Research
Interests
Enzymology
of the Penicillin-Binding Proteins (PBPs) and Development of New
Antibacterial Agents
The
penicillin-binding proteins
are ubiquitous bacterial enzymes involved in cell wall biosynthesis. As
their name implies, these enzymes are the targets of the beta-lactam
antibiotics. The emergence of antibiotic resistant pathogenic bacteria,
including resistance to the beta-lactam antibiotics, posses a serious
public health threat (Antimicrobial
Resistance, NIAID Fact Sheet). This threat is increase given the
potential use of antibiotic resistant pathogenic bacteria as
bioterrorism agents (NIAID Biodefense Web
Site). It is the goal of this research
project to perform detailed enzymological studies of the PBPs, and to
use information gained from these studies for the development of new
inhibitors of the PBPs for use as new antibacterial agents. As observed
by Waxman and Strominger (1983) "The absence of a simple, rapid,
and sensitive assay has made detailed kinetic and enzymological studies
of purified CPases (PBPs) slow and difficult". Our initial efforts
in this area focused on the development of new and improved assay
methods for these medically important enzymes. The concept of
non-linear coupled enzyme assay has been introduced as the basis for
these assays. Using these assays we have characterized in some detail
the enzymological properties of several LMM PBPs, including their pH
dependence and basic substrate specificity. These studies, performed in
collaboration with Drs. Robert Nicholas at the University of North
Carolina in Chapel Hill and Christopher Davies at the University of
SOuth Carolina in Charleston, have provided useful mechanistic and
physiological information on these enzymes. A series of potential
transition state analog inhibitors for these enzymes have also been
prepared and characterized, and reveal that peptide boronic acids as
currently the best peptide mimetic inhibitors known for these enzymes.
Additional studies to further explore the enzymology of these enzyme of
to develop improved peptide mimetic inhibitors are currently underway.
Gutheil, W.G.
(1998) "An
Equilibrium Based Assay for D-Lactate using D-Lactate Dehydrogenase.
Application to Penicillin-Binding Protein Activity Against D-Lactate
Containing Substrates", Anal.
Biochem 259, 62-67.
Gutheil WG,
Stefanova ME, Nicholas
RA.
(2000) "Fluorescent coupled enzyme assays for D-alanine: application to
penicillin-binding protein and vancomycin activity assays." Anal Biochem 287, 196-202.
Stefanova ME, Davies C, Nicholas RA, Gutheil WG (2002) "pH, inhibitor,
and substrate specificity studies on Escherichia coli
penicillin-binding protein 5" Biochim Biophys Acta 1597, 292-300.
Pechenov A, Stefanova ME, Nicholas RA, Peddi S, Gutheil WG (2003)
"Potential transition state analogue inhibitors for the
penicillin-binding proteins" Biochemistry 42, 579-88.
Stefanova ME, Tomberg J,
Olesky M, Holtje JV, Gutheil WG, Nicholas RA (2003) "Neisseria
gonorrhoeae penicillin-binding protein 3 exhibits exceptionally high
carboxypeptidase and beta-lactam binding activities" Biochemistry 42, 14614-25.
Stefanova ME, Tomberg J, Davies C, Nicholas RA, Gutheil WG (2004)
"Overexpression and enzymatic characterization of Neisseria gonorrhoeae
penicillin-binding protein 4" Eur J Biochem 271, 23-32.
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Hierarchical
Interaction Based Analysis of Complex Thermodynamic Systems.
Many thermodynamic
systems of
fundamental interested are "complex" in the sense that they posses a
number of possible interactions between individual events. One example
of such a system is the binding of oxygen by hemoglobin which, despite
a century of intense study, remains the subject of debate concerning
the thermodynamic and mechanistic details of its mechanism. The problem
with complex systems is that they require a large number of parameters
to describe their physical behavior, and this large number of
parameters cannot always be determined from the available experimental
data for a complex system. Even in situations were all the parameters
are available, it is likely that these parameters will not be
completely "independent" in either the physical or statistical sense,
and there is interpretive value in finding the minimal set of
independent parameters required to describe the system. The question
is, is there a scientifically and mathematically rigorous method for
finding a minimal set of independent parameters for a complex system?
We
have developed a method
for explicitly treating complex state (i.e., path independent) systems
as a hierarchy of interactions. The concept of hierarchical
interactions is illustrated in the accompanying FIGURES.
For two ligands
binding to a protein a term ab used to account for the possible
interaction of the two ligands. For three ligands a third order
interaction term abc is used to account for the potential
interaction of all three ligands. Note that the abc term occurs
on all three pathways leading to the PABC complex in the figure. This
term represents the mutual interaction of the three ligands, and can be
considered equivalently as the effect of A binding on how B and C
interact, the effect of B binding on how A and C interact, and the
effect of C on how A and B interact. Therefore, for the abc
interaction to exist physically requires that the ab, ac,
and bc interactions to exist physically, i.e., for a higher
order term to exist requires all lower order terms which it modulates
to exist.
This simple observation has
profound consequences for treating complex systems. For example, in a
theoretical analysis of a complex system, if it can be established by
inference or conjecture that a given lower order term is equal to zero,
than all higher order related to this term will drop out of the
analysis. This provides the basis for our theoretical treatment of
allosterism in a dimeric protein, a problem which had resisted all
previous attempts at analysis. This concept can also be used for the
statistical analysis of experimental data to provide the minimal set of
parameters required to explain the experimental data, as demonstrated
in the recently published analysis of spectroscopically monitored
hemoglobin oxygen binding data.
