Literature DB >> 26616092

Dynamics-Based Discovery of Allosteric Inhibitors: Selection of New Ligands for the C-terminal Domain of Hsp90.

Giulia Morra1, Marco A C Neves1, Christopher J Plescia1, Shinji Tsustsumi1, Len Neckers1, Gennady Verkhivker1, Dario C Altieri1, Giorgio Colombo1.   

Abstract

The study of allosteric functional modulation in dynamic proteins is attracting increasing attention. In particular, the discovery of new allosteric sites may generate novel opportunities and strategies for drug development, overcoming the limits of classical active-site oriented drug design. In this paper, we report on the results of a novel, ab initio, fully computational approach for the discovery of allosteric inhibitors based on the physical characterization of signal propagation mechanisms in proteins and apply it to the important molecular chaperone Hsp90. We first characterize the allosteric "hot spots" involved in interdomain communication pathways from the nucleotide-binding site in the N-domain to the distal C-domain. On this basis, we develop dynamic pharmacophore models to screen drug libraries in the search for small molecules with the functional and conformational properties necessary to bind these "hot spot" allosteric sites. Experimental tests show that the selected moelcules bind the Hsp90 C-domain, exhibit antiproliferative activity in different tumor cell lines, while not affecting proliferation of normal human cells, destabilize Hsp90 client proteins, and disrupt association with several cochaperones known to bind the N- and M-domains of Hsp90. These results prove that the hits alter Hsp90 function by affecting its conformational dynamics and recognition properties through an allosteric mechanism. These findings provide us with new insights on the discovery and development of new allosteric inhibitors that are active on important cellular pathways through computational biology. Though based on the specific case of Hsp90, our approach is general and can readily be extended to other target proteins and pathways.

Entities:  

Year:  2010        PMID: 26616092      PMCID: PMC7575213          DOI: 10.1021/ct100334n

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


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