Le facteur de motilité autocrine (AMF) est une cytokine sécrétée par les cellules tumorales qui a été détectée dans le sérum et l'urine de patients cancéreux. Cette enzyme stimule la motilité des cellules cancéreuses in vitro et provoque des métastases in vivo. Elle peut être utilisée comme un biomarqueur métastasique.Dans cette étude, un biocapteur électrochimique sensible et spécifique a été conçu pour la détection et la quantification d'une enzyme modèle de l’AMF humain : la PGI de mammifère. Le biocapteur a été construit par liaison de 6-phosphate-D-fructose (F6P) sur une surface d'or d’électrode fonctionnalisée covalemment par des groupements oxyamine.La reconnaissance entre l’enzyme et le biorécepteur a été quantifiée par spectroscopie d'impédance électrochimique et voltammétrie dans une gamme de 10 fM à 100 nM. La limite de détection mesurée est de 6,6 fM. La sélectivité a été prouvée, ainsi que la reproductibilité. Notre biocapteur est une preuve de concept très prometteuse d'un futur dispositif analytique miniaturisé conçu pour la détection rapide, facile et précis de l'AMF. Il pourrait en outre contribuer à valider l'AMF en tant que nouveau biomarqueur du cancer métastatique.Afin d’étudier les interactions mises en jeu dans la reconnaissance entre l’enzyme et le biorécepteur, des études de mécanique moléculaire polarisable via le champ de forces SIBFA ont été réalisées. SIBFA est un champ de forces de seconde génération basé sur les résultats des décompositions ab-initio de l’énergie d’interaction et inclut donc la polarisation mais aussi l’énergie de transfert de charge.Pour cette étude nous avons mis en place deux modèles d’AMF pour SIBFA, une forme entière et une forme réduite, et nous avons construit un mime du biocapteur pour SIBFA. Pour cela, il a fallu concevoir et calibrer chaque fragment nécessaire à l’élaboration du mime. Ensuite différentes minimisations d’énergie ont été réalisées, en prenant en compte ou non la solvatation, puis des études sur les interactions mises en jeu ont été effectuées. / Autocrine motility factor (AMF) is a cytokine secreted by tumor cells that could be detected in the serum and the urine of cancer patients. This enzyme stimulates tumor cells motility in vitro and causes metastasis in vivo. It can be used as a biomarker of metastasis.In this study, a sensitive and specific electrochemical biosensor was designed for the detection and quantitation of a model of the human enzyme AMF: the mammalian PGI. The biosensor was constructed by covalently binding D-fructose 6-phosphate (F6P) on the oxyamine functionalized surface of a gold electrode.Recognition between the enzyme and the bioreceptor was quantified by electrochemical impedance spectroscopy and voltammetry in the range of 10 fM to 100 nM. The measured detection limit was 6.6 fM. Selectivity and reproducibility were also proven. Our biosensor is a promising proof of concept for the design of a future miniaturized analytical device for fast, easy and accurate detection of AMF. It could also help validate the AMF as a new biomarker of metastatic cancer.To study the interactions involved in the recognition process between the enzyme and the bioreceptor, we performed polarizable molecular mechanic studies using the force field SIBFA. SIBFA is a second-generation force field based on the results of ab- initio decomposition energy of interaction and therefore includes not only the polarization but also the charge transfer energy.For this study we have developed two models of AMF for SIBFA, an entire form and a reduced form, and we built a mime of the biosensor for SIBFA. For this, it was necessary to design and calibrate each fragment essential for the development of the mime. Then, different energy minimizations were carried out, some of which taking into account solvation parameters. Studies of interactions between the mime and the AMF model are being carried out.

