Heme-based gas sensor proteins have the ability to sense diatomic molecules such as O2 (FixL, EcDos or HemAT), CO (CooA, a CO-sensing protein of Rhodospirillum rubrum) and NO (guanylate cyclase) molecules and subsequently regulate numerous important biological processes in prokaryotic and eukaryotic organisms. The sensing function of these proteins is initiated by the binding of an effector (i.e., O2, CO, etc5) to the heme iron which then leads to a cascade of conformational events which gives rise to changes in kinase activity, DNA-binding activity, etc... In order to better understand the mechanism heme-based signaling, time resolved photothermal methods as well as transient optical techniques were utilized to obtain thermodynamic profiles for ligand binding/release in heme based signaling proteins including HemAT from Bacillus subtilis (aerotactic transducer), FixL from Sinorhizobium meliloti (regulation of the nitrogen fixation) and CooA from Rhodospirillum rubrum (transcriptional activator). In addition, a number of model systems were examined to understand the underlying thermodynamic processes involved in heme ligation. The variation of volume and enthalpy changes associated with spin state change of the iron from high-spin to low-spin where examined using the spin crossover Fe(III)(salten)(mepepy) complex. In addition, the experimental determination of the volume change due to electrostriction events were using Ru(II)(L)3 and the Debye-Hückel equation. Finally, different model heme proteins were studied to understand how a signal is conformationaly transmitted within a heme protein matrix. Sandbar shark hemoglobin was examined as an example of a non-signaling an allosteric protein. Two different peroxidases (horseradish and soybean) which have a direct channel between the heme pocket and the solvent involving no barrier energetic for the photodissociated ligand leaving the heme pocket were examined as example of non-signaling, non-allosteric proteins. The results show that each protein has a unique thermodynamic profile to conformationaly transmit signals subsequent to photodissociation of CO, even within the same class of protein (i.e. PAS domains, globins, etc...).

L'interaction non-covalente entre un ligand et un récepteur selon un modèle clé-serrure constitue une des bases essentielles de tout système biologique. La présence de multiples clés et serrures sur les biomolécules conduit à des interactions multivalentes. Les lectines sont très fréquemment structurées en homo-multimères et sont donc des cibles de choix pour l'étude des interactions avec des structures multivalentes glycosylées. Ligands et récepteurs multivalents peuvent obéir à plusieurs mécanismes d'association conduisant à des profils thermodynamiques et cinétiques permettant de rationnaliser les améliorations spectaculaires d'affinité souvent observées. L'utilisation de ligands de faible valence et de petite taille permet une présentation contrôlée des sucres au travers d'une structure unique bien définie. Ces glycoclusters sont des plateformes adaptées à l'étude de l'influence de la topologie de la présentation des sucres sur l'interaction. La synthèse de glycoclusters a été optimisée selon une voie convergente de glycosylation puis de couplage par CuAAC permettant la synthèse de structures multi-glycosylées telles que des calix[4]arènes de différentes conformations, des peptoïdes linéaires et cycliques ou encore des porphyrines. Ces ligands ont été évalués par quatre techniques d'analyse des interactions (HIA, ELLA, SPR, ITC) principalement en présence de la lectine PA-IL de Pseudomonas aeruginosa mais également avec la Galectine-1 humaine et la lectine d'Erythrina cristagalli (légumineuse). Des glycoclusters de seconde génération ont été ensuite été préparés avec l'objectif d'optimiser les composantes enthalpiques et entropiques de l'interaction. Les résultats indiquent que de légères modifications de la présentation des sucres peuvent induire des mécanismes d'association différents. La conception de structures rigidifiées a révélé des profils thermodynamiques contre-intuitifs qui ont pu être modélisés. Par cette étude, plusieurs ligands ont montré des affinités sans précédent pour la lectine PA-IL. Le meilleur ligand multivalent de première génération a confirmé un potentiel thérapeutique prometteur in vivo.

