Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7492
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dc.contributor.authorLi, Hongjianen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorChan, Ho Chanen_US
dc.contributor.authorCheung, Hei Lunen_US
dc.contributor.authorWong, Man-Honen_US
dc.date.accessioned2023-03-15T03:50:50Z-
dc.date.available2023-03-15T03:50:50Z-
dc.date.issued2014-
dc.identifier.citationProceedings of the International Conference on Information Visualisation 6902920, pp. 302-307en_US
dc.identifier.isbn978-1-4799-4103-2-
dc.identifier.issn1550-6037-
dc.identifier.issn1550-6037-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7492-
dc.description.abstractWe present iSyn, a WebGL-based tool for interactivede novo drug design. It features an evolutionary algorithm that automatically designs novel ligands with drug-like properties and synthetic feasibility using click chemistry. Isyn interfaces with our popular and fast molecular docking engine idock, remarkably reducing the evaluation and ranking time of drug candidates. Furthermore, inspired by our user friendly and high-performance WebGL visualizer iview, our iSyn also implements a tailor-made interactive visualizer to aid novel drug design. We believe iSyn can supplement the efforts of medicinal chemists in drug discovery research. To illustrate the utility of iSyn in generating novelligands ex nihilo, we designed predicted inhibitors of two important drug targets, which are RNA editing ligase 1(REL1) from T. Brucei, the etiological agent of African sleeping sickness, and cyclin-dependent kinase 2 (CDK2), a positive regulator of eukaryotic cell cycle progression. Results show that iSyn managed to significantly enhance the predicted binding affinity of the best generated ligand by more than 3 orders of magnitude in potency. Isyn is written in C++, Python, HTML5 and JavaScript. It is free and open source, available athttp://istar.cse.cuhk.edu.hk/iSyn.tgz. It has been tested successfully on both Linux and Windows.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofProceedings of the International Conference on Information Visualisationen_US
dc.titleiSyn: WebGL-Based Interactive De Novo Drug Designen_US
dc.typePeer Reviewed Journal Articleen_US
dc.identifier.doi10.1109/IV.2014.10-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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