L’électrophorèse est une technique puissante permettant de séparer des biomarqueurs présents dans les liquides biologiques.L’électrophorèse de zone libre transporte des molécules en milieu liquide sous l’influence de deux contributions : le flux électrophorétique et le flux électroosmotique (EOF). C’est ce dernier flux EOF qui permet d’optimiser la résolution analytique de la séparation et donc de simplifier le mélange avant sa détection. Notre équipe a développé un contrôle en temps réel de l’ EOF en intégrant une interface polarisable diélectrique dans un dispositif microfluidique. Le carbone amorphe azoté (CNx avec x=15%) a été choisi comme ce matériau.Comme le CNx ne peut pas être déposé directement sur un substrat de verre à cause de sa faible adhérence, deux matériaux différents ont été proposés comme couche d’accroche : le carbure de silicium (SiC) et le platine (Pt). Nous avons tout d’abord optimisé l’adhésion entre le film CNx et la couche d’accroche SiC par différentes procédures de fabrication. Cependant, en raison d’une faible adhérence, le film CNx s’est rapidement décollé en électrolyte liquide. Par contre, nous avons prouvé que certaines architectures hybrides incluant du Pt dans la couche d’accroche sont incroyablement robustes. Même après deux mois dans une solution millimolaire de KCl, le CNx adhérait toujours au verre sans aucune trace de délamination. Ce dispositif a fourni aussi une grande fenêtre de polarisabilité (de -1V à +1V). Nous avons enfin développé une architecture hybride « couche d’accroche isolée/couche électriquement polarisable/électrodes de grille enterrées/ polymère » afin d’éviter toute perte faradique dans l’électrolyte liquide ou vers les circuits conducteurs du dispositif. A l’issue de ces travaux, nous pensons être en mesure de proposer un composant fluidique complexe et robuste qui permet une modulation en temps réel de l’ EOF lors de migrations électrophorétiques. / Electrophoresis is currently an efficient way to separate precious biomarkers from complex mixtures. It takes place to transport molecules under two contributions: the electrophoretic flow and the electroosmotic flow (EOF). The latter allows to optimize the analytical resolution of the separation.Our team has developed a real-time dynamic control of the EOF by integrating a dielectric polarizable interface in the microfluidic device.Amorphous carbon nitride (CNx with x=15%) has dielectric properties and was chosen to be the polarizable interface. Since it cannot be deposited directly onto glass substrate, we have proposed and studied two different materials as the sticking underlayer: silicon carbide (SiC) and platinum (Pt).In the case of SiC, we have optimized the adhesion between CNx film and SiC underlayer through different fabrication procedures.However, due to poor adhesion, CNx film delaminated into liquid electrolyte quickly.Compared to SiC, Pt is a good sticking underlayerfor CNx. It was found out that even after two months in KCl solution, CNx still stuck robustly toPt. Meanwhile, the device provided a large windowof polarizability (from -1V to +1V). Finally, toavoid any faradic loss in the liquid electrolyte ortowards the conductive circuitry of the device, we have developed a sticking underlayer/electrically polarizable/polymeric hybrid architecture. This architecture appears to be the most robust existing polarizable interface for strong and long-term adhesion onto glass substrates.

Les composés à base de matériaux ferroélectriques présentent un large éventail de propriétés d'un grand intérêt fondamental et industriel. Ils possèdent un couplage entre la polarisation, la contrainte, le champ électrique et la température et trouvent application dans les dispositifs à l'échelle nanométrique. Les ferroélectriques sont aujourd'hui par exemple déjà utilisés dans les condensateurs, les mémoires, les capteurs et les actionneurs. Afin de comprendre la relation entre leurs propriétés physiques exceptionnelles et leur structure, des méthodes numériques capables de simuler à l'échelle nanométrique sont souhaitées. Pour ce faire, le modèle d'ions polarisables (PIM) est appliqué, modèle dans lequel les ions sont considérés comme des espèces polarisables possédant des charges nominales. En regard des techniques de modélisation actuelles, l'utilisation de charges nominales devrait faciliter l'inclusion de diverses compositions et l'étude des défauts et des effets de surface. Les paramètres du PIM sont dérivés par une procédure d'ajustement sur des données de références obtenues par des calculs avec la théorie de la fonctionnelle de la densité (DFT). Pour une première étape vers la modélisation ferroélectrique avec PIM, l'accent est mis sur le développement d'un potentiel d'interaction pour le prototype ferroélectrique BaTiO3. BaTiO3 présente une séquence complexe de transition de phase (rhomboédrique, orthorhombique, tétragonale, cubique) qui est liée à de petites différences d'énergie de l'ordre de quelques meV/unité de formule. Pour cette raison, le développement d'un potentiel d'interaction pour BaTiO3 nécessite une grande précision pour décrire correctement l’équilibre entre les interactions à courte et à longue portée. Il a été démontré au cours de ce travail que des effets asymétriques du nuage d'électrons par rapport au noyau seraient nécessaires pour une représentation précise des forces à courte portée. Puisque de tels effets ne sont pas inclus dans le PIM, des erreurs de compensation dans la procédure d'ajustement entre les interactions à courte et à longue portée sont permises afin d'obtenir le meilleur ajustement global. Le PIM développé pour BaTiO3 reproduit plusieurs propriétés à température nulle. À température finie, le PIM prédit que la phase rhomboédrique sera stable jusqu'à 160K. Dans la plage de température comprise entre 160K et 210K, de fortes fluctuations de la polarisation et des paramètres de maille sont observées et aucune phase bien définie ne peut être distinguée. A partir de 210K, la phase cubique paraélectrique est atteinte. Le modèle PIM développé dans cette thèse peut être appliqué à des études à basse température dans la phase ferroélectrique rhomboédrique. Il peut donc être utilisé pour étudier les effets de surface ou des lacunes d'oxygène dans la phase rhomboédrique de BaTiO3 . / Ferroelectric based compounds present a wide range of properties which are from great fundamental and industrial interest on nanoscale. Ferroelectric based compounds possesses strong coupling between polarization, stress, electric field and temperature and are nowadays already used in capacitors, memories, sensors, and actuators. In order to understand the relationship between microstructure and the outstanding properties, numerical methods able to simulate at nanoscale are disired. For this propose, the Polarizable Ion Model (PIM) is employed that treats the ions as polarizable species with nominal charge. In comparison to current modelisation techniques, the use of nominal charges should facilitate the inclusion of various materials composition and the study of defect and surface effects. The pametrization of the model is derived by a fit on ab initio DFT reference calculations. For a first step towards ferroelectric modelling with PIM, the focus lies on the developpment of an interaction potential for the prototyp ferroelectric BaTiO3. BaTiO3 presents a complex phase transition sequence (rhombohedral, orthorhombic, tetragonal, cubic) that is related to small energy differences of the order of some meV/formula unit. Thus, the development of a reliable interaction potential requires high precision and a correct description of the balance between short range and long range interactions. It has been demonstrated during this work that for an accurate representation of the short range forces asymmetric size effects of the electron cloud with respect to the nucleus would be necessary. As such size effects are not included in the PIM, compensation errors in the fitting procedure between short range and long range interactions are allowed in order to obtain the best global fit. The developed PIM model reproduces several zero temperature properties of BaTiO3. At finite temperature the PIM predicts the rhombohedral phase to be stable up to 160K. In the temperature range between 160K and 210K strong fluctuations in polarization and cell parameters are observed and no well-defined phase can be distinguished. From 210K on, the average paraelectric cubic phase is reached.

