A modelagem das interações entre macromoléculas e ligantes ainda se depara com diversos desafios na área de desenho de fármacos assistidos por computador. Apesar do crescimento da área, temas como a flexibilidade do receptor, funções de pontuação e solvatação ainda têm sido alvo de intensa investigação na comunidade científica. Com o objetivo de analisar a interação em milhares ou milhões de complexos, é imprescindível uma boa harmonização entre o custo computacional e a acurácia dos métodos computacionais que permitem a classificação de ligantes de acordo com a energia de interação. O LiBELa (Ligand Binding Energy Landscape) é um programa de docagem molecular com abordagem híbrida, ou seja, utiliza informações do ligante e do receptor durante o processo de docagem. Inicialmente, as características estéricas e eletrostáticas de um ligante de referência (cristalográfico, por exemplo) são utilizadas nos cálculos de similaridade e sobreposição, obtendo assim uma conformação inicial pré-otimizada do ligante testado. Em seguida, a energia de interação é minimizada no sítio ativo de receptor a partir de potenciais energéticos. Quatro funções de pontuação baseadas em campo de força foram testadas e otimizadas, compostas por potenciais de van der Waals, de Coulomb, e uma função empírica de solvatação denominada função de Stouten-Verkhivker (SV). A flexibilidade do sistema foi tratada através da geração de confôrmeros que amostram os graus de liberdade dos ligantes descritos como semi-rígidos e através de potenciais atenuados que suavizam a superfície de energia de interação, permitindo interações em distâncias interatômicas antes repulsivas. Como ponto de partida, os métodos implementados no programa LiBELa demonstraram resultados satisfatórios nos testes de cross- e self-docking, mostrando ser uma ferramenta eficiente em encontrar os modos de ligação cristalográficos de forma equivalente ou até melhor às dos programas comparados. Através de testes de enriquecimento nos conjuntos de dados DUD, DUDE e CM-DUD, foram otimizadas de forma sistemática as constantes dielétrica, do termo de solvatação, e dos termos de atenuação. Também foi realizado um paralelo entre as funções de pontuação, incluindo a atenuação e o termo de solvatação. Estes mesmos testes mostraram resultados superiores do LiBELa de 39% e 15% em comparação com um programa baseado puramente no receptor (DOCK 6.6), relativo à média da área sob a curva em escala semi-logarítmica nas bases de dados DUDE e DUD respectivamente. Apesar da função de solvatação SV implementada no LiBELa apresentar boa correlação com dados experimentais (r=0,72) e com o modelo Zou GB de solvatação (r=0,88), não apresentou correlação significativa com os métodos GB e PB implementados no pacote de programas disponível no AmberTools. Comparadas às funções de pontuação do LiBELa, as funções com correção para solvatação apresentaram pior enriquecimento, salvo alguns alvos específicos. Por fim, foram realizados ensaios de docagem molecular utilizando como alvo uma enzima β-galactosidase da família GH42, cuja estrutura fora resolvida em nosso grupo. Os resultados permitiram conclusões acerca de como o modo de ligação interfere na preferência de ligação entre dissacarídeos de ligações glicosídicas distintas, consistentes com dados experimentais de ensaios cinéticos de ligação. / Modeling the interactions between macromolecules and ligands still faces several challenges in the computer-aided drug design area. Despite the growth in the area, subjects such as receptor flexibility, scoring functions and solvation still have been widely explored in the scientific community. In order to analyze the interaction for thousands or millions of complexes, a good harmonization between the computational cost and the accuracy of the calculation methods in molecular docking programs is essential. LiBELa (Ligand Binding Energy Landscape) is a hybrid approach program that uses both ligand and receptor information for ligand docking. Initially, the steric and electrostatic characteristics from a reference binder (crystallographic, for example) are used to similarity and overlay calculations, thus obtaining an initial conformation of the ligand tested. Then, within the receptor´s active site, the interaction energy is minimized using energetic potentials. Four force field-based scoring functions were tested and optimized, composed of van der Waals and Coulomb potentials and an empirical solvation function called Stouten-Verkhivker (SV). Concerning the system flexibility, besides the confomers generation that sample the degrees of freedom for semi-rigid ligands, attenuated potentials smooth the energy surface allowing interactions between previously repulsive interatomic distances. As a starting point, LiBELa performed satisfactorily in the cross- and self-docking tests, showing that is an