PHD Finger Protein 6 (PHF6) is a zinc finger transcriptional regulator implicated in neurodevelopmental disorders such as Börjeson–Forssman–Lehmann Syndrome (BFLS) and hematological malignancies including T-cell acute lymphoblastic leukemia (T-ALL). Its architecture, comprising two zinc-binding PHD domains and extensive intrinsically disordered regions, complicates conventional drug development yet makes PHF6 an attractive target for allosteric modulation. This thesis applies a multi-layered computational strategy to evaluate the allosteric druggability of PHF6. Structural models from crystallographic data (PDB ID: 4NN2) and AlphaFold predictions were optimized, followed by allosteric pocket identification using complementary prediction tools. Cross-validated sites were ranked by structural properties and predicted druggability. Virtual screening of ZINC, DrugBank, and Enamine libraries identified candidate ligands, whose pharmacokinetic profiles were assessed through ADME analysis to prioritize drug-like compounds. Residue interaction network analysis was then used to compare ligand-free and ligand-bound states, revealing that ligand binding reorganizes key communication hubs. Importantly, the boundary residue between structured and disordered regions gained centrality, highlighting its role in allosteric signaling. Overall, this work establishes a computational framework for exploring allosteric sites in PHF6, identifies drug-like candidate ligands, and proposes strategies to target disordered regions through structured domains, offering a foundation for future experimental validation.
PHD Finger Protein 6 (PHF6) is a zinc finger transcriptional regulator implicated in neurodevelopmental disorders such as Börjeson–Forssman–Lehmann Syndrome (BFLS) and hematological malignancies including T-cell acute lymphoblastic leukemia (T-ALL). Its architecture, comprising two zinc-binding PHD domains and extensive intrinsically disordered regions, complicates conventional drug development yet makes PHF6 an attractive target for allosteric modulation. This thesis applies a multi-layered computational strategy to evaluate the allosteric druggability of PHF6. Structural models from crystallographic data (PDB ID: 4NN2) and AlphaFold predictions were optimized, followed by allosteric pocket identification using complementary prediction tools. Cross-validated sites were ranked by structural properties and predicted druggability. Virtual screening of ZINC, DrugBank, and Enamine libraries identified candidate ligands, whose pharmacokinetic profiles were assessed through ADME analysis to prioritize drug-like compounds. Residue interaction network analysis was then used to compare ligand-free and ligand-bound states, revealing that ligand binding reorganizes key communication hubs. Importantly, the boundary residue between structured and disordered regions gained centrality, highlighting its role in allosteric signaling. Overall, this work establishes a computational framework for exploring allosteric sites in PHF6, identifies drug-like candidate ligands, and proposes strategies to target disordered regions through structured domains, offering a foundation for future experimental validation.
Virtual Screening and Allosterism Analysis of PHD finger protein 6
PEQINI, LISIA
2024/2025
Abstract
PHD Finger Protein 6 (PHF6) is a zinc finger transcriptional regulator implicated in neurodevelopmental disorders such as Börjeson–Forssman–Lehmann Syndrome (BFLS) and hematological malignancies including T-cell acute lymphoblastic leukemia (T-ALL). Its architecture, comprising two zinc-binding PHD domains and extensive intrinsically disordered regions, complicates conventional drug development yet makes PHF6 an attractive target for allosteric modulation. This thesis applies a multi-layered computational strategy to evaluate the allosteric druggability of PHF6. Structural models from crystallographic data (PDB ID: 4NN2) and AlphaFold predictions were optimized, followed by allosteric pocket identification using complementary prediction tools. Cross-validated sites were ranked by structural properties and predicted druggability. Virtual screening of ZINC, DrugBank, and Enamine libraries identified candidate ligands, whose pharmacokinetic profiles were assessed through ADME analysis to prioritize drug-like compounds. Residue interaction network analysis was then used to compare ligand-free and ligand-bound states, revealing that ligand binding reorganizes key communication hubs. Importantly, the boundary residue between structured and disordered regions gained centrality, highlighting its role in allosteric signaling. Overall, this work establishes a computational framework for exploring allosteric sites in PHF6, identifies drug-like candidate ligands, and proposes strategies to target disordered regions through structured domains, offering a foundation for future experimental validation.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/91414