Identifying small-molecule inhibitors of protein interactions has traditionally presented a challenge for modern screening methods, despite interest stemming from the fact that such interactions comprise the underlying mechanisms for cell proliferation, differentiation, and survival. The objective of this application is to employ insights from computational methodology we have recently developed to address the distinct challenges associated with finding inhibitors of different classes of protein surface. Our central hypothesis is that exploring protein fluctuations leading to formation of surface pockets is criticl for understanding the regions of chemical space in which suitable inhibitory compounds may be found. We propose to meet our objective by pursuit of the following three specific aims: 1) Apply pocket optimization for selecting and characterizing protein targets. 2) Employ protein-ligand complementarity to build libraries enriched in protein interface inhibitors. 3) Extend these tools to allosteric inhibitors of protein interfaces. The proposed research is innovative in its ue of insight from protein fluctuations to identify binding pockets. By first confirming the ability o a target protein to form a suitable pocket and second assembling a complementary library, we collectively address the two main hurdles outlined above that have hitherto hindered identification of small molecules that directly inhibit protein-protein interactions. By combining this approach with in vitro biochemical screening, we expect to identify novel inhibitors of protei interactions involving each of three well-validated cancer targets: Bcl-xL, survivin, and b- TrCP.

Public Health Relevance

This research is expected to have an important positive impact because it will provide new insights and tools to address the distinct challenges associated with finding small-molecule inhibitors of protein interactions. This contribution is significant because protein interactions have traditionally represented challenging targets for modern screening methods, despite interest stemming from the fact that such interactions comprise the underlying mechanisms for cell proliferation, differentiation, and survival.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM099959-01A1
Application #
8304731
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
2012-04-01
Project End
2017-03-31
Budget Start
2012-04-01
Budget End
2013-03-31
Support Year
1
Fiscal Year
2012
Total Cost
$276,046
Indirect Cost
$86,046
Name
University of Kansas Lawrence
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
076248616
City
Lawrence
State
KS
Country
United States
Zip Code
66045
Dickson, Alex; Bailey, Christopher T; Karanicolas, John (2016) Optimal allosteric stabilization sites using contact stabilization analysis. J Comput Chem :
Gowthaman, Ragul; Miller, Sven A; Rogers, Steven et al. (2016) DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites. J Med Chem 59:4152-70
Johnson, David K; Karanicolas, John (2016) Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions. J Chem Inf Model 56:399-411
Bazzoli, Andrea; Kelow, Simon P; Karanicolas, John (2015) Enhancements to the Rosetta Energy Function Enable Improved Identification of Small Molecules that Inhibit Protein-Protein Interactions. PLoS One 10:e0140359
Gowthaman, Ragul; Lyskov, Sergey; Karanicolas, John (2015) DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites. PLoS One 10:e0131612
Johnson, David K; Karanicolas, John (2015) Selectivity by small-molecule inhibitors of protein interactions can be driven by protein surface fluctuations. PLoS Comput Biol 11:e1004081
Khar, Karen R; Goldschmidt, Lukasz; Karanicolas, John (2013) Fast docking on graphics processing units via Ray-Casting. PLoS One 8:e70661
Gowthaman, Ragul; Deeds, Eric J; Karanicolas, John (2013) Structural properties of non-traditional drug targets present new challenges for virtual screening. J Chem Inf Model 53:2073-81
Johnson, David K; Karanicolas, John (2013) Druggable protein interaction sites are more predisposed to surface pocket formation than the rest of the protein surface. PLoS Comput Biol 9:e1002951