Development and application of ligand-based computational methods for de-novo drug design and virtual screening

Ligand-based computational drug discovery (LB-CADD) methods have been used widely over the last several decades to aid medicinal chemistry campaigns via virtual high-throughput screening (vHTS) and de-novo molecular design. A new de-novo drug design algorithm, BCL::EvoGen, based on a stochastic sear...

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Main Author: Geanes, Alexander Richard
Other Authors: Jens Meiler
Format: Others
Language:en
Published: VANDERBILT 2016
Subjects:
Online Access:http://etd.library.vanderbilt.edu/available/etd-11172016-133216/
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spelling ndltd-VANDERBILT-oai-VANDERBILTETD-etd-11172016-1332162016-11-19T05:27:14Z Development and application of ligand-based computational methods for de-novo drug design and virtual screening Geanes, Alexander Richard Chemistry Ligand-based computational drug discovery (LB-CADD) methods have been used widely over the last several decades to aid medicinal chemistry campaigns via virtual high-throughput screening (vHTS) and de-novo molecular design. A new de-novo drug design algorithm, BCL::EvoGen, based on a stochastic search algorithm was implemented within the BioChemical Library developed at Vanderbilt University. The EvoGen algorithm leverages reaction-based structure modification methods to iteratively build chemical structures, and ligand-based molecule scoring functions to guide molecular design. Results indicate that the EvoGen algorithm is capable of designing high-scoring molecules with novel and chemically reasonable structures. In a second study, LB-CADD models were used to prioritize a subset of a compound library the discovery of muscarinic acetylcholine receptor M5 negative allosteric modulators. An orthosteric antagonist VU0549108 (VU108) was discovered which exhibited an M5 IC50 of 5.23 uM and moderate selectivity across other muscarinic receptors. In addition, VU108 contains a novel chemical scaffold not previously associated with muscarinic receptor ligands. Jens Meiler Craig Lindsley VANDERBILT 2016-11-18 text application/pdf http://etd.library.vanderbilt.edu/available/etd-11172016-133216/ http://etd.library.vanderbilt.edu/available/etd-11172016-133216/ en unrestricted I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.
collection NDLTD
language en
format Others
sources NDLTD
topic Chemistry
spellingShingle Chemistry
Geanes, Alexander Richard
Development and application of ligand-based computational methods for de-novo drug design and virtual screening
description Ligand-based computational drug discovery (LB-CADD) methods have been used widely over the last several decades to aid medicinal chemistry campaigns via virtual high-throughput screening (vHTS) and de-novo molecular design. A new de-novo drug design algorithm, BCL::EvoGen, based on a stochastic search algorithm was implemented within the BioChemical Library developed at Vanderbilt University. The EvoGen algorithm leverages reaction-based structure modification methods to iteratively build chemical structures, and ligand-based molecule scoring functions to guide molecular design. Results indicate that the EvoGen algorithm is capable of designing high-scoring molecules with novel and chemically reasonable structures. In a second study, LB-CADD models were used to prioritize a subset of a compound library the discovery of muscarinic acetylcholine receptor M5 negative allosteric modulators. An orthosteric antagonist VU0549108 (VU108) was discovered which exhibited an M5 IC50 of 5.23 uM and moderate selectivity across other muscarinic receptors. In addition, VU108 contains a novel chemical scaffold not previously associated with muscarinic receptor ligands.
author2 Jens Meiler
author_facet Jens Meiler
Geanes, Alexander Richard
author Geanes, Alexander Richard
author_sort Geanes, Alexander Richard
title Development and application of ligand-based computational methods for de-novo drug design and virtual screening
title_short Development and application of ligand-based computational methods for de-novo drug design and virtual screening
title_full Development and application of ligand-based computational methods for de-novo drug design and virtual screening
title_fullStr Development and application of ligand-based computational methods for de-novo drug design and virtual screening
title_full_unstemmed Development and application of ligand-based computational methods for de-novo drug design and virtual screening
title_sort development and application of ligand-based computational methods for de-novo drug design and virtual screening
publisher VANDERBILT
publishDate 2016
url http://etd.library.vanderbilt.edu/available/etd-11172016-133216/
work_keys_str_mv AT geanesalexanderrichard developmentandapplicationofligandbasedcomputationalmethodsfordenovodrugdesignandvirtualscreening
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