| Titre : | COMPUTATIONAL MODELING AND DRUG DISCOVERY IN THE CONTEXT OF HOST-PATHOGEN INTERACTIONS: APPLICATION TO SARS-COV-2 AND AGGREGATIBACTER ACTINOMYCETEMCOMITANS | | Type de document : | thèse | | Auteurs : | HAKMI MOHAMMED, Auteur | | Année de publication : | 2023 | | Langues : | Anglais (eng) | | Mots-clés : | Host Pathogen Interaction Computational Modeling Molecular Dynamics Molecular Docking SARS-CoV-2 Aggregatibacter actinomycetemcomitans Hôte pathogène interaction modélisation informatique dynamique moléculaire amarrage moléculaire SARS-CoV-2 Aggregatibacter actinomycetemcomitans SARS-CoV-المضيف الممرض التفاعل النمذجة المعلوماتية، الديناميكيات الجزيئية الإرساء الجزيئي 2 Aggregatibacter actinomycetemcomitans | | Résumé : | The study of host-pathogen interactions (HPIs) is crucial for understanding the mechanisms of infectious diseases and developing effective treatments. However, experimental methods for studying HPIs can be timeconsuming and yield limited results. As a result, computational methods have become an impressive tool for HPI prediction and modeling, given recent technological advances and the availability of vast amounts of genomic data. The aim of this thesis is to investigate proteomic interactions that offer insight into the critical molecular processes involved in infection mechanisms. Specifically, we focused on protein-protein interactions between the host and the pathogen, which present significant challenges related to infectious diseases and drug development. Using computational methods, we explored crucial drug targets from two human pathogens : SARS-CoV-2 and Aggregatibacter actinomycetemcomitans. For SARS-CoV-2, we examined two key proteins: the spike protein and the main protease. We investigated the interaction between the spike protein and the human ACE2 receptor and proposed novel compounds that disrupt this interaction and prevent the virus from infecting host cells. Additionally, we examined the use of existing antiviral agents to block the main protease's catalytic site and prevent its interaction with viral and possibly host proteins. For Aggregatibacter actinomycetemcomitans, we employed computational modeling and simulation to construct a high-resolution atomic model of its major virulence factor, the leukotoxin, and assessed its potential as a drug target. Furthermore, we established a computational model of the interaction between leukotoxin and its receptor LFA1, which could serve as a starting point for inhibitor design. | | Numéro (Thèse ou Mémoire) : | D0112023 | | Président : | KETTANI Anass | | Directeur : | IBRAHIMI Azeddine ; Jaouad El HARTI | | Juge : | EL JAOUDI Rachid | | Juge : | Khalil HAMMANI | | Juge : | Samira SERRAGUI ; Oumkeltoum ENNIBI |
COMPUTATIONAL MODELING AND DRUG DISCOVERY IN THE CONTEXT OF HOST-PATHOGEN INTERACTIONS: APPLICATION TO SARS-COV-2 AND AGGREGATIBACTER ACTINOMYCETEMCOMITANS [thèse] / HAKMI MOHAMMED, Auteur . - 2023. Langues : Anglais ( eng) | Mots-clés : | Host Pathogen Interaction Computational Modeling Molecular Dynamics Molecular Docking SARS-CoV-2 Aggregatibacter actinomycetemcomitans Hôte pathogène interaction modélisation informatique dynamique moléculaire amarrage moléculaire SARS-CoV-2 Aggregatibacter actinomycetemcomitans SARS-CoV-المضيف الممرض التفاعل النمذجة المعلوماتية، الديناميكيات الجزيئية الإرساء الجزيئي 2 Aggregatibacter actinomycetemcomitans | | Résumé : | The study of host-pathogen interactions (HPIs) is crucial for understanding the mechanisms of infectious diseases and developing effective treatments. However, experimental methods for studying HPIs can be timeconsuming and yield limited results. As a result, computational methods have become an impressive tool for HPI prediction and modeling, given recent technological advances and the availability of vast amounts of genomic data. The aim of this thesis is to investigate proteomic interactions that offer insight into the critical molecular processes involved in infection mechanisms. Specifically, we focused on protein-protein interactions between the host and the pathogen, which present significant challenges related to infectious diseases and drug development. Using computational methods, we explored crucial drug targets from two human pathogens : SARS-CoV-2 and Aggregatibacter actinomycetemcomitans. For SARS-CoV-2, we examined two key proteins: the spike protein and the main protease. We investigated the interaction between the spike protein and the human ACE2 receptor and proposed novel compounds that disrupt this interaction and prevent the virus from infecting host cells. Additionally, we examined the use of existing antiviral agents to block the main protease's catalytic site and prevent its interaction with viral and possibly host proteins. For Aggregatibacter actinomycetemcomitans, we employed computational modeling and simulation to construct a high-resolution atomic model of its major virulence factor, the leukotoxin, and assessed its potential as a drug target. Furthermore, we established a computational model of the interaction between leukotoxin and its receptor LFA1, which could serve as a starting point for inhibitor design. | | Numéro (Thèse ou Mémoire) : | D0112023 | | Président : | KETTANI Anass | | Directeur : | IBRAHIMI Azeddine ; Jaouad El HARTI | | Juge : | EL JAOUDI Rachid | | Juge : | Khalil HAMMANI | | Juge : | Samira SERRAGUI ; Oumkeltoum ENNIBI |
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