Show simple item record

dc.contributor.authorSarnpitak, Pakornwit
dc.contributor.authorMujumdar, Prashant
dc.contributor.authorTaylor, Paul
dc.contributor.authorCross, Megan
dc.contributor.authorCoster, Mark J
dc.contributor.authorGorse, Alain-Dominique
dc.contributor.authorKrasavin, Mikhail
dc.contributor.authorHofmann, Andreas
dc.date.accessioned2017-06-01T02:42:50Z
dc.date.available2017-06-01T02:42:50Z
dc.date.issued2015
dc.identifier.issn0734-9750
dc.identifier.doi10.1016/j.biotechadv.2015.05.006
dc.identifier.urihttp://hdl.handle.net/10072/152470
dc.description.abstractComputational docking as a means to prioritise small molecules in drug discovery projects remains a highly popular in silico screening approach. Contemporary docking approaches without experimental parametrisation can reliably differentiate active and inactive chemotypes in a protein binding site, but the absence of a correlation between the score of a predicted binding pose and the biological activity of the molecule presents a clear limitation. Several novel or improved computational approaches have been developed in the recent past to aid in screening and profiling of small-molecule ligands for drug discovery, but also more broadly in developing conceptual relationships between different protein targets by chemical probing. Among those new methodologies is a strategy known as inverse virtual screening, which involves the docking of a compound into different protein structures. In the present article, we review the different computational screening methodologies that employ docking of atomic models, and, by means of a case study, present an approach that expands the inverse virtual screening concept. By computationally screening a reasonably sized library of 1235 compounds against a panel of 48 mostly human kinases, we have been able to identify five groups of putative lead compounds with substantial diversity when compared to each other. One representative of each of the five groups was synthesised, and tested in kinase inhibition assays, yielding two compounds with micro-molar inhibition in five human kinases. This highly economic and cost-effective methodology holds great promise for drug discovery projects, especially in cases where a group of target proteins share high structural similarity in their binding sites.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherElsevier
dc.publisher.placeUnited States
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto7
dc.relation.ispartofjournalBiotechnology Advances
dc.subject.fieldofresearchMedical Parasitology
dc.subject.fieldofresearchBiological Sciences
dc.subject.fieldofresearchEngineering
dc.subject.fieldofresearchTechnology
dc.subject.fieldofresearchcode110803
dc.subject.fieldofresearchcode06
dc.subject.fieldofresearchcode09
dc.subject.fieldofresearchcode10
dc.titlePanel docking of small-molecule libraries – prospects to improve efficiency of lead compound discovery
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.versionPost-print
gro.facultyGriffith Sciences, Griffith Institute for Drug Discovery
gro.rights.copyright© 2015 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorCoster, Mark J.
gro.griffith.authorHofmann, Andreas
gro.griffith.authorKrasavin, Mikhail
gro.griffith.authorSarnpitak, Pakornwit
gro.griffith.authorMujumdar, Prashant
gro.griffith.authorCross, Megan O.
gro.griffith.authorGorse, Dominique


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record