Redox reactions are crucial to biological processes that protect organisms against oxidative stress. Metalloenzymes, such as cytochrome c peroxidases which reduce excess hydrogen peroxide into water in the periplasm of multiple bacterial organisms, play a key role in detoxification mechanisms. While accurate computational tools can be used to simulate ground state redox potentials in biomolecules, adapting such approaches to properly describe redox reactions in transition metal complexes, particularly in hemes in heterogeneous protein environments, remains a significant challenge. Here we present the results of polarizable hybrid QM/MM studies of the reduction potentials of two heme sites in the cytochrome c peroxidase of Nitrosomonas europaea. The simulated redox potential of the catalytic site Low Potential (LP) is in good agreement with the experiment, while for the High Potential (HP) heme the computational estimate significantly overestimate the experimental value. We have found that environment polarization shifts the computed value of the redox potential of the catalytic LP heme by 1.3 V, while it does not affect that of the non-catalytic High Potential (HP) heme. We demonstrate that it is necessary to account for mutual polarization of heme site and the protein environment when describing redox processes, particularly those that involve more charged heme sites. We have explored the role of various factors such as heme geometries, axial ligands, propionate side chains, and electrostatic field of the protein in tuning the redox potentials of hemes in NeCcP. The fluctuations in computed vertical ionization and electron attachment energies are predominantly affected by fluctuations in the electrostatic field of the environment but not by fluctuations in heme geometries. We attribute the difference in computed LP and HP heme reduction potentials of 0.05 V and 1.15 V, respectively, to different axial ligands and electrostatic interactions of the hemes with the protein environment. / 2023-06-30T00:00:00Z

The present study attempts to find an alternate computational tool to model the complex physical interactions within the molten salt FLiNaK in a way that is both efficient and accurate. Additionally, this study seeks to describe the effects of several different types of impurities on the FLiNaK salt system. This study selects two different polarizable force fields, the AMOEBA polarizable approach and the polarizable ion model, to determine the density and the structure of the impure FLiNaK salt mixtures at typical operating temperatures in molten salt reactors (between 500-900 °C). This study conducts ab initio molecular dynamics (AIMD) simulations and classical molecular dynamics (CMD) for these salt mixtures to determine the correct parameter set for these two force fields. This study also uses an optimizer to minimize the difference between the forces calculated with AIMD and CMD simulation data. The AMOEBA polarizable approach is able to predict density for FLiNaK; however, it is unable to reliably predict other thermophysical properties due to the instability of its CMD simulations. The polarizable ion model is able to reliably determine density and salt structure for pure and impure FLiNaK mixtures. This model can be further used to determine other thermophysical properties. The polarizable ion model predicted densities for four impure salt mixtures: FLiNaK-MoF3, FLiNaK-UF3, FLiNaK-CsF, and FLiNaK-ZrF4. The predicted densities at 700 °C given in kg/m3 are 1929.94, 2454.15, 1650.67, and 1961.87, respectively with an error compared to the additive density model of -2.51%, -5.79%, -17.15%, and -1.67%, respectively. This study presents the radial distribution function and density correlation functions for each salt mixture. This study also presents a discussion of the shortcomings of the AMOEBA polarizable approach, as well as further work that may be done with these tools.

