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An international journal for chemical science
RESEARCH ARTICLE

Imaginative Order from Reasonable Chaos: Conformation-Driven Activity and Reactivity in Exploring Protein–Ligand Interactions

Alexander F. Moore A , David J. Newman A B , Shoba Ranganathan A and Fei Liu A C
+ Author Affiliations
- Author Affiliations

A Department of Molecular Sciences, Macquarie University, North Ryde, NSW 2109, Australia.

B Newman Consulting LLC, Wayne, PA 19087, USA.

C Corresponding author. Email: fei.liu@mq.edu.au

Australian Journal of Chemistry 71(12) 917-930 https://doi.org/10.1071/CH18416
Submitted: 20 August 2018  Accepted: 9 October 2018   Published: 12 November 2018

Abstract

Sir Derek Barton’s seminal work on steroid conformational analysis opened up a new era of enquiry into how the preferred conformation of any molecule could have profound effects on its physical–chemical properties and activities. Conformation-based effects on molecular activity and reactivity continue to manifest, with one key area of investigation currently focussed on conformational entropy in driving protein–ligand interactions. Carrying on from Barton’s initial insight on natural product conformational properties, new questions now address how conformational flexibility within a bioactive natural product structural framework (reasonable chaos), can be directed to confer dynamically new protein–ligand interactions beyond the basic lock–key model (imaginative order). Here we summarise our work on exploring conformational diversity from fluorinated natural product fragments, and how this approach of conformation-coupled diversity-oriented synthesis can be used to iteratively derive ligands with enhanced specificity against highly homologous protein domains. Our results demonstrate that the conformation entropic states of highly conserved protein domains differ significantly, and this conformational diversity, beyond primary sequence analysis, can be duly captured and exploited by natural-product derived ligands with complementary conformational dynamics for enhancing recognition specificity in drug lead discovery.


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