| Titre : | "REPURPOSING ANTIPSYCHOTIC DRUG HALOPERIDOL FOR CANCER THERAPY: IN SILICO AND SYNTHESIS INVESTIGATION " | | Type de document : | thèse | | Auteurs : | EL GUENNOUNI KAOUTAR, Auteur | | Année de publication : | 2024 | | Langues : | Anglais (eng) | | Mots-clés : | cancer signaling pathways drug repurposing Haloperidol cancer voies de signalisation réorientation des médicaments Halopéridol السرطان مسارات الإشارات إعادة توجيه الدواء هالوبيريدول | | Résumé : | Cancer remains a leading cause of mortality globally, necessitating the development of novel therapeutic approaches and effective medications. Drug development is a lengthy, complex, and costly process. Consequently, drug repurposing has emerged as a promising alternative, allowing for faster and more cost-effective transitions into phase 2 or 3 clinical trials due to previously established safety profiles. Antipsychotic drugs, such as Haloperidol, have shown potential anti-cancer properties. This study aimed to identify the potential targets of haloperidol through in silico methods and to synthesize Haloperidol for future experimental validation. Target prediction using SwissTargetPrediction indicated that 20% of the target classes were kinases, which play critical roles in cell signaling pathways and are implicated in cancer initiation and progression. Ten relevant protein targets were selected for further investigation: PI3K, PIM-1, ALK, Rho-associated protein, MDM2, JAK1, MEK, MNK, CDK9, and IGF1-R. Molecular docking studies revealed that haloperidol exhibited significant inhibitory potency against JAK1, Rho-associated proteins, and CDK9, with clustering analysis showing structural similarity to MDM2 inhibitors. Machine Learning-based QSAR predicted lower IC50 values for haloperidol, particularly against JAK1, compared to other models. Analogues demonstrated even lower IC50 values compared to Haloperidol. The most promising targets (JAK1, MDM2, and ROCK) were subjected to molecular dynamics simulations, which confirmed stable complex formation between Haloperidol and JAK1, though not outperforming the reference inhibitor, peficitinib. Haloperidol was synthesized for subsequent experimental validation to confirm these findings. | | Numéro (Thèse ou Mémoire) : | MM0212024 | | Président : | ELJAOUDI Rachid | | Directeur : | OUADGHIRI Mouna | | Juge : | KANDOUSSI Ilham | | Juge : | BOURICHA El Mehdi | | Juge : | RAMLI YOUSSEF |
"REPURPOSING ANTIPSYCHOTIC DRUG HALOPERIDOL FOR CANCER THERAPY: IN SILICO AND SYNTHESIS INVESTIGATION " [thèse] / EL GUENNOUNI KAOUTAR, Auteur . - 2024. Langues : Anglais ( eng) | Mots-clés : | cancer signaling pathways drug repurposing Haloperidol cancer voies de signalisation réorientation des médicaments Halopéridol السرطان مسارات الإشارات إعادة توجيه الدواء هالوبيريدول | | Résumé : | Cancer remains a leading cause of mortality globally, necessitating the development of novel therapeutic approaches and effective medications. Drug development is a lengthy, complex, and costly process. Consequently, drug repurposing has emerged as a promising alternative, allowing for faster and more cost-effective transitions into phase 2 or 3 clinical trials due to previously established safety profiles. Antipsychotic drugs, such as Haloperidol, have shown potential anti-cancer properties. This study aimed to identify the potential targets of haloperidol through in silico methods and to synthesize Haloperidol for future experimental validation. Target prediction using SwissTargetPrediction indicated that 20% of the target classes were kinases, which play critical roles in cell signaling pathways and are implicated in cancer initiation and progression. Ten relevant protein targets were selected for further investigation: PI3K, PIM-1, ALK, Rho-associated protein, MDM2, JAK1, MEK, MNK, CDK9, and IGF1-R. Molecular docking studies revealed that haloperidol exhibited significant inhibitory potency against JAK1, Rho-associated proteins, and CDK9, with clustering analysis showing structural similarity to MDM2 inhibitors. Machine Learning-based QSAR predicted lower IC50 values for haloperidol, particularly against JAK1, compared to other models. Analogues demonstrated even lower IC50 values compared to Haloperidol. The most promising targets (JAK1, MDM2, and ROCK) were subjected to molecular dynamics simulations, which confirmed stable complex formation between Haloperidol and JAK1, though not outperforming the reference inhibitor, peficitinib. Haloperidol was synthesized for subsequent experimental validation to confirm these findings. | | Numéro (Thèse ou Mémoire) : | MM0212024 | | Président : | ELJAOUDI Rachid | | Directeur : | OUADGHIRI Mouna | | Juge : | KANDOUSSI Ilham | | Juge : | BOURICHA El Mehdi | | Juge : | RAMLI YOUSSEF |
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