In this work, the development of parameters for a series of imidazolium-based ionic liquids molecules, now included in the AMOEBA force field, is discussed. The quality of obtained parameters is tested in a variety of calculations to reproduce structural, thermodynamic, and transport properties. First, it is proposed a novel method to parameterize in a faster, and more efficient way parameters for the AMOEBA force field that can be applied to any imidazolim-based cation. Second, AMOEBA-IL polarizable force field is applied to study the N-tert-butyloxycarbonylation of aniline reaction mechanism in water/[EMIM][BF4] solvent via QM/MM approach and compared with the reaction carried out in gas-phase and implicit solvent media. Third, AMOEBA-IL force field is applied in alchemical calculations. Free energies of solvation for selected solutes solvated in [EMIm][OTf] are calculated via BAR method implemented in TINKER considering the effect of polarization as well as the methodology to perform the sampling of the alchemical process. Finally, QM/MM calculations using AMOEBA to get more insights into the catalytic reaction mechanism of horseradish peroxidase enzyme, particularly the structures involved in the transition from Cp I to Cp II.

G-quadruplexes (GQs) are highly stable noncanonical nucleic acid structures that form in the DNA of human cells and play fundamental roles in maintaining genomic stability and regulating gene expression. These unique structures exert broad influence over biologically important processes and can modulate cell survival and human health. In fact, mutations, hyper-stability, and dissociation of GQs are implicated in neurodegenerative disease, mental retardation, premature-aging conditions, and various cancers. As such, GQs are novel drug targets. GQ-targeting therapeutics are developed to influence the folding and genetic interactions of GQs that are implicated in diseased states. To do so requires a greater understanding of GQ structure and dynamics and molecular dynamics (MD) simulations are well suited to provide these fundamental insights. Previous MD simulations of GQs have provided limited information due to inaccuracies in their models, namely the nonpolarizable nature of their force fields (FFs). The cutting-edge Drude polarizable FF models electronic degrees of freedom, allowing charge distribution to change in response to its environment. This is an important component for modeling ion-ion and ion-DNA interactions and can influence the overall stability of GQ structures. The work herein employs the Drude polarizable FF to 1) describe the role of electronic structure on the dynamics and folded stability of GQs, 2) determine the impact of ion interaction on GQ stability, and 3) characterize the role of G-hairpin motifs in GQ intermediates. Such fundamental investigations will help clarify GQs role in healthy and diseased states and transform our understanding of noncanonical DNA, improving human health, therapeutic design, and fundamental science. / Doctor of Philosophy / Human health and disease are influenced by unique nucleic acid structures called G-quadruplexes (GQs). GQs form when DNA or RNA fold into a square-shaped structure that is stabilized by ion interactions and special hydrogen bonding patterns. These GQ structures exert broad influence over normal biological processes, but also play a role in neurodegeneration, intellectual disabilities, premature-aging conditions, and various cancers, many of which are chemotherapeutic resistant. As such, modulating GQ structures, or their interactions with proteins, is a promising therapeutic approach. However, a greater understanding of GQ folding, folded structure, and interactions with other biomolecules is needed to do so. Computational techniques such as molecular dynamics (MD) simulations use experimental data and fundamental biophysics to gain new insights on these properties and inform novel drug design. In this project, we explored the dynamics of several distinct GQ structures and folding intermediates with state-of-the-art MD simulation methods. In doing so, we provided new insight on their structural features as well as their interactions with extended DNA sequences and different ion types, which serve as fundamental information for future structural or computer-aided drug design studies.

