Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.794738
Title: Identification of novel anti-RSV and antienterovirus inhibitors by computer-aided drug design
Author: Manganaro, Roberto
ISNI:       0000 0004 8500 8051
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2019
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Abstract:
Respiratory Syncytial Virus (RSV), which is the principal etiological cause of LRTIs (Low Respiratory Tract Infections) worldwide, and the virus members of the enterovirus genus, causing a wide range of diseases, ranging from enteric or respiratory infections to handfoot- and-mouth disease and acute flaccid paralysis, are associated with severe treats for public health. Currently, there are no effective small-molecule antiviral on the market for the treatment or prevention of these viral infections. In the first part of the project about RSV, the N and F proteins were chosen as targets for the identification of new anti-RSV agents. On the RSV N protein, different computer-aided techniques were used for structure-based virtual screenings, of commercially available drug-like compounds. The two most potent hits were chosen as a starting point for further investigations. A series of analogues were synthesised and evaluated for anti-RSV activity in a virus-cell-based assay. Computer-aided techniques were also used for the rational -helix mimics, able to inhibit the protein-protein interactions between the trimeric inner coiled- -helixes of the F protein. The most promising compound and a series of analogues were synthesised and evaluated for their anti-RSV activities in a virus-cell-based assay. For the second part of the project on enterovirus, the highly conserved 2C protein among the enterovirus species was investigated. Starting from fluoxetine, which has been identified to inhibit viral replication by targeting 2C protein, and the new resolved EVA 71 2C crystal structure was used to investigate and to elucidate the binding mechanism of fluoxetine, using molecular modelling methodologies. The gained data were used to design, synthesise and evaluate new antiviral agents. Also, different molecular modelling techniques were used to perform a virtual screening in order to identify new potential inhibitors of the ATPase pocket of the 2C protein.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.794738  DOI: Not available
Keywords: Q Science (General)
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