Protein-ligand and protein-protein interactions are critical to cellular function. Most cellular metabolic and signal tranduction pathways are influenced by these interactions, consequently molecular level understanding of these associations is an important area of biochemical research. We have examined the thermodynamics of several protein-protein associations and the protein-ligand interactions that mediate them. Using Fluorescence Correlation Spectroscopy, we have examined the putative interaction between pig heart malate dehydrogenase (MDH) and citrate synthase (CTS). We demonstrate a specific, low-affinity interaction between these enzymes. The association is highly polyethylene glycol (PEG)-dependent, and at high concentrations of NaCl or PEG, non-specific aggregates are formed. We demonstrate that oxaloacetate, the intermediate common to both CTS and MDH, induces the association at concentrations below the Km of CTS, suggesting that the open conformation of CTS is involved in the association. Using several biophysical techniques, we have examined the subunit associations of B. stearothermophilus phosphofructokinase (PFK). We demonstrate that the inhibitor bound conformation of the enzyme has reduced subunit affinity. The kinetics and thermodynamics of the phosphoenolpyrvuate (PEP)-induced dissociation of PFK have been quantified. Binding substrate, fructose-6-phosphate (F6P), stabilizes the enzyme to inhibitor-induced dissociation by 132-fold. These data suggest that subunit associations may play a role in the allosteric inhibition of PFK by PEP. The thermodynamics of the protein-ligand associations and allosteric inhibition of E. coli phosphofructokinase have been examined using intrinsic fluorescence and hydrostatic pressure. Both ligand-binding affinity and PEP inhibition are diminished by pressure, whereas substrate-binding affinity for inhibitor-bound enzyme is pressure-insensitive. Larger entropic than enthalpic changes with pressure lead to the overall reduction in free energies. Using a fluorescence-based assay, we have developed a series of baroresistant buffer mixtures. By combining a buffer with acid dissociation of negative volume with a buffer of positive volume, a pressure-resistant mixture is produced. Alteration of the molar ratio of the two component buffers yields mixtures that are pressure-insensitive at pH values around neutrality.

The development and approval of new drugs is an expensive process. The total cost for the approval of a new compound is on average 1.0 - 1.2 billion dollars and the entire process lasts about 12 - 15 years. The main difficulties are related to poor pharmacokinetics, lack of efficacy and unwanted side effects. These problems have naturally led to the question if new and alternative methodologies can be developed to find reliable and low cost alternatives to existing practices. Nowadays, computer-assisted tools are used to support the decision process along the early stages of the drug discovery path leading from the identification of a suitable biomolecular target to the design/optimization of drug-like molecules. This process includes assessments about target druggability, screening of molecular libraries and the optimization of lead compounds where new drug-like molecules able to bind with sufficiently affinity and specificity to a disease-involved protein are designed. Existing computational methods used by the pharmaceutical industry are usually focused on the screening of library compounds such as docking, chemoinformatics and other ligand-based methods to predict and improve binding affinities, but their reliable application requires improvements in accuracy. New quantitative methods based on molecular simulations of drug binding to a protein could greatly improve prospects for the reliable in-silico design of new potent drug candidates. A common parameter used by medicinal chemists to quantify the affinity between candidate ligands and a target protein is represented by the free energy of binding. However, despite the increased amount of structural information, predicting binding free energy is still a challenge and this technique has found limited use beyond academia. A major reason for limited adoption in the industry is that reliable computer models of drug binding to a protein must reproduce the change in molecular conformations of the drug and protein upon complex formation and this includes the correct modelling of weak non-covalent interactions such as hydrogen bonds, burials of hydrophobic surface areas, Van der Waals interactions, fixations of molecular degrees of freedom solvation/desolvation of polar groups and different entropy contributions related to the solvent and protein interactions. For several classes of proteins these phenomena are not easy to model and often require extremely computationally intensive simulations. The main goal of the thesis was to explore efficient ways of computing binding affinities by using molecular simulations. With this aim, novel software to compute relative binding free energies has been developed. The implementation is based on alchemical transformations and it extended a preexisted piece of software Sire, a molecular modeling framework, by using the OpenMM APIs to run fast molecular dynamics simulations on the latest GPGPU technology. This new piece of software has equipped the scientific community with a flexible and fast tool, not only to predict relative binding affinities, but also a starting point to develop new sampling methods for instance hybrid molecular dynamics and Monte Carlo. The implementation has been validated on the prediction of relative hydration free energy of small molecules, showing good agreement with experimental data. In addition, non-additive effects to binding affinities in series of congeneric Thrombin inhibitors were investigated. Although excellent agreement between predicted and experimental relative binding affinities was achieved, it was not possible to accurately predict the non-additivity levels in most of the examined inhibitors, thus suggesting that improved force fields are required to further advance the state-of-the art of the field.

