Yersinia pestis is a Category A priority agent according to the classification by the National Institute of Allergy and Infectious Diseases. It is the pathogen that causes plague. Because there are already evidences that blocking the protein tyrosine phosphatase YopH of this bacterium can remove the pathogenic effects of this bacterium, the long-term goal of this research is to use a unique blend of computational and experimental methods to speed up the discovery and development of anti-plague agents targeting this protein. There are three specific aims for this application.
Specific Aim 1 focuses on optimizing the lead p-nitrocatechol sulfate (pNCS). Our computational studies have already generated useful insights into improving pNCS for selective binding towards YopH. We will perform more quantitative calculations to further elaborate these findings. The most useful insights will then guide the construction of focused chemical libraries for experimental screening and the synthesis of computer-aided designed compounds for experimental testing.
Specific Aim 2 focuses on identifying new leads with different chemical scaffolds. We will first use computational approaches to screen chemical libraries to come up with a more manageable number of compounds for experimental screening. These computational approaches include modern molecular docking technology incorporating receptor flexibility, a Quantum Mechanics/Poisson- Boltzmann-Surface-Area model for evaluating clogP to use with Lipinski's Rules to assess whether compounds are drug-like, and informatics approach for guiding the development of selective drugs. On the experimental side, we are drawing our previous experiences on developing in vitro assays of YopH, PTP1B, PTPa and VHR. We will also determine the crystal structure of complexes between YopH and some of the most promising inhibitors to aid rational optimization of the new drug leads.
Specific Aim 3 focuses on performing preliminary optimization of the drug leads obtained from Specific Aim 2. Computational chemical modification experiments (using our Quantum Mechanics/Molecular Mechanics/Poisson-Boltzmann-Surface-Area model and statistical mechanical perturbation theory), comparative pocket analysis of YopH and the whole family of human protein phosphatases, and computational prediction of drug-likeliness will be performed to help suggest compounds that are worthwhile to synthesize for experimental testing. For the current funding period we have set our goal of identifying inhibitors with Ki values of less than 50 nM and a selectivity of 100-fold in favor of YopH (versus the other PTPases noted above). The tight collaboration between a computational and an experimental laboratory will also provide a good opportunity to more thoroughly validate modern computational methods for drug design. Yersinia pestis is a Category A priority agent according to the classification by the National Institute of Allergy and Infectious Diseases. It is the pathogen that causes plague and can be misused as a weapon.
This research aims at identifying anti-plague agents that target a protein called YopH of this bacterium. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AI071991-01A1
Application #
7306010
Study Section
Special Emphasis Panel (ZRG1-BCMB-N (90))
Program Officer
Mukhopadhyay, Suman
Project Start
2007-09-29
Project End
2009-08-31
Budget Start
2007-09-29
Budget End
2008-08-31
Support Year
1
Fiscal Year
2007
Total Cost
$239,625
Indirect Cost
Name
University of Missouri-St. Louis
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
804883825
City
Saint Louis
State
MO
Country
United States
Zip Code
63121
Wong, Chung F (2015) Flexible receptor docking for drug discovery. Expert Opin Drug Discov 10:1189-200
Huang, Zunnan; He, Yantao; Zhang, Xian et al. (2010) Derivatives of salicylic acid as inhibitors of YopH in Yersinia pestis. Chem Biol Drug Des 76:85-99
Huang, Zunnan; Wong, Chung F (2009) Docking flexible peptide to flexible protein by molecular dynamics using two implicit-solvent models: an evaluation in protein kinase and phosphatase systems. J Phys Chem B 113:14343-54