<p>Proteins fold into well-defined three-dimensional structures to carry out their biological functions which involve non-covalent interactions with other cellular molecules. Knowledge about the thermodynamic properties of proteins and protein-ligand complexes is essential for answering fundamental biological questions and drug or biomarker discovery. Recently, chemical labeling strategies have been combined with mass spectrometry methods to generate thermodynamic information about protein folding and ligand binding interactions. The work in this thesis is focused on the development and application of two such chemical labeling protocols coupled with mass spectrometry including one termed, SUPREX (stability of unpurified proteins from rates of H/D exchange), and one termed SPROX (stability of proteins from rates of oxidation). The work described in this thesis is divided into two parts. The first part involves the application of SUPREX to the thermodynamic analysis of a protein folding chaperone, Hsp33, and its interaction with unfolded protein substrates. The second part involves the development of a new chemical labeling protocol that can be used to make protein folding and ligand binding measurements on the proteomic scale. </p><p>In the first part of this work, the SUPREX technique was used to study the binding interaction between the molecular chaperone Hsp33 and four different unfolded protein substrates including citrate synthase, lactate dehydrogenase, malate dehydrogenase, and aldolase. The results of the studies, which were performed at the intact protein level, suggest that the cooperativity of the Hsp33 folding/unfolding reaction increases upon binding with denatured protein substrates. This is consistent with the burial of significant hydrophobic surface area in Hsp33 when it interacts with its substrate proteins. The SUPREX derived Kd-values for Hsp33 complexes with four different substrates were also found to be all within a range of 3-300 nM. The interaction between Hsp33 and one of its substrates, citrate synthase (CS), was characterized at a higher structural resolution by using the SUPREX technique in combination with a protease digestion protocol. Using this protocol, the thermodynamic properties for both Hsp33 and CS were evaluated at different stages of binding, including reduced Hsp33 (inactive form), oxidized Hsp33 (active form), followed by native CS and finally of Hsp33ox -CS complexes before and after reduction with DTT. The results suggest that Hsp33 binds unfolded proteins that still have a significant amount of residual higher- order structure. Structural rearrangements of the substrate protein appear to occur upon reduction of the Hsp33-substrate complexes, which may facilitate the transfer of the substrate protein to other protein folding chaperone systems. </p><p>In the second part of this dissertation, a mass spectrometry-based covalent labeling protocol, which relies on the amidination rate of globally protected protein amine groups, was designed and applied to the thermodynamic analysis of several eight protein samples including: six purified proteins (ubiquitin, BCAII, RNaseA, 4OT, and lysozyme with, and without GlcNAc), a five-protein mixture comprised of ubiquitin, BCAII, RNaseA, Cytochome C, and lysozyme, and a yeast cell lysate. The results demonstrate that in ideal cases the folding free energies of proteins and the dissociation constants of protein-ligand complexes can be accurately evaluated using the protocol. Also demonstrated is the new method's compatibility with three different mass spectrometry-based readouts including an intact protein readout using MALDI, a gel-based proteomics readout using MALDI, and an LC-MS-based proteomics readout using isobaric mass tags. The results of the cell lysate sample analysis highlight the complementarity of the labeling protocol to other chemical modification strategies that have been recently developed to make thermodynamic measurements of protein folding and stability on the proteomic scale.</p> / Dissertation

