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Cheminformatics approach to identify bioactive inhibitors against type I dehydroquinase (DHQ1) enzyme of typhoidal Salmonella typhi.

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dc.contributor.author Mariyam, Safa
dc.date.accessioned 2024-01-04T07:44:41Z
dc.date.available 2024-01-04T07:44:41Z
dc.date.issued 2023
dc.identifier.other 330472
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/41476
dc.description Supervisor : : Dr. Saadia Andleeb en_US
dc.description.abstract The 21st century's foremost public health concern is the widespread occurrence of antibiotic resistance. The chronic carriage of Salmonella typhi. is the primary source of enteric fever transmission and perforation of resistant typhoid especially among children in developing countries. However, the paradigm to ‘disarm’ the bacteria instead of killing it directly can augment our dwindling antimicrobial arsenal with limited resistance. In this context, the Shikimate pathway exclusive to bacteria is a desirable target for the generation of antibacterial therapies. The enzyme 3-dehydroquinate dehydratase type 1 (DHQ1) in Salmonella typhi. is a validated and crucial therapeutic target because of its key role in the bacterial aromatic amino acid production pathway. The goal of the current investigation is to ascertain which bioactive substances have inhibitory action against the DHQ1 enzyme. The protein data bank (PDB) provided the protein's three dimensional structure. To identify potential anti-typhoidal compounds, structure-based virtual screening (SBVS) was performed using 551 natural and anti- infection compounds from ApexBio database. About 206 compounds out of 551 were filtered based on physicochemical properties and Lipinki’s rule and went through the molecular docking process. The top ten ligands (Cabotegravir, Imatinib, Prulifloxacin, Limonin, Silibinin, Atovaquone, Betamethasone Valerate GSK1324726A, Isavuconazole, and Raltegravir) were chosen based on their greatest binding affinities, which ranged from -9.8 to -9.1 (kcal/mol). Moreover, PASS analysis was used to prioritise the best inhibitory chemical by performing ADMET analysis, bioactivity prediction, and pharmacokinetic property prediction. Additionally, RMSF values (root mean square fluctuation) from molecular dynamic modelling demonstrated that the docked protein-ligand combination was stable. Experiments conducted in vitro and in vivo will also help to clarify the safe and effective therapeutic role of the substances that are prioritized. en_US
dc.language.iso en en_US
dc.publisher Atta Ur Rahman School of Applied Biosciences (ASAB), NUST en_US
dc.subject Typhoid, anti-typhoidal compounds, Structure-based virtual screening (SBVS), PASS analysis, ADMET analysis, molecular dynamic modelling en_US
dc.title Cheminformatics approach to identify bioactive inhibitors against type I dehydroquinase (DHQ1) enzyme of typhoidal Salmonella typhi. en_US
dc.type Thesis en_US


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