Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/58745
Title: Design and identification of novel Androgen Receptor inhibitors using the experimental small Androgen Receptor modulators (S)-11 and (R)-9, and (R)-bicalutamide scaffolds as lead molecules
Authors: Neykova, Simona
Keywords: Prostate -- Cancer
Prostate -- Cancer -- Hormone therapy
Androgens -- Receptors
Antiandrogens
Issue Date: 2019
Citation: Neykova, S. (2019). Design and identification of novel Androgen Receptor inhibitors using the experimental small Androgen Receptor modulators (S)-11 and (R)-9, and (R)-bicalutamide scaffolds as lead molecules (Master's dissertation).
Abstract: Current pharmacological treatment of prostate cancer centres around Androgen Receptor (AR) inhibition or Androgen deprivation. Eventually the AR mutates and becomes resistant to treatment. The aim of this study was to identify novel structures capable of mutant AR inhibition. Two drug design approaches – Virtual Screening (VS) and de novo drug design were adopted. Evidence in literature has shown that novel molecules (S)-11 and (R)-9 are capable of mutant AR inhibition, so they were chosen as leads to probe the mutant AR for this study. PDB crystallographic deposition with ID 1Z95[3] describing the holo R-bicalutamide:AR complex was used as a template. Sybyl®-X, X-Score®, LigandScout®, ZINCPharmer®, BIOVIA Discovery Studio Visualiser® 2016 and LigBuilder®v1.2 were the software tools used to probe the AR mutant and to screen for molecules capable of its inhibition. 905 hit molecules were obtained from VS. They were sorted according to their affinity for the mutant AR in the following order: by highest Total Score, followed by highest CScore and then by highest Global CScore. The six molecules with the highest Total Score were selected. 348 novel molecules were generated from 3 seed structures using de novo drug design. The molecules with the highest binding affinity from each seed group results were chosen and filtered for Lipinski Rules compliance. The molecules obtained though VS are more structurally diverse compared to the de novo molecules. The optimal molecular structures from both approaches will be proposed for computational validation and for in vivo signalling assays.
Description: M.PHARM.
URI: https://www.um.edu.mt/library/oar/handle/123456789/58745
Appears in Collections:Dissertations - FacM&S - 2019
Dissertations - FacM&SPha - 2019

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