<p>A new approach to analysis of protein-ligand interactions, termed proteochemometrics, has been developed. Contrary to traditional quantitative structure-activity relationship (QSAR) methods that aim to correlate a description of ligands to their interactions with one particular target protein, proteochemometrics considers many targets simultaneously.</p><p>Proteochemometrics thus analyzes the experimentally determined protein-ligand interaction activity data by correlating the data to a complex description of all interaction partners and; in a more general case even to interaction environment and assaying conditions, as well. In this way, a proteochemometric model analyzes an “interaction space,” from which only one cross-section would be contemplated by any one QSAR model.</p><p>Proteochemometric models reveal the physicochemical and structural properties that are essential for protein-ligand complementarity and determine specificity of molecular interactions. From a drug design perspective, models may find use in the design of drugs with improved selectivity and in the design of drugs for multiple targets, such as mutated proteins (e.g., drug resistant mutations of pathogens).</p><p>In this thesis, a general concept for creating of proteochemometric models and approaches for validation and interpretation of models are presented. Different types of physicochemical and structural description of ligands and macromolecules are evaluated; mathematical algorithms for proteochemometric modeling, in particular for analysis of large-scale data sets, are developed. Artificial chimeric proteins constructed according to principles of statistical design are used to derive high-resolution models for small classes of proteins.</p><p>The studies of this thesis use data sets comprising ligand interactions with several families of G protein-coupled receptors. The presented approach is, however, general and can be applied to study molecular recognition mechanisms of any class of drug targets.</p>

A new approach to analysis of protein-ligand interactions, termed proteochemometrics, has been developed. Contrary to traditional quantitative structure-activity relationship (QSAR) methods that aim to correlate a description of ligands to their interactions with one particular target protein, proteochemometrics considers many targets simultaneously. Proteochemometrics thus analyzes the experimentally determined protein-ligand interaction activity data by correlating the data to a complex description of all interaction partners and; in a more general case even to interaction environment and assaying conditions, as well. In this way, a proteochemometric model analyzes an “interaction space,” from which only one cross-section would be contemplated by any one QSAR model. Proteochemometric models reveal the physicochemical and structural properties that are essential for protein-ligand complementarity and determine specificity of molecular interactions. From a drug design perspective, models may find use in the design of drugs with improved selectivity and in the design of drugs for multiple targets, such as mutated proteins (e.g., drug resistant mutations of pathogens). In this thesis, a general concept for creating of proteochemometric models and approaches for validation and interpretation of models are presented. Different types of physicochemical and structural description of ligands and macromolecules are evaluated; mathematical algorithms for proteochemometric modeling, in particular for analysis of large-scale data sets, are developed. Artificial chimeric proteins constructed according to principles of statistical design are used to derive high-resolution models for small classes of proteins. The studies of this thesis use data sets comprising ligand interactions with several families of G protein-coupled receptors. The presented approach is, however, general and can be applied to study molecular recognition mechanisms of any class of drug targets.