Two-stroke poppet-valved engines may combine the high power density of two - stroke engines and the low emissions of poppet-valved engines. A two-stroke diesel engine can generate the same power as a four-stroke engine of the same size, but at higher (leaner) air/fuel ratios. Diesel combustion at high air/fuel ratios generally means hydrocarbons, soot and carbon monoxide are oxidised more completely to water and carbon dioxide in the cylinder, and the opportunity to increase the rate of exhaust gas recirculation should reduce the formation of nitrogen oxides (NOx). The concept is being explored as a means of economically modifying diesel engines to make them cleaner and/or more powerful. This study details the application of two computational models to this problem. The first model is a relatively simple thermodynamic model created by the author capable of rapidly estimating the behaviour of entire engine systems. It was used to estimate near-optimum engine system parameters at single engine operating points and over a six-mode engine cycle. The second model is a detailed CFD model called KIVA-ERC. It is a hybrid of the KIVA engine modelling package developed at the Los Alamos National Laboratory and combustion and emissions subroutines developed at the University of Wisconsin-Madison Engine Research Center. It was used for detailed scavenging and combustion simulations and to provide estimates of emissions levels. Both models were calibrated and validated for four-stroke cycle operation using experimental data. The thermodynamic model was used to provide initial and boundary conditions to the KIVA-ERC model. Conversely, the combustion simulations were used to adjust zero-dimensional combustion correlations when experimental data was not available. Scavenging simulations were performed with shrouded and unshrouded intake valves. A new two-zone scavenging model was proposed and validated using multidimensional scavenging simulations. A method for predicting the behaviour of the two-stroke engine system based on four-stroke data has been proposed. The results using this method indicate that a four-stroke diesel engine with minor modifications can be converted to a two-stroke cycle and achieve substantially the same fuel efficiency as the original engine. However, emissions levels can not be predicted accurately without experimental data from a physical prototype. It is therefore recommended that such a prototype be constructed, based on design parameters obtained from the numerical models used in this study.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Um dos grandes desafios enfrentados pela indústria do petróleo é reduzir o impacto causado pela cristalização indesejável de hidrocarbonetos parafínicos de elevada massa molar em tubulações e equipamentos de produção. A cristalização de parafinas em petróleo é normalmente detectada através da determinação da temperatura inicial de aparecimento de cristais (TIAC), que pode ser estimada através de modelagem termodinâmica com base na composição do petróleo. Os objetivos deste trabalho são: estudar os principais modelos termodinâmicos adotados para descrever a precipitação de parafinas; verificar a validade desses modelos para os petróleos brasileiros e determinar qual modelo é o mais adequado para esses óleos. Para tanto, três formas de cálculo da razão entre as fugacidades das fases sólida e líquida e cinco modelos para calcular os coeficientes de atividade dos componentes em cada fase são aplicados aos dados de composição de vinte e três petróleos brasileiros. Os resultados mostram que o modelo ideal de múltiplas fases sólidas e o modelo de Escobar-Remolina geram valores bastante abaixo da TIAC experimental. Para os modelos de única fase sólida ideal, de Won e de Coutinho, foi possível observar que: a) a grande maioria dos erros é negativa; b) que estes se distribuem melhor em torno de zero quando se utiliza a correlação de Coutinho para o cálculo dos valores de &#61529;i; c) os valores de erro médio para os modelos de Coutinho, de Won e ideal com única fase sólida se equivalem, qualquer que seja o modelo utilizado para o cálculo de &#61529;i, exceto para o caso em que todos os compostos presentes na fase líquida podem precipitar; d) os valores obtidos através do modelo de Coutinho apresentam erro sistemático em relação ao modelo ideal de única fase sólida; e) as diferentes formas de se calcular a razão entre as fugacidades da fase sólida e líquida (&#61529;i) influenciam fortemente a capacidade preditiva dos modelos, o que não era esperado; f) o perfil do primeiro cristal formado nos petróleos é influenciado pelas moléculas mais pesadas presentes nos resíduos, o que mostra a necessidade de se desenvolver metodologias precisas e robustas de caracterização de resíduos; g) a inclusão de uma estimativa para a composição dos resíduos efetivamente melhorou o desempenho dos modelos em petróleos médio; h) em petróleos pesados, houve um aumento do erro de previsão da TIAC devido à pouca ou nenhuma quantidade de parafinas nos resíduos desses óleos. A necessidade de uma melhor caracterização dos resíduos de petróleos é corroborada pelo fato da TIAC calculada pelos modelos ser, via de regra, mais baixa que a TIAC experimental e pela melhora no desempenho dos modelos quando se estimou a composição dos resíduos, em petróleos médios / A