eficient tool to reproduce crystallographic binding modes equivalently to or even better than reference programs. Through enrichment of DUD, DUDE and CM-DUD datasets, the dielectric constant, solvation and softening terms were systematically optimized. It also allowed a parallel between scoring functions, including attenuation and solvation term. Finally, it revealed the LiBELa showed an enhancement of 39% and 15% as compared to the purely receptor-based program DOCK 6.6, relative to the mean of the area under the curve on a semi-logarithmic scale in the DUDE and DUD databases respectively. Although the SV solvation function implemented in LiBELa showed good correlations with experimental data (r = 0.72) and with the Zou GB / SA solvation method implemented in DOCK6 (r = 0.88), it did not show significant correlation with the GB/SA and PB/SA methods implemented in AmberTools. Comparing all the LiBELa tested scoring functions, those including solvation correction showed worse enrichments, except for some specific targets. Finally, molecular docking experiments using LiBELa were conducted with a β-galactosidase from GH42 family, whose structure was solved in our group. The results allowed conclusions concerning how the binding mode interferes the preference for some disaccharides of distinct glycosidic bonds, consistent with experimental data from kinetic assays.

A modelagem das interações entre macromoléculas e ligantes ainda se depara com diversos desafios na área de desenho de fármacos assistidos por computador. Apesar do crescimento da área, temas como a flexibilidade do receptor, funções de pontuação e solvatação ainda têm sido alvo de intensa investigação na comunidade científica. Com o objetivo de analisar a interação em milhares ou milhões de complexos, é imprescindível uma boa harmonização entre o custo computacional e a acurácia dos métodos computacionais que permitem a classificação de ligantes de acordo com a energia de interação. O LiBELa (Ligand Binding Energy Landscape) é um programa de docagem molecular com abordagem híbrida, ou seja, utiliza informações do ligante e do receptor durante o processo de docagem. Inicialmente, as características estéricas e eletrostáticas de um ligante de referência (cristalográfico, por exemplo) são utilizadas nos cálculos de similaridade e sobreposição, obtendo assim uma conformação inicial pré-otimizada do ligante testado. Em seguida, a energia de interação é minimizada no sítio ativo de receptor a partir de potenciais energéticos. Quatro funções de pontuação baseadas em campo de força foram testadas e otimizadas, compostas por potenciais de van der Waals, de Coulomb, e uma função empírica de solvatação denominada função de Stouten-Verkhivker (SV). A flexibilidade do sistema foi tratada através da geração de confôrmeros que amostram os graus de liberdade dos ligantes descritos como semi-rígidos e através de potenciais atenuados que suavizam a superfície de energia de interação, permitindo interações em distâncias interatômicas antes repulsivas. Como ponto de partida, os métodos implementados no programa LiBELa demonstraram resultados satisfatórios nos testes de cross- e self-docking, mostrando ser uma ferramenta eficiente em encontrar os modos de ligação cristalográficos de forma equivalente ou até melhor às dos programas comparados. Através de testes de enriquecimento nos conjuntos de dados DUD, DUDE e CM-DUD, foram otimizadas de forma sistemática as constantes dielétrica, do termo de solvatação, e dos termos de atenuação. Também foi realizado um paralelo entre as funções de pontuação, incluindo a atenuação e o termo de solvatação. Estes mesmos testes mostraram resultados superiores do LiBELa de 39% e 15% em comparação com um programa baseado puramente no receptor (DOCK 6.6), relativo à média da área sob a curva em escala semi-logarítmica nas bases de dados DUDE e DUD respectivamente. Apesar da função de solvatação SV implementada no LiBELa apresentar boa correlação com dados experimentais (r=0,72) e com o modelo Zou GB de solvatação (r=0,88), não apresentou correlação significativa com os métodos GB e PB implementados no pacote de programas disponível no AmberTools. Comparadas às funções de pontuação do LiBELa, as funções com correção para solvatação apresentaram pior enriquecimento, salvo alguns alvos específicos. Por fim, foram realizados ensaios de docagem molecular utilizando como alvo uma enzima β-galactosidase da família GH42, cuja estrutura fora resolvida em nosso grupo. Os resultados permitiram conclusões acerca de como o modo de ligação interfere na preferência de ligação entre dissacarídeos de ligações glicosídicas distintas, consistentes com dados experimentais de ensaios cinéticos de ligação. / Modeling the interactions between macromolecules and ligands still faces several challenges in the computer-aided drug design area. Despite the