Orientador: Anita Jocelyne Marsaioli / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-10T11:28:25Z (GMT). No. of bitstreams: 1 Figueiredo_IsisMartins_D.pdf: 1626484 bytes, checksum: 2c55f1a5b794f6f6e1c4a4931c394c4d (MD5) Previous issue date: 2006 / Resumo: Durante as últimas décadas, muitos métodos de RMN de H foram desenvolvidos e aplicados para triagem e caracterização de interações intermoleculares e para a metabonômica. Estes são temas recentes da RMN e ambos serão abordados em dois capítulos distintos neste trabalho. No Capítulo 1 foi realizada a implantação e otimização de técnicas de RMN como (STD, WaterLOGSY, NOE pumping e DOSY-NOESY). Para tanto, utilizou-se um sistema composto por albumina de soro bovino BSA e uma mistura de cinco compostos (ác. salicílico, cafeína, ác. cítrico, ác. adipico e D-glucose) dentre os quais, apenas o ácido salicílico e a cafeína interagiram com a BSA. Além disso, uma análise comparativa entre as técnicas permitiu afirmar que os experimentos de STD e WaterLOGSY são os mais sensíveis e rápidos fornecendo complementarmente o domínio hidrofóbico e hidrofílico de ligação com o ligante. Com intuito de confirmar nossa habilidade na aplicação destas técnicas, as mesmas foram aplicadas a um sistema composto por uma Chaperone Hsp70, substratos (ATP e ADP) e um polipeptíteo Angiotensina 2 (Asp-Arg-Val-Tyr-Ile-His-Pro-Phe). A análise desse sistema por WaterLOGSY e a comparação com os resultados obtidos por STD permitiu a obtenção do epitopo 1 o qual é formado pela porção adenosina do A TP ou ADP quando estes estão complexados a Hsp70 e do epitopo 2 formado pela porção hidrofóbica da Angiotensina 2 (Val-Tyr-Ile-His-Pro-Phe) que interage com a Hsp70. Já no Capitulo 2, a RMN de H foi aplicada na investigação da metabonômica do liquido cerebroespinal de pacientes com Esclerose Múltipla (EM). A análise dos dados de RMN através de métodos quimiométricos (HCA, PCA e PLS-DA) revelou alguns metabólitos importantes, dentre os quais o b-hidroxibutirato (1,17 ppm) e um sinal de proteína (0,065 ppm) foram detectados apenas em amostras EM podendo ser considerados marcadores de reações bioquímicas de degradação de mielina. Portanto, este estudo alcançou com êxito os objetivos traçados de implementar novas técnicas de RMN aplicadas a sistemas biológicos além de trazer novas informações sobre a Hsp70 e EM / Abstract: Over the past years H NMR methods have been developed and applied to the screening and characterization of protein epitopes in ligand receptor complexes and metabonomics. These are recent NMR methods issues of the present PhD thesis. To investigate proteinligand complexes we first optimized techniques that were unavailable at IQ/UNICAMP such as STD, WaterLOGSY, NOE pumping and DOSY-NOESY which were specially designed for epitope mapping. In order to optimized these techniques we employed a mixture of five compounds (salicilic ac., caffeine, citric ac., adipic ac. and D-glucose) and bovine serum albumine (BSA). Among the studied ligands salicilic acid and caffeine were the best. From these experiments we additionally concluded that STD and WaterLOGSY were most sensitive and appropriate for epitope mapping. A second system was investigated consisting of Chaperone Hsp70, cofactor (ATP and ADP) and polypeptide Angiotensine 2 (Asp-Arg-Val-Tyr-Ile-His-Pro-Phe). Epitope I was characterized as containing a lipophylic domain in which the adenosine portion of ATP or ADP was bound to Hsp70. Epitope 2 was the polypeptide-binding site in which the apoIar portion of Angiotensine 2 (Val-Tyr-Ile-His-Pro-Phe) was tightly bound to Hsp70. In chapter 2, H NMR was the major tool employed to investigate the metabonomics of CSF of Multiple Sclerosis patients. Analyses of the H NMR data applying quimiometric methods (HCA, PCA and PLS-DA) revealed that some metabolites, from which b-hydroxybutirate (1,17 ppm) and a protein signal (0,065 ppm) were detected in EM patients only. These signals were never described as EM biomarkers before. To match these observations a full set of lipolytic and proteolytic biochemical reactions were proposed which are responsible for myelin degradation. Therefore, in this study we describe the successful implementation of these new NMR techniques that were applied to biological systems revealing new aspects of the Hsp70 and MS / Doutorado / Quimica Organica / Doutor em Ciências