major challenge faced by the oil industry is to reduce the impact of undesirable crystallization of high molecular weight paraffins in pipelines and production equipments. The paraffin crystallization is usually detected by measuring the wax appearance temperature (WAT), which can be estimated from composition based thermodynamic modeling. The goals of this work are: to study the main thermodynamic models adopted for paraffin crystallization description, to check models performances for Brazilian crudes and to determine the best model for these oils. For this, composition data from twenty-three Brazilian oils were used. For the thermodynamic modeling of wax precipitation in these crude oils, three forms of calculating the ratio between the solid and the liquid phase fugacities and five models to calculate the activity coefficients of components in each phase were used. The results showed that the ideal model for multiple solid phases and the Escobar-Remolina model give results far below the experimental WAT. For the single solid ideal, Won and Coutinho models, the points to be mentioned are described as follows: a) most of the errors is negative; b) the errors distribution is better when the correlation used for &#61529;i calculation is the number 2; c) the average errors for ideal, Won and Coutinho models are equivalent, except when all the oil components are considered to precipitate; d) the results obtained from Coutinho model presents systematic error in relation to the ideal model; e) the different ways to calculate the ratio between the solid and the liquid phase fugacities strongly influence the predictive ability of models, which was not expected; f) the composition profile of the first crystal formed in the oil is influenced by the heavier molecules in the residue, which shows the need of developing robust and accurate methods of heavy fractions characterization; g) the inclusion of an estimate for the residue composition effectively improved the performance of models for intermediate crude; h) for heavy oil, there was an increase in prediction error due to the little amount of paraffinic compounds in these residues. The need for better characterization of the residues is corroborated by the fact that the calculated WAT is normally lower than the experimental WAT and by the improvement on the models performance when the estimation of the residue composition was done for intermediate crudes

Face au problème des micropolluants émergents trouvés dans l’eau, l’utilisation de carbones activés est un moyen de réduire cette pollution à la source. Le but de ce travail est de mieux comprendre les mécanismes d’adsorption de certains micropolluants sur des tissus et feutres de carbones activés.Neuf molécules ont été étudiées dont des médicaments : la carbamazépine (CBZ), le diclofénac (DFN), l’ibuprofène (IBP) et l’ofloxacine (OFX), un produit anticorrosion : le benzotriazole (BZT), un perturbateur endocrinien : le bisphénol-A (BPA), deux herbicides : le mécoprop (MCP) et le pentachlorophénol (PCP) et une molécule utilisée comme indicateur de pollution des eaux usées : la caféine (CAF). Les adsorbants ultramicroporeux (tissu KIP1200 et feutre CSV4) et l’adsorbant mésoporeux (tissu BBV 800) (fournis par Dacarb, France) ont été caractérisés par adsorption d'azote à 77K et de CO2 à 273K, titrages acido-basiques (méthode de Boehm), mesure du pHpzc (point isoélectrique). Les cinétiques et isothermes d'adsorption ont été étudiées à 25°C à pH=7,5 dans un tampon phosphate NaHPO4/KH2PO4 (à 0,04M). La concentration résiduelle est analysée par HPLC.Les cinétiques d'adsorption ont été étudiées pour les 9 molécules à différentes concentrations initiales. Le temps pour atteindre l’équilibre d’adsorption dépend du volume des molécules ainsi que de leur affinité avec l’adsorbant. La quantité maximale adsorbable dépend du volume microporeux ainsi que de la surface spécifique de l’adsorbant, la quantité adsorbable est donc plus importante sur le tissu KIP 1200 que sur le feutre CSV 4. La vitesse de diffusion est la plus lente pour les adsorbants possédant un volume microporeux important, le tissu mésoporeux BBV 800 permet donc une adsorption rapide grâce à de plus larges pores qui permettent un accès plus rapide à la porosité.Des analyses en mélanges binaires et multi composés ont alors été réalisées pour connaître les paramètres clés gouvernant les cinétiques d’adsorption. Une compétition existe entre molécules dans certains cas (BZT et MCP par exemple) avec une première phase gouvernée par la cinétique d’adsorption liée à la diffusion dans les pores et la deuxième phase gouvernée par des phénomènes thermodynamiques entre le système soluté/solvant/carbone.Les