To further demonstrate the utility of
this approach it has recently been applied to the analysis of
thermodynamic interactions between proton binding events in a series of
organic and inorganic polyprotic acids and bases. For both rigid
inorganic acids, as well as for relatively flexible organic acids,
third order interactions were essentially zero, confirming a basic
tenent of the hierarchical interaction approach that higher order terms
are less likely to be physically/statistically significant than lower
order terms. In addition, the values for the pairwise interactions
between pairs of protons could be correlated with molecular structure,
providing unique insight into physical basis of proton interactions in
these
two simple systems.
Gutheil, WG,
McKenna,
CE (1992) "Unique and Independent Parameters (UIP) Formulation for
Thermodynamic Models of Complex Protein Ligand Systems", Biophys.
Chem. 45, 171-179.
Gutheil, WG (1992)
"Thermodynamic Model of Cooperativity in a Dimeric Protein: Unique and
Independent Parameters Formulation", Biophys.
Chem. 45, 181-191.
Gutheil, WG (1994)
"The
Reformulation of Thermodynamic Systems with Aggregation, and
Theoretical Methods for the Analysis of Ligand Binding in Proteins With
Monomer-Multimer Equilibria", Biophys.
Chem. 52, 83-95.
Gutheil, WG (1998)
"Statistical Analysis of Data Pertaining to Complex State Systems by
Stepwise Regression with Reformulated Parameters. Application to
Spectroscopically Monitored Hemoglobin Oxygen Binding Data", Biophys.
Chem. 70, 185-201.
Gutheil WG (2002)
"A simple
chemical
example of hierarchical thermodynamic interactions: the protonation
equilibria of inorganic polyprotic acids" Biophys Chem 88, 35-45.
Gutheil WG (2000)
"Application
of hierarchical thermodynamic interactions to the protonation
equilibria of organic polyprotic acids" Biophys Chem 88, 119-26.
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Glutathione-Dependant
Formaldehyde Dehydrogenases (presently an inactive research area in my
lab)
The
glutathione-dependant
formaldehyde dydrogenases (GS-FDHs) are ubiquitous enzymes involved in
the detoxification of the mutagen formaldehyde. These enzymes are
members of superfamily of zinc dependent alcohol dehydrogenases (ADHs).
The very highly conserved nature of the GS-FDHs suggests the GS-FDHs as
the evolutionary predecessors to the entire superfamily of zinc ADHs.
In E. coli and H. influenza this enzymes activity is
inducible. The additional characterization of this enzymes functional
evolution into the other members of this superfamily of enzymes would
shed light on how new enzyme activities evolve from existing
activities. Further characterization of the induction of this enzymes
activity in bacteria would provide information on how biological
systems respond to the deleterious effects of mutagens.
Gutheil, W.G.,
Holmquist, B.
& Vallee, B.L. (1992) "Purification, Characterization, and Partial
Sequence of the Glutathione-Dependant Formaldehyde Dehydrogenase from
Escherichia coli: A Class III Alcohol Dehydrogenase", Biochemistry
31, 475-481.
Gutheil, W.G.,
Kasimoglu, E.,
& Nicholson, P.C. (1997) "Induction of Glutathione-Dependent
Formaldehyde Dehydrogenase Activity in Escherichia coli and Hemophilus
influenza", Biophys.
Biochem. Res. Comm. 238, 693-696.
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Numerical
Modeling and Statistical Analysis of Data Pertaining to Complex Kinetic
Systems
The scientific
process requires
the ability to quantitatively account for the behavior of the system
under study. In some cases quantitative description is simple, for
example the average weight of a group of acorns is a simple calculation
which leads directly to the desired physical constant. Complex kinetic
systems represent situations where a simple calculations cannot provide
the final answer to the problem. Kinetic problems of this type arise in
a wide variety of situations ranging from the characterization of
enzyme-inhibitor interactions to the quantitative analysis of gene
regulation. As part of our interest in the quantitative treatment of
complex kinetic systems of this type, we have prepared a Matlab based
software package (kinlsq) for the numerical simulation of kinetic
models. This package also allows for non-linear least squares
statistical analysis of data. The user must purchase a copy of Matlab,
and the Optimization Toolbox and Simulink, from The MathWorks.
1) Gutheil, WG,
Bachovchin, WW
(1993) "Separation of L-Pro-DL-boroPro Diastereomers
and Kinetic Analysis of Their Inhibition of Dipeptidyl Peptidase IV. A
New Method for the Analysis of Slow, Tight-Binding Inhibition", Biochemistry
32, 8723-8731.
2) Dahl, NK,
Gutheil, WG,
Liscum, L (1993) "Abnormal Regulation of Low Density
Lipoprotein-Sensitive Events in a Cholesterol Transport Mutant", J.
Biol. Chem. 268, 16979-6986.
3) Gutheil, WG,
Kettner, CE
Bachovchin, WW (1994) "Kinlsq: A Program for Fitting Kinetics
Data With Numerically Integrated Rate Equations and its Application to
the Analysis of Slow, Tight-Binding Inhibition", Anal.
Biochem. 223, 13-20.
4) Gutheil, WG,
Subramanyam,
M, Flentke, GR, Sanford, DG, Munoz, E, Huber, BT,
Bachovchin, WW (1994) "HIV-1 Tat Binds to DP IV (CD 26). A Possible
Mechanism for Tat Mediated Immunosuppression", Proc.
Natl. Acad. Sci. USA 91, 6594-6598.
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