<p>Detection and quantification of protein-ligand binding interactions is extremely important for understanding interactions that occur in biological systems. Since traditional techniques for characterizing these types of interactions cannot be performed in complex systems such as cell lysates, a series of energetics-based techniques that are capable of assessing protein stability and measuring ligand binding affinities have been developed to overcome some of the limitations of previous techniques. Now that the capabilities of the energetics-based techniques have been exhibited in model systems, the false-positive rates of the techniques, the range of biological questions to which the techniques can be addressed, and the use of the techniques to discover novel interactions in unknown systems remained to be shown. The Stability of Proteins from Rates of Oxidation (SPROX) technique and the Pulse Proteolysis (PP) technique were applied to a wide range of biological questions in both yeast and human cell lysates to evaluate the scope of these experimental workflows. The false-positive rate of iTRAQ-SPROX protein target discovery on orbitrap mass spectrometer systems was determined to be < 0.8 %. The iTRAQ-SPROX technique was successfully applied to the discovery of both known and novel protein-protein, protein-ATP, and protein-drug interactions, leading to the quantification of protein-ligand binding affinities in each of these studies. In the pursuit of discovering geldanamycin protein interactors, the use of iTRAQ-SPROX and SILAC-PP in combination was determined to be advantageous for confirming protein-ligand interactions since the techniques utilize different quantitation strategies that are subject to separate technical errors in quantitation. Finally, the iTRAQ-SPROX and SILAC-PP techniques were used to evaluate the interactions of manassantin A in a human cell lysate. In this work, a previously unknown protein target of manassantin A, Filamin A, was detected as a hit protein using both the iTRAQ-SPROX and SILAC-PP protocols. The work completed in this dissertation has expanded the understanding of the limitations of energetics-based techniques and shown that biological replicate analyses are essential to confirm ligand interactions with novel protein targets.</p> / Dissertation

La compréhension et la prédiction des relations structure-fonction de protéines par des approches in sillico représentent aujourd'hui un challenge. Malgré le développement récent de méthodes algorithmiques pour l'étude du mouvement et des interactions moléculaires, la flexibilité de macromolécules reste largement hors de portée des outils actuels de modélisation moléculaire. L'objectif de cette thèse est de développer une nouvelle approche basée sur des algorithmes de planification de mouvement issus de la robotique pour mieux traiter la flexibilité moléculaire dans l'étude des interactions protéiques. Nous avons étendu un algorithme récent d'exploration par échantillonnage aléatoire, ML-RRT pour le désassemblage d'objets articulés complexes. Cet algorithme repose sur la décomposition des paramètres de configuration en deux sous-ensembles actifs et passifs, qui sont traités de manière découplée. Les extensions proposées permettent de considérer plusieurs degrés de mobilité pour la partie passive, qui peut être poussée ou attirée par la partie active. Cet outil algorithmique a été appliqué avec succès pour l'étude des changements conformationnels de protéines induits lors de la diffusion d'un ligand. A partir de cette extension, nous avons développé une nouvelle méthode pour la résolution simultanée du séquençage et des mouvements de désassemblage entre plusieurs objets. La méthode, nommée Iterative-ML-RRT, calcule non seulement les trajectoires permettant d'extraire toutes les pièces d'un objet complexe assemblé, mais également l'ordre permettant le désassemblage. L'approche est générale et a été appliquée pour l'étude du processus de dissociation de complexes macromoléculaires en introduisant une fonction d'évaluation basée sur l'énergie d'interaction. Les résultats présentés dans cette thèse montrent non seulement l'efficacité mais aussi la généralité des algorithmes proposés. / Understanding and predicting structure-function relationships in proteins with fully in silico approaches remain today a great challenge. Despite recent developments of computational methods for studying molecular motions and interactions, dealing with macromolecular flexibility largely remains out of reach of the existing molecular modeling tools. The aim of this thesis is to develop a novel approach based on motion planning algorithms originating from robotics to better deal with macromolecular flexibility in protein interaction studies. We have extended a recent sampling-based algorithm, ML-RRT, for (dis)-assembly path planning of complex articulated objects. This algorithm is based on a partition of the configuration parameters into active and passive subsets, which are then treated in a decoupled manner. The presented extensions permit to consider different levels of mobility for the passive parts that can be pushed or pulled by the motion of active parts. This algorithmic tool is successfully applied to study protein conformational changes induced by the diffusion of a ligand inside it. Building on the extension of ML-RRT, we have developed a novel method for simultaneously (dis)assembly sequencing and path planning. The new method, called Iterative-ML-RRT, computes not only the paths for extracting all the parts from a complex assembled object, but also the preferred order that the disassembly process has to follow. We have applied this general approach for studying disassembly pathways of macromolecular complexes considering a scoring function based on the interaction energy. The results described in this thesis prove not only the efficacy but also the generality of the proposed algorithms

