Evaluation and Optimisation of in silico - Zammit, Sharon;Shoemake, Claire;Azzopardi, Lilian
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Breast cancer is defined as the uncontrolled growth of neoplastic cells in breast tissues, which can be environmentally and or hormonally induced. This project uses GW5638, a selective oestrogen receptor modulator with clinical potential in the management of tamoxifen-resistant breast cancer as lead molecule in the in silico drug design of novel antagonists. This molecule is particularly interesting due to its ability to induce a hitherto undocumented conformational change in receptor structure, delineating a new ligand binding domain (LBD) conformation in which helix 12 occupies a distinct…mehr

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Produktbeschreibung
Breast cancer is defined as the uncontrolled growth of neoplastic cells in breast tissues, which can be environmentally and or hormonally induced. This project uses GW5638, a selective oestrogen receptor modulator with clinical potential in the management of tamoxifen-resistant breast cancer as lead molecule in the in silico drug design of novel antagonists. This molecule is particularly interesting due to its ability to induce a hitherto undocumented conformational change in receptor structure, delineating a new ligand binding domain (LBD) conformation in which helix 12 occupies a distinct spatial orientation. Protein data bank crystallographic deposition 1R5K describing the holo GW5638:oestrogen receptor complex was identified and mutual affinity calculated in X-Score ® v1.3 for baseline affinity establishment. In phase 1 of the study, GW5638 was edited computationally and five seed structures were generated. Each seed sustained molecular growth using the GROW algorithm of LigBuilder ® v2 at pre-selected loci considered as non-critical to binding and clinical efficacy on the basis of SAR studies.
Autorenporträt
Sharon Zammit - Education: Bachelor of Science (Honors) in Pharmaceutical Science, University of Malta, Malta, June 2015. Master of Pharmacy, University of Malta, Malta. Masters's Thesis: Evaluation and Optimisation of in silico Designed Oestrogen Receptor Modulators for the management of breast cancer, September, 2016.