growth in the area, subjects such as receptor flexibility, scoring functions and solvation still have been widely explored in the scientific community. In order to analyze the interaction for thousands or millions of complexes, a good harmonization between the computational cost and the accuracy of the calculation methods in molecular docking programs is essential. LiBELa (Ligand Binding Energy Landscape) is a hybrid approach program that uses both ligand and receptor information for ligand docking. Initially, the steric and electrostatic characteristics from a reference binder (crystallographic, for example) are used to similarity and overlay calculations, thus obtaining an initial conformation of the ligand tested. Then, within the receptor´s active site, the interaction energy is minimized using energetic potentials. Four force field-based scoring functions were tested and optimized, composed of van der Waals and Coulomb potentials and an empirical solvation function called Stouten-Verkhivker (SV). Concerning the system flexibility, besides the confomers generation that sample the degrees of freedom for semi-rigid ligands, attenuated potentials smooth the energy surface allowing interactions between previously repulsive interatomic distances. As a starting point, LiBELa performed satisfactorily in the cross- and self-docking tests, showing that is an eficient tool to reproduce crystallographic binding modes equivalently to or even better than reference programs. Through enrichment of DUD, DUDE and CM-DUD datasets, the dielectric constant, solvation and softening terms were systematically optimized. It also allowed a parallel between scoring functions, including attenuation and solvation term. Finally, it revealed the LiBELa showed an enhancement of 39% and 15% as compared to the purely receptor-based program DOCK 6.6, relative to the mean of the area under the curve on a semi-logarithmic scale in the DUDE and DUD databases respectively. Although the SV solvation function implemented in LiBELa showed good correlations with experimental data (r = 0.72) and with the Zou GB / SA solvation method implemented in DOCK6 (r = 0.88), it did not show significant correlation with the GB/SA and PB/SA methods implemented in AmberTools. Comparing all the LiBELa tested scoring functions, those including solvation correction showed worse enrichments, except for some specific targets. Finally, molecular docking experiments using LiBELa were conducted with a β-galactosidase from GH42 family, whose structure was solved in our group. The results allowed conclusions concerning how the binding mode interferes the preference for some disaccharides of distinct glycosidic bonds, consistent with experimental data from kinetic assays.

A range of biochemically diverse molecules located in the plasma membrane— such as proteins, glycans, and lipids—mediate cellular recognition events, initiation of signalling pathways, and the regulation of processes important for the normal development and function of multicellular organisms. Interactions mediated by cell surface receptors can be challenging to detect in biochemical assays, because they are often highly transient, and membrane-embedded receptors are difficult to solubilise in their native conformation. The biochemical features of low-affinity extracellular protein interactions have therefore necessitated the development of bespoke methods to detect them. Here, I develop a genome-scale cell-based genetic screening approach using CRISPR-Cas9 knockout technology that reveals cellular pathways required for specific cell surface recognition events. Using a panel of high-affinity monoclonal antibodies, I first establish a method from which I identify not only the direct receptor but also other required gene products, such as co-receptors, post-translational modi cations, and transcription factors contributing to antigen expression and subsequent antibody-antigen recognition on the surface of cells. I next adapt this method to identify cellular factors required for receptor interactions for a panel of recombinant proteins corresponding to the ectodomains of cell surface proteins to the endogenous surface receptors present on a range of cell lines. In addition to finding general cellular features recognised by many ectodomains, I also identify direct interaction partners of recombinant protein probes on cell surfaces together with intracellular genes required for such associations. Using this method, I identify IGF2R as a binding partner for the R2 subunit of GABAB receptors, providing a mechanism for the internalisation and regulation of GABAB receptor signalling. The results here demonstrate that this single approach can identify the molecular nature and cell biology of surface receptors without the need to make any prior assumptions regarding their biochemical properties.