isothermes d'adsorption ont été réalisés à 3 températures différentes et modélisées par des équations de Langmuir-Freundlich pour tous les micropolluants. Des paramètres thermodynamiques (enthalpie d’adsorption et enthalpie libre) ont alors été calculés et corrélés aux propriétés physico-chimiques des molécules. Une corrélation est mise en évidence entre l’enthalpie libre et la polarisabilité des molécules ainsi que les forces de Van der Waals déterminées avec le logiciel COSMO-RS mettant en évidence l’importance des forces non polaires dans le phénomène d’adsorption. Des mesures par calorimétrie d’adsorption à très faibles quantités adsorbées ont permis de mettre en évidence que l’entropie est le paramètre thermodynamique qui contrôle l’adsorption de molécules (BZT, PCP, CAF et OFX) sur le tissu KIP 1200. De fortes énergies d’interaction ont été mis en évidence entre les molécules (BZT, CAF et OFX) et les sites d’adsorption.Une étude d’adsorption-désorption de N2 et de CO2 sur des tissus KIP 1200 chargés en PCP, BZT, CAF et OFX a permis de mieux localiser le lieu de l’adsorption dans la porosité montrant une adsorption prioritairement dans les ultramicropores puis dans les supermicropores. Il a été montré également par cette méthode et par des mesures thermiques que l’eau est fortement adsorbée dans la porosité. / A lot of studies have revealed that some organic molecules such as pharmaceutical molecules, solvents, pesticides, etc.. are frequently found in water, at concentrations below µg/L, even after treatment at the exhaust of wastewater treatment plants. These molecules are highly toxic when accumulated in environment. One of the possibility for removing these micropollutants is the adsorption on activated carbons. Thus the aim of this work is to better understand the adsorption mechanism of some micropollutants onto activated carbon (ACs) in felt or fabric form.Nine micropollutants were studied, such as some pharmaceuticals: Carbamazepine (CBZ), Diclofenac (DFN), Ibuprofen (IBP), and Ofloxacin (OFX); one anti-corrosion compound : Benzotriazol (BZT); two herbicides : Mecoprop (MCP) and Pentachlorophenol (PCP) and an endocrine disruptor : Bisphenol A (BPA). Adsorption of Caffeine (CAF) which is an anthropic indicator of pollution in waste water, was also studied. The ACs (microporous KIP1200 fabric and CSV4 felt and mesoporous BBV 800 fabric, from Dacarb, France) were characterized by N2 adsorption-desorption at 77 K and CO2 adsorption at 273 K, pHpzc (point of zero charge) measurements and acido-basic titrations (Boehm method). The adsorption kinetics and isotherms were studied at pH 7.4 at 25°C in NaHPO4/KH2PO4 buffered solutions (about 0.04 M) using UV spectrometry and HPLC for the analysis of organic molecules in the remaining solution.Kinetics have been studied for 9 molecules at different initial concentrations. Time to reach adsorption equilibrium depends of the volume of the molecule and its affinity with the activated carbon. The maximum adsorbed quantity depends of the microporous volume and the specific area of the adsorbent, the adsorbed quantity is then bigger for KIP 1200 fabric than for CSV 4 felt. The speed of diffusion is slower for the adsorbent with high microporous volume, the mesoporous BBV 800 fabric gives place to a quick adsorption kinetics thanks to its large pores that gives an easy access to porosity.Binary and multi components kinetics have been done in order to understand key processes that drive kinetics adsorption. Competition between molecules have been shown (for BZT and MCP for example). Adsorption kinetics can be divided into two phases: the first one is driven by pore diffusion and the second one by thermodynamic phenomenon between the solute, the solvent and the AC.The adsorption isotherms of the molecules were studied at 13, 25 and 40°C; and the thermodynamic parameters (isoteric enthalpies and entropies Gibbs free energies) were determined. A correlation between Gibbs free energy and polarizability of molecules as well as Van der Waals energy calculated with Cosmotherm software shows the importance of non polar forces on adsorption phenomenon. Adsorption calorimetry experiments showed that entropy is the thermodynamic parameter that drives adsorption of molecules (BZT, PCP, CAF and OFX) onto KIP 1200 fabric.The pore size distributions of the carbons loaded with micropollutants were determined by DFT simulation from CO2 and N2 adsorption isotherms, to investigate the porosity accessible to the adsorbate. The accessible pore are firstly the ultramicropores and then supermicropores. With this technique and thermal experiments, it has been shown that water is highly bonded inside the porosity.