Protein Kinases are critical constituents of signal transduction networks and their malfunction is associated with disease including cancer, inflammation, diabetes, and heart disease. Traditional drug discovery efforts have pursued inhibitors that target the ATP binding site with little consideration for other sites on protein kinase surfaces. Our hypothesis is that we can use structure-based design techniques to identify novel small molecule binding sites (exosites) on the surface of protein kinases. We know that other exosites must exist because screens of natural products and synthetic libraries have identified ATP-noncompetitive inhibitors for many members of the kinase family. The first goal of this research is to provide a new therapeutic approach to target three protein kinases, Protein Kinase A, Protein Kinase B and Aurora A Kinase. This will be achieved by the successful completion of three aims (I) To identify, through computational analysis, novel druggable sites ('exosites') on PKA, PKB and Aurora A;(II) To identify, by virtual ligand screening, small drug-like molecules that bind to exosites on these kinases and inhibit function;(III) To develop these inhibitors into drug-leads through chemical optimization, structural characterization and iteration. In our final aim: (IV) We will apply our computational analysis to the whole kinase family and identify druggable exosites for other members. We will make available our findings through the Protein Kinase Resource (a public web-based kinase resource), so that these novel exosites can be targeted by academic groups working on specific protein kinases. The nature of the project is multi-disciplinary and we believe that the goals are within reach due to our combined expertise in computational, molecular and structural biology.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
7R01GM074832-05
Application #
7961365
Study Section
Special Emphasis Panel (ZRG1-BCMB-Q (02))
Program Officer
Fabian, Miles
Project Start
2006-05-01
Project End
2011-04-30
Budget Start
2009-08-01
Budget End
2011-04-30
Support Year
5
Fiscal Year
2009
Total Cost
$196,068
Indirect Cost
Name
University of California San Diego
Department
Type
Schools of Pharmacy
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Warszycki, Dawid; Rueda, Manuel; Mordalski, Stefan et al. (2017) From Homology Models to a Set of Predictive Binding Pockets-a 5-HT1A Receptor Case Study. J Chem Inf Model 57:311-321
Rueda, Manuel; Totrov, Max; Abagyan, Ruben (2012) ALiBERO: evolving a team of complementary pocket conformations rather than a single leader. J Chem Inf Model 52:2705-14
Katritch, Vsevolod; Kufareva, Irina; Abagyan, Ruben (2011) Structure based prediction of subtype-selectivity for adenosine receptor antagonists. Neuropharmacology 60:108-15
Grigoryan, A V; Kufareva, I; Totrov, M et al. (2010) Spatial chemical distance based on atomic property fields. J Comput Aided Mol Des 24:173-82
Park, So-Jung; Kufareva, Irina; Abagyan, Ruben (2010) Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using conformational ensembles. J Comput Aided Mol Des 24:459-71
Rueda, Manuel; Bottegoni, Giovanni; Abagyan, Ruben (2010) Recipes for the selection of experimental protein conformations for virtual screening. J Chem Inf Model 50:186-93
Katritch, Vsevolod; Rueda, Manuel; Lam, Polo Chun-Hung et al. (2010) GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex. Proteins 78:197-211
Cheltsov, Anton V; Aoyagi, Mika; Aleshin, Alexander et al. (2010) Vaccinia virus virulence factor N1L is a novel promising target for antiviral therapeutic intervention. J Med Chem 53:3899-906
Rueda, Manuel; Katritch, Vsevolod; Raush, Eugene et al. (2010) SimiCon: a web tool for protein-ligand model comparison through calculation of equivalent atomic contacts. Bioinformatics 26:2784-5
Katritch, Vsevolod; Jaakola, Veli-Pekka; Lane, J Robert et al. (2010) Structure-based discovery of novel chemotypes for adenosine A(2A) receptor antagonists. J Med Chem 53:1799-809

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