Les biosenseurs sont des dispositifs analytiques utilisés pour la détection de reconnaissance moléculaire. Ils consistent en un élément biologique immobilisé en contact intime avec un transducteur approprié qui convertit un signal biochimique en un signal électrique quantifiable. Leur principe est basé sur la reconnaissance d'une ou plusieurs molécules d'intérêt en solution (le ligand), par un composant biologique (le récepteur) étroitement lié au substrat transducteur. Le senseur réagit aux interactions récepteur-ligand et produit un signal mesurable, généralement proportionnel à la concentration du ligand fixé. Les biosenseurs sont déjà utilisés dans beaucoup de domaines différents, notamment dans le domaine médical (diagnostique et thérapeutique), le contrôle de l’environnement, et l’analyse et le monitoring de processus biotechnologiques. <p><p>La recherche concerne la mise au point d’un nouveau type de biosenseurs polyvalents à haute performance. Ces senseurs utilisent un élément de transduction optique dont la surface a été fonctionnalisée en vue de permettre la détection sélective d'interactions récepteur-ligand ainsi que le dosage des molécules fixées aux récepteurs. La technique utilisée pour la détection et le dosage est celle de la Spectroscopie ATR-FTIR (Spectroscopie Infra Rouge à Transformée de Fourrier en Réflexion Total Atténuée). Le système permet la détection directe, en temps réel, et sans marquage des molécules ciblées. La spectroscopie ATR-FTIR fournit une analyse des molécules sur base de leur empreinte spectrale infra rouge (IR) caractéristique, ce qui offre une mine d'informations pour identifier les ligands. Ce nouveau système de biosenseur, appelé BIA-ATR (Biospecific Interaction Analysis – Attenuated Total Reflection) est original et offre des avantages majeurs par rapport à la plus part des biosenseurs commercialement disponibles. Il fournit à l’utilisateur le spectre IR entier du ligand étudié, permettant non seulement le dosage quantitatif de ce dernier, mais aussi d’identifier sa nature intrinsèque. Un autre avantage est sa grande sensibilité ;le senseur BIA-ATR peut détecter la fixation de petites molécules et dans certains cas, aussi les réactions chimiques associées. <p><p>Le potentiel de cette nouvelle technologie de senseur est évalué dans ce travail par son application à plusieurs systèmes d’intérêt biologique et médical :la détection de protéines en milieux complexes, appliquée à la détection du Facteur VIII de coagulation du sang impliqué dans l’hémophilie de type A ;la fixation d’une petite molécule, le phosphate (phosphorylation), sur l’ATPase gastrique, un récepteur protéique de grande taille responsable de la sécrétion d’acide dans l’estomac et la détection et dosage d’un antibiotique, la vancomycine, utilisé en soins intensifs hospitaliers dans les cas d’infections bactériennes sévères à Staphylocoques dorés.<p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Notch receptors and ligands are single-pass transmembrane proteins which play important roles in cell-cell communication. Notch in ‘harmony’ with other signaling pathways regulate the entire diversity of metazoan life (Artavanis-Tsakonas & Muskavitch, 2010). These signaling pathways also play key roles in regulatingseveral developmental processes. Given the importance of Notch signaling in various developmental decisions, it is not surprising that aberrant gain or loss-of-function of Notch pathway leads to several human diseases including cancer (Ranganathan et al, 2011). Notch signaling has also been implicated in various human cancers, most notably in T-cell acute lymphoblastic leukemia (T-ALL) (Weng et al, 2004). In view of the importance of Notch signaling in cancers, therapeutic molecules targeting this pathway are making their way into clinical trials (Rizzo et al, 2008). This underscores the importance of understanding the mechanism of Notch receptor activation in normal and patho-physiological conditions. In this thesis, antibodies against different domains of human Notch1 receptor have been used as tools to understand the mechanism of receptor activation. This work has provided insights into the role of Notch1 extracellular domain in ligand-dependent receptor activation. Further, the mechanism of ligand-independent receptor activation in T-ALL associated mutant Notch1 has also been investigated. This understanding of ligand-dependent and independent receptor activation facilitated development of mechanistic inhibitors of Notch signaling for therapeutic targeting of the cancer stem cells (CSCs) across the pectrum of cancers. The thesis is divived into two parts. Part-I focuses on understanding the role of Notch1 extracellular