Yes / Materials-binding peptides offer promising routes to the production of tailored Pd nanomaterials in aqueous media, enabling the optimization of catalytic properties. However, the atomic-scale details needed to make these advances are relatively scarce and challenging to obtain. Molecular simulations can provide key insights into the structure of peptides adsorbed at the aqueous Pd interface, provided that the force-field can appropriately capture the relevant bio-interface interactions. Here, we introduce and apply a new polarizable force field, PdP-CHARMM, for the simulation of biomolecule–Pd binding under aqueous conditions. PdP-CHARMM was parametrized with density functional theory (DFT) calculations, using a process compatible with similar polarizable force-fields created for Ag and Au surfaces, ultimately enabling a direct comparison of peptide binding modes across these metal substrates. As part of our process for developing PdP-CHARMM, we provide an extensive study of the performance of ten different dispersion-inclusive DFT functionals in recovering biomolecule–Pd(111) binding. We use the functional with best all-round performance to create PdP-CHARMM.We then employ PdP-CHARMM and metadynamics simulations to estimate the adsorption free energy for a range of amino acids at the aqueous Pd(111) interface. Our findings suggest that only His and Met favor direct contact with the Pd substrate, which we attribute to a remarkably robust interfacial solvation layering. Replica-exchange with solute tempering molecular dynamics simulations of two experimentally-identified Pd-binding peptides also indicate surface contact to be chiefly mediated by His and Met residues at aqueous Pd(111). Adsorption of these two peptides was also predicted for the Au(111) interface, revealing distinct differences in both the solvation structure and modes of peptide adsorption at the Au and Pd interfaces. We propose that this sharp contrast in peptide binding is largely due to the differences in interfacial solvent structuring. / Air Force Office for Scientfi c Research (Grant #FA9550-12-1-0226)

With recent advances and cost reductions in next generation sequencing (NGS), the amount of genetic sequence data is increasing rapidly. However, before patient specific genetic information reaches its full potential to advance clinical diagnostics, the immense degree of genetic heterogeneity that contributes to human disease must be more fully understood. For example, although large numbers of genetic variations are discovered during clinical use of NGS, annotating and understanding the impact of such coding variations on protein phenotype remains a bottleneck (i.e. what is the molecular mechanism behind deafness phenotypes). Fortunately, computational methods are emerging that can be used to efficiently study protein coding variants, and thereby overcome the bottleneck brought on by rapid adoption of clinical sequencing. To study proteins via physics-based computational algorithms, high-quality 3D structural models are essential. These protein models can be obtained using a variety of numerical optimization methods that operate on physics-based potential energy functions. Accurate protein structures serve as input to downstream variation analysis algorithms. In this work, we applied a novel amino acid side-chain optimization algorithm, which operated on an advanced model of atomic interactions (i.e. the AMOEBA polarizable force field), to a set of 164 protein structural models implicated in deafness. The resulting models were evaluated with the MolProbity structure validation tool. MolProbity “scores” were originally calibrated to predict the quality of X-ray diffraction data used to generate a given protein model (i.e. a 1.0 Å or lower MolProbity score indicates a protein model from high quality data, while a score of 4.0 Å or higher reflects relatively poor data). In this work, the side-chain optimization algorithm improved mean MolProbity score from 2.65 Å (42nd percentile) to nearly atomic resolution at 1.41 Å (95th percentile). However, side-chain optimization with the AMOEBA many-body potential function is computationally expensive. Thus, a second contribution of this work is a parallelization scheme that utilizes nVidia graphical processing units (GPUs) to accelerate the side-chain repacking algorithm. With the use of one GPU, our side-chain optimization algorithm achieved a 25 times speed-up compared to using two Intel Xeon E5-2680v4 central processing units (CPUs). We expect the GPU acceleration scheme to lessen demand on computing resources dedicated to protein structure optimization efforts and thereby dramatically expand the number of protein structures available to aid in interpretation of missense variations associated with deafness.

Biological molecules are essential parts of organisms and participate in a variety of biological processes within cells. Understanding the relationship between sequence, structure, and function of biological molecules are of fundamental importance in life science and the health care industry. In this dissertation, a multi-scale approach was utilized to develop coarse-grained molecular models for protein and RNA simulations. By simplifying the atomistic representation of a biomolecular system, the coarse-grained approach enables the molecular dynamics simulations to reveal the biological processes, which occur on the time and length scales that are inaccessible to the all-atom models. For RNA, an "intermediate" coarse-grained model was proposed to provide both accuracy and efficiency for RNA 3D structure modeling and prediction. The overall potential parameters were derived based on structural statistics sampled from experimental structures. For protein, a general, transferable coarse-grain framework based on the Gay-Berne potential and electrostatic point multipole expansion was developed for polypeptide simulations. Next, an advanced atomistic model was developed to model electrostatic interaction with high resolution and incorporates electronic polarization effect that is ignored in conventional atomistic models. The last part of my thesis work involves applying all-atom molecular simulations to address important questions and problems in biophysics and structural biology. For example, the interaction between protein and miRNA, the recognition mechanism of antigen and antibody, and the structure dynamics of protein in mixed denaturants. / text