In recent years the application of single-molecule techniques to probe biomolecules and intermolecular interactions at single-molecule resolution has expanded rapidly. Here, I investigate a series of peptides and proteins in an attempt to gain a better understanding of nanopore sensing as a single-molecule technique. The analysis of retro, inversed, and retro-inversed isomers of glucagon and α-helical Fmoc-D2A10K2 peptide showed that nanopore sensing utilizing a wild-type α-hemolysin pore can distinguish between all four isomers while circular dichroism can only distinguish between chiral isomers, but not between directional isomers. The investigation of a series of proteins of different chemical and physical properties revealed important information about nanopore analysis of proteins. Contrary to some reports in the literature, all proteins analysed here induced large blockade events. The frequency of total events and the proportion of large blockade events were significantly reduced in tris(hydroxymethyl)aminomethane or 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid buffers and were only restored by the addition of ethylenediaminetetraacetic acid or the use of phosphate buffer, both of which can sequester metal ions. Furthermore, the results obtained with the proteins in the presence of ligands demonstrated that transient or partial unfolding of proteins can be detected by nanopore analysis confirming the usefulness of this technique for conformational studies or for protein/ligand interactions. Interestingly, while the blockade current histograms were different for each protein there was no obvious correlation between the properties of the proteins and the blockade current histograms. In an attempt to identify whether the large blockade events were translocation or intercalation, both an indirect and a direct approach were taken. The indirect approach which relies on the effect of voltage on the interaction of the molecule with the pore provided no conclusive answer to the question of protein translocation through the α-hemolysin pore. In contrast, the direct approach in which ribonuclease A is added to the cis side of the pore and then the trans side is tested for enzyme activity showed that ribonuclease A doesn't translocate through the α-hemolysin pore.

<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

Les interactions intermoléculaires entre une protéine et ses différents partenaires représentent des cibles de plus en plus prisées pour l'élaboration de composés thérapeutiques capables d'intervenir dans des processus biologiques. La méthode FBDD (Fragment-Based Drug Design) permet de concevoir des molécules bioactives tels que des inhibiteurs, à partir de la structure tridimensionnelle du complexe formé entre la protéine et une molécule fragment. Dans le cadre de ce projet de thèse nous proposons d'utiliser le déplacement chimique pour l'étude des structures 3D de ces complexes protéine-ligand. Nous nous focaliserons sur la mesure des perturbations de déplacement chimique CSP (Chemical Shift Perturbations) des atomes d'une protéine cible, induites par la liaison d'un fragment. Nous démontrerons la puissance de cet outil RMN à travers la simulation des CSP induits par l'interaction d'un fragment sur une protéine cible et leur comparaison aux CSP expérimentaux. L'analyse sera réalisée sur deux protéines cibles et la comparaison des données expérimentales et simulées permettra dans un premier temps de mettre en évidence un réarrangement structural de la protéine Bcl-xL lors de son interaction avec un fragment. Puis, dans un second temps, nous montrerons que cette analyse quantitative des CSP peut permettre de déterminer l'orientation des fragments dans le site d'interaction de la protéine PRDX5. Nous comparerons alors les performances de la méthode pour différents types de protons proposant ainsi de nouvelles pistes pour la compréhension du comportement des CSP vis-à-vis de leurs contributions électroniques / Intermolecular interactions between protein and its partners represent highly attractive targets for the elaboration of therapeutic compounds abble to interfere in biological processes. A novel approach in drug design called Fragment-Based Drug Design (FBDD) consists of designing bioactive molecules like inhibitors, from the 3D structure of the complex formed between a protein and a fragment molecule (MW < 300g/mol). Here we suggest using the chemical shift, to study these protein-ligand structures. We will particularly focus on the measurement of Chemical Shift Perturbations (CSP) induced by the fragment-binding on protein’s nuclei. We will evidence the potency of this NMR tool through simulation of CSP induced by fragment interaction on protein target and the comparison with experimental CSP. Two protein targets will be used and the comparison between experimental and simulated data will evidence on one hand, the structural rearrangement of the protein Bcl-xL upon fragment-binding. On the other hand, we will demonstrate that this quantitative use of CSP is unable to determinate fragment orientations inside the protein PRDX5 binding site. We will compare the performances of the method for different kinds of protein and proposing answers to better understand the behaviour of CSP toward their different electronic contributions