domain in receptor-ligand interactions using antibodies as a tool. In part-II, implications of these antibodies in therapeutic targeting of CSCs has been investigated. Part-I Unfolding the Mechanism of Notch1 Receptor Activation The extracellular domain of Notch1 receptor consists of 36 EGF-like repeats that contribute to ligand binding (Kopan & Ilagan, 2009). Despite extensive studies on the downstream consequences of Notch signaling, the initial events of ligandreceptor interactions have not been clearly elucidated. In the absence of structural insights into the receptor-ligand interactions, it was important to decipher the roles of various receptor domains in ligand-binding and consequent signaling. In this study, antibodies have been employed as tools for in-depth analyses of Notch receptorligand, interactions. Studies in Drosophila Notch receptor suggest that EGF-like repeats 11-12 are necessary and sufficient for ligand binding (Rebay et al, 1991). However, the role of these repeats in human Notch1 receptor-ligand interaction(s) was not clearly elucidated. Antibodies were generated against Notch1 EGF-like repeats 11-15. Further, these antibodies were characterized for their specificity for Notch1 receptor in various ligand-binding and signaling assays. The results suggest that the monoclonal antibodies (MAbs) against EGF-like repeats 11-12 were more potent inhibitors of ligand-binding compared to the antibodies against EGF-like repeats 13-15. As a part of these investigations, the Notch ligands Jagged1 and Jagged2, Delta-like1 and Delta-like4 were purified and characterized in various assays. Ability of these ligands to interact with Notch1 EGF-like repeat 11-15 was determined using Surface Plasmon Resonance. The Jagged family of ligands demonstrated higher affinity for this recept or fragment when compared to the Delta family of ligands. The relatively low affinities (μM) of all the ligands suggested possibile involvement of other EGF-like repeats in ligand-binding. This was further investigated using antibodies against other EGF-like repeats of Notch1. In Drosophila Notch EGF-like repeats 24-29 have been implicated in the ligand-dependent gain-of-function phenotype, suggesting a plausible involvement of this region in receptor activation (Pei & Baker, 2008). Therefore, role of human Notch1 EGF-like repeats 21-30 in ligand-binding and signaling was investigated. These EGF-like repeats demonstrated specific interaction with the ligand-binding domain (EGF-like repeats 11-15). This suggested that in the absence of the ligand, these inter-domain interactions keep the receptor in an auto-inhibited conformation. Further, ligand binding to EGF-like repeats 11-15 dissociated pre-formed interdomain interactions. These results suggested that, the binding of ligand to EGF-like repeat 11-12 overcomes the negative constraint imposed by the intra-domain interactions which might lead to receptor activation. Next, to understand the role of EGF-like repeats 21-30 in ligand binding, polyclonal antibodies were generated against the same and extensively characterized in various solid-phase and cell-based assays. These antibodies demonstrated partial inhibition of ligand-binding. Further, using immunoaffinity purified antibodies it was demonstrated that antibodies against EGF-like repeats 25-26 were most potent inhibitors of ligand-binding compared to antibodies against EGF-like repeats 21-24 and 27-30. These results provided novel insights into Notch1 receptor activation. The model proposed on the basis of these results suggested that ligand-binding to EGF-like repeats 11-12 competes with the inter-domain interaction, in turn dissociating EGF-like repeats 21-30 from the ligandbinding domain. It emerged that this altered conformation of the receptor creates a secondary ligand-binding site at EFG-like repeats 25-26. Overall these results provided novel insight into the mechanism of Notch receptor-ligand interaction(s). Part-II Implication in Cancer Stem Cell Targeting Recent studies have suggested existence of the CSC population in various cancers (Clevers, 2011). Notch signaling plays an important role in maintenance of these CSCs (Pannuti et al, 2010). Thus, targeting Notch signaling may provide a potential therapeutic tool for CSC targeting. Several studies have indicated that Notch1 receptor and ligands are overexpressed in breast cancer cells compared to the normal breast epithelium (Mittal et al, 2009; Reedijk et al, 2005; Reedijk et al, 2008). Moreover, it has been suggested that Notch1 signaling plays a key role in breast carcinogenesis (Stylianou et al, 2006). Monoclonal antibodies (MAbs) were used as mechanistic inhibitors of aberrant Notch1 