatibility, which is tedious, unsustainable, and not cost-effective. Hence, this thesis reports the structural basis of guest-host interaction in the gastrointestinal delivery of lipophilic bioactive compounds using protein-based vehicles. This research employed fluorescence quenching techniques to estimate the influence of protein modification, fractionation and ionic strength on the nature and strength of interactions between protein and bioactive compounds. Morphological examination was carried out with transmission electron microscopy, confocal and widefield fluorescence microscopy whereas the sizes of the nano and micro-complexes was measured with dynamic light scattering techniques. Thermal stability was measured with differential scanning calorimetry and functional group characterization done with Fourier Transform infrared spectroscopy. Encapsulation efficiency was estimated by UV-Visible spectroscopy whereas in vitro bioactive compound release study was carried out in simulated salivary, gastric and intestinal fluids. Cytotoxicity assessment was estimated by calcein leakage assay. The study showed that protein modification affects the strength of protein-curcumin interaction and encapsulation efficiency. Pea protein succinylation increased electrostatic interaction with chitosan but decreased protein-curcumin interaction. Pea glutelin, albumin and globulin fractions showed different binding strengths with curcumin and the protein hydrophobicity and encapsulation efficiency correlated positively with the binding strength. The study also investigated the impact of bioactive compound lipophilicity and physiological ionic strength on the interaction between protein and bioactive compound. Lipophilicity influenced the strength of protein-bioactive compound interaction, while ionic strength changed the mode of interaction from static to static-dynamic quenching. The morphology of the nano and micro complexes formed with protein varied depending on the nature of encapsulated bioactive compound. Finally, bio-nano interaction involving giant unilamellar vesicles and curcumin-loaded pea protein of various surface functionalities as model biomembrane and nanoparticles respectively, was investigated. The result showed that while the protein/chitosan shell stabilizes bioactive compounds from degradation, the bioactive compound modulates their interaction with biomembrane. Overall, this work has demonstrated that for a rational design of protein-based nano/micro-encapsulation system, it is essential to consider the influence of the structural and physicochemical properties of proteins and bioactive compounds, stabilizing intermolecular forces, ionic strength of the environment, lipophilicity of the bioactive compounds, mechanism of release and modulation of cytotoxicity by bioactive compound. For instance, in high ionic strength solution, the stoichiometric ratio between protein carrier and bioactive compounds influences the stability of the complex. Balancing the intermolecular forces in the shell and core of bilayer complexes is essential for the stability of nanocomplexes and the presence of bioactive compound stabilizes the macromolecular carrier to minimal biomembrane disruption.

Yes / Investigations of structural reactivity, molecular interactions and vibrational characterization of pharmaceutical drugs are helpful in understanding their behaviour. The aim of this study is to determine the molecular, electronic and chemical properties of the antibiotic drug nitrofurantoin (NF), after cocrystallisation with 3-aminobenzoic acid (3ABA) and to understand how those changes lead to variation of properties in the cocrystal NF–3ABA. NF–3ABA formation is explained by stabilization via the hydrogen-bond network between NF and 3ABA molecules. It is thoroughly characterized by IR, Raman and CP-MAS solid-state 13C NMR techniques, along with quantum chemical calculations. The results of IR, Raman, and 13C NMR analyses showed that imide N–H23 and C12[double bond, length as m-dash]O of NF interact with the acid C[double bond, length as m-dash]O and –OH groups in 3-ABA, respectively. Therefore the IR, Raman, and 13C NMR spectra verified the formation of N–H⋯O and O–H⋯O hydrogen bonds. To study hydrogen bonding interactions theoretically in NF–3ABA, two functionals B3LYP and wB97X-D have been used. A comparison is made between the results obtained by B3LYP and those predicted at the wB97X-D level. It is found that wB97X-D is best applied density functional theory (DFT) functional to describe the hydrogen bonding interactions. The strength and nature of hydrogen bonding in NF–3ABA have been analysed by quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) analysis. To validate the results obtained by QTAIM theory and to study the long-range forces, such as van der Waals interactions, the steric effects in NF–3ABA, the reduced density gradient (RDG) and the isosurface have been plotted using Multiwfn software. QTAIM and isosurface analysis suggested that the hydrogen bonding interactions present in NF–3ABA are moderate in nature. The calculated HOMO–LUMO energy gap shows that NF–3ABA is more active than NF and 3ABA. Chemical reactivity descriptors are calculated to understand the various aspects of pharmacological sciences. Chemical reactivity parameters show that NF–3ABA is softer and chemically more reactive than NF. The results suggest that cocrystals can be a feasible alternative for positively changing the targeted physicochemical properties of an active pharmaceutical ingredient (API). / V. R. Vangala acknowledges the financial support of the Royal Society of Chemistry for mobility grant (2015/17).

Hearkening to calls from life scientists for aid in interpreting rapidly-growing repositories of data, the fields of bioinformatics and computational systems biology continue to bear increasingly sophisticated methods capable of summarizing and distilling pertinent phenomena captured by high-throughput experiments. Techniques in analysis of genome-wide gene expression (e.g., microarray) data, for example, have moved beyond simply detecting individual genes perturbed in treatment-control experiments to reporting the collective perturbation of biologically-related collections of genes, or "processes". Recent expression analysis methods have focused on improving comprehensibility of results by reporting concise, non-redundant sets of processes by leveraging statistical modeling techniques such as Bayesian networks. Simultaneously, integrating gene expression measurements with gene interaction networks has led to computation of response networks--subgraphs of interaction networks in which genes exhibit strong collective perturbation or co-expression. Methods that integrate process annotations of genes with interaction networks identify high-level connections between biological processes, themselves. To identify context-specific changes in these inter-process connections, however, techniques beyond process-based expression analysis, which reports only perturbed processes and not their relationships, response networks, composed of interactions between genes rather than processes, and existing techniques in process connection detection, which do not incorporate specific biological context, proved necessary. We present two novel methods which take inspiration from the latest techniques in process-based gene expression analysis, computation of response networks, and computation of inter-process connections. We motivate the need for detecting inter-process connections by identifying a collection of processes exhibiting significant differences in collective expression in two liver tissue culture systems widely used in toxicological and pharmaceutical assays. Next, we identify perturbed connections between these processes via a novel method that integrates gene expression, interaction, and annotation data. Finally, we present another novel method that computes non-redundant sets of perturbed inter-process connections, and apply it to several additional liver-related data sets. These applications demonstrate the ability of our methods to capture and report biologically relevant high-level trends. / Ph. D.