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020			_aTHE0009443 (Local) _qHardback
040			_aUMP _beng _cUMP _erda
090			_aFSTI .M53 2022 r Thesis
100	1		_aMiah Roney, _eauthor.
245	1	0	_aIdentification of usnic acid derivatives as new antiviral agents via virtual screening on dengue, influenza A and avian influenza A / _cMiah Roney
264		1	_aPahang : _bUMP, _c2022
264		4	_c© 2022
300			_a318 pages : _bIllustration ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
337			_2rdamedia _acomputer
338			_2rdacarrier _avolume
338			_2rdacarrier _acomputer disc
347			_2rda _atext file _bPDF
500			_aFaculty of Industrial Sciences and Technology
502			_aThesis (Master of Science) -- Universiti Malaysia Pahang – 2022
504			_aIncludes bibliographical references
520	3		_aEmerging viral infections continue to pose a significant threat to global public health in recent years. Viral diseases such as Dengue, Influenza (H1N1), and Avian Influenza have caused a significant challenge to the healthcare systems, economic growth, and development. Still now, there are no drugs available to combat the DENV and Avian Influenza A viruses. On the other hand, only two drugs have been developed against Influenza A virus based on the neuraminidase enzyme but need to annual updating because these drugs ineffective against the new subtype of Influenza A. Even though new antiviral drugs have been developed and approved annually, the cost and environmental issues remain the main challenges for scientists. The new innovative approaches involving computational technology need to be employed in drug development and discovery. Thus, the studies aimed to discover new potential antiviral lead compounds from usnic acid derivatives in-house database through virtual screening via various in silico approaches such as pharmacophore filtering, molecular docking screening, and pharmacokinetic prediction. There were three main parts covered; Part 1: Discovery of anti-DENV’s lead compound, Part 2: Discovery of anti-Influenza A’s lead compound and Part 3: Discovery of anti-avian Influenza A’s lead compound. Four hundred twenty-eight usnic acid derivatives as in-house database was generated by retrieved from the various literature sources. The use of usnic acid derivatives is due to their incredible antiviral activities. According to current research, usnic acid has strong larvicidal properties toward Aedes aegypti. The combination of ligand-based and structure-based virtual screening model was built leading by pharmacophore filtering, molecular docking screening followed by pharmacokinetic predictions including drug-likeness and CYP2D6 filtering to afford the lead compounds for each target (dengue, Influenza A and avian Influenza A). The in-house usnic acid derivatives database was screened using the selected pharmacophore models to afford one hundred sixteen compounds for novel DENV-3 NS5 protease, twenty-three compounds for Influenza A, and twenty-one compounds for Avian Influenza A inhibitors. In the next virtual screening stage, molecular docking and interaction analysis indicated that forty-one DENV compounds, four Influenza compounds, and five Avian Influenza compounds could plausibly be active against the targets. Further filtering by ADME prediction tools and drug-likeness prediction of forty-one, four and five compounds from DENV, Influenza and Avian Influenza, respectively, resulted in seven hit compounds for DENV, two hit compounds for Influenza and two compounds for Avian Influenza virus, respectively. The lead molecule, called compound-362, compound-4, and compound-5, was discovered after screening the hit compounds against DENV, Influenza, and Avian Influenza utilising the cytochrome P450 enzyme. To corroborate the durability of docked complexes and the binding conformation established during docking testing, a molecular dynamic (MD) simulation of lead compounds 362, 4 and 5 was performed. Ultimately, the lead compounds 362, 4 and 5 discovered for DENV, Influenza A and Avian Influenza A, respectively, exhibited a high pharmacophore fit value, string binding affinity, excellent pharmacokinetics, and drug-like characteristics in general. Thus, it proved that the virtual screening model employed in this study was reliable.
610	2	0	_aFaculty of Industrial Sciences and Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aThesis _xDissertations
942			_2lcc _cTHESIS