signaling for therapeutic targeting of CSCs. One such antibody, MAb 602.101, against Notch1 ligand-binding domain (EGF-like repeat 11-12) inhibited proliferation and depleted breast CSCs. This MAb also modulated genes associated with stemness and epithelial to mesenchymal transition (EMT). Furthermore, MAb 602.101 irreversibly inhibited the sphere-forming potential of breast cancer cells by modulating long-term self renewing capacity of breast CSCs. Inhibition of Notch1 signaling by the MAb also depleted the chemoresistant CD44Hi/CD24Low sub-population in breast cancer cells. Interestingly, antibody treatment led to elevated expression of genes associated with myoepithelial lineage, which suggested that inhibition of Notch1 signaling might induce a differentiation program leading to reduction in the CSC population. This study demonstrated the importance of Notch1 signaling in CSCs and effectiveness of antibodies as a tool for specific targeting of individual Notch receptors in cancer therapeutics. While aberrant expression of receptors and ligands leads to breast cancer (Reedijk et al, 2005), gain-of-function mutations are associated with 40-50% of TALL\ patients (Weng et al, 2004). These mutations lead to ligand-independent receptor activation (Malecki et al, 2006). Despite several attempts of successful antibodymediated therapeutic targeting of Notch1 (Aste-Amézaga et al, 2010; Wu et al, 2010), specific antibodies recognizing T-ALL associated mutant Notch1 remains elusive. Using homology modeling, the mutation induced conformational change in T-ALL associated mutant Notch1 was predicted. These results suggested that mutation led to conformational changes in the Notch1 negative regulatory region (NRR) This conformation change might result in the constitutive activation of Notch1 signaling leading to pathogenesis. Next, MAbs were generated against the wild-type Notch1 NRR and characterized in flow-cytometry based assays for identification of conformation specific antibodies. These antibodies were classified as either wild-type specific, mutant specific or unbiased to receptor conformations. One such mutant specific MAb 604.107 demonstrated higher binding to mutant Notch1 in flowcytometer and SPR based experiments. This MAb also demonstrated specific inhibition of T-ALL associated mutant Notch1 signaling without affecting the wildtype signaling. Moreover, antibody treatment also inhibited proliferation and depleted leukemia initiating sub-population in patient derived T-ALL cells. Taken together, this study provides a novel tool for specific targeting of mutant Notch1 receptors in TALL. CSCs are inherently chemo-resistant and lead to tumor relapse (Chen et al, 2012). Recent studies have demonstrated a strong correlation between Notch1 signaling in lung CSCs and chemotherapy resistance (Hassan et al, 2013). In this study, Notch1 heterogeneity in solid tumors viz. breast and colon cancers was investigated. Using the antibodies generated previously in this study, Notch1High and Notch1Low sub-populations from MDA-MB-231 (breast cancer) and HCT-116 (colon cancer) cell lines were flow-sorted. It was demonstrated that the Notch1High subpopulation represented the sphere-forming CSCs in breast and colon cancer. The Notch1High sub-population also demonstrated chemo-resistant properties and expressed higher level of EMT and stemness markers. These results suggested explicit involvement of Notch1 signaling in EMT and maintenance of CSCs subpopulation in these cancers. The anti-Notch1 MAb also inhibited proliferation of the chemo-resistant Notch1High sub-population. Further, treatment with MAb inhibited expression of ABCC1 transporters in these drug-resistant cells leading to augmentation of chemotherapeutic response. Using mouse xenograft assays, it was demonstrated that Notch1 signaling plays an important role in the maintenacne of tumor-initiating sub-population in breast and colon cancer cells. Prior exposure of breast and colon cancer cells to MAb inhibited the tumor forming potential of these cells in xenotransplantation assays. Treatment with MAb alone or in combination with chemotherapy led to regression of pre-formed tumors in breast and colon xenograft models. These results demonstrated existence of Notch1 heterogeneity in breast and colon cancer cells and emphasised the importance of targeting Notch1 signaling to overcome drug-resistance in these cancers. The results described above have provided important insights into Notch1 receptor activation and this understanding was translated into therapeutic targeting of CSCs. This “proof-of-principle” demonstration has significant mechanistic and applied implications in Notch and cancer biology.