New Type of Metalloproteinase Inhibitor:  Design and Synthesis of New Phosphonamide-Based Hydroxamic Acids

Sawa, Masaaki; Kiyoi, Takao; Kurokawa, Kiriko; Kumihara, Hiroshi; Yamamoto, Masakazu; Miyasaka, Tomohiro; Ito, Yasuko; Hirayama, Ryoichi; Inoue, Tomomi; Kirii, Yasuyuki; Nishiwaki, Eiji; Ohmoto, Hiroshi; Yu, Min; Ishibushi, Etsuko; Inoue, Yoshimasa; Yoshino, Kohichiro; Kondo, Hirosato

doi:10.1021/jm0103211

Cited by 120 publications

(86 citation statements)

References 33 publications

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“…4). This observation is supported by experimental K i values for the set of 35 phosphonamide hydroxamates (39). The structures of the compounds suggest that neutral and positive atoms bind in S1Ј subsite and neutral atoms dock into S3Ј subsite.…”

Section: Resultssupporting

confidence: 53%

See 1 more Smart Citation

Similarity of Binding Sites of Human Matrix Metalloproteinases

Lukáčová

Zhang

Mackov

et al. 2004

Journal of Biological Chemistry

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Tissue components hydrolyzing matrix metalloproteinases (MMPs) exhibit a high sequence similarity (56 -64% in catalytic domains) and yet a significant degree of functional specificity. The hexapeptide-binding sites of 24 known human MMPs were compared in terms of their force field interaction energies with five probes that are most frequently encountered in substrates and inhibitors. The probes moved along a grid enclosing partially flexible binding sites in rigid catalytic domains that were represented by published experimental structures and comparative models and new comparative models for nine most recently characterized MMPs. For individual MMPs, representative interaction energies were obtained as averages for all suitable experimental structures. Correlations of the representative energies for all MMP pairs were succinctly catalogued for individual probes, subsites, and correlation levels. Among the probes (neutral sp 3 carbon and sp 3 oxygen, positive sp 3 nitrogen and hydrogen, and negative carbonyl oxygen), the last probe is least distinctive. Similarities of subsites are decreasing as S1 > S2 > S3 > S1 ϳ S3 > S2 . Most interesting, occupancies of subsites in published structures of MMP-inhibitor complexes follow an almost parallel trend, alluding to overall low selectivity of known MMP inhibitors. Flexible subsite S1 that appears as the specificity pocket in rigid x-ray structures is actually very similar among individual MMPs. Several correlations indicated that MMPs 3, 8, and 12 have similar binding sites. Modeling results are corroborated with published experimental data on MMP inhibition and substrate specificities. The results provide numerous clues for development of specific inhibitors and substrates, as well as for selection of MMPs for testing that provides maximum information without redundant experiments.

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Section: Resultssupporting

confidence: 53%

“…For instance, the whole-site correlations (Fig. 2) indicate similarity of MMP 1 with MMPs 2, 3, and 8 (R 2 Ն 0.7), but two sets of experimental activities (9,39) show no significant correlation between MMP1 and the remaining three enzymes.…”

Section: Resultsmentioning

confidence: 99%

Similarity of Binding Sites of Human Matrix Metalloproteinases

Lukáčová

Zhang

Mackov

et al. 2004

Journal of Biological Chemistry

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“…1) of the hydroxamate inhibitors 46 of MMP-9 behaved anomalously: the quality of correlations did not improve with increased simulation time and some outliers adopted comparatively different conformations during MD simulations. We decided to examine whether a correlation taking into account multiple binding modes could improve the results.…”

Section: Resultsmentioning

confidence: 97%

Processing Multimode Binding Situations in Simulation-Based Prediction of Ligand−Macromolecule Affinities

et al. 2005

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The Linear Response (LR) approximation and similar approaches belong to practical methods for estimation of ligand-receptor binding affinities. The approaches correlate experimental binding affinities with the changes upon binding of the ligand electrostatic and van der Waals energies, and of solvation characteristics. These attributes are expressed as ensemble averages that are obtained by conformational sampling of the protein-ligand complex and of the free ligand by molecular dynamics or Monte Carlo simulations. We observed that outliers in the LR correlations occasionally exhibit major conformational changes of the complex during sampling. We treated the situation as a multi-mode binding case, for which the observed association constant is the sum of the partial association constants of individual states/modes. The resulting nonlinear expression for the binding affinities contains all the LR variables for individual modes that are scaled by the same 2-4 adjustable parameters as in the one-mode LR equation. The multi-mode method was applied to inhibitors of a matrix metalloproteinase, where this treatment improved the explained variance in experimental activity from 75% for the uni-mode case to about 85%. The predictive ability scaled accordingly, as verified by extensive cross-validations.

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“…(4) to the data for the one-mode and multi-mode LR approaches with classical and QM/MM energy parameters are summarized in Table 1. In all cases, the dependent variable was ln (1/K i ) because the reported K i values [23] are the inhibition constants, not the association constants. The quality of individual fits can be assessed using the statistical indices in Table 1 and also the plot of residuals vs. the experimental activities for individual equations (Figure 3).…”

Section: Resultsmentioning

confidence: 99%

“…To examine this possibility, the mm QM/MM LR method was applied to a set of 28 diverse hydroxamate inhibitors [23] of gelatinase B (MMP-9), a member of the family of matrix metalloproteinases (MMPs). MMPs participate in remodeling of extracellular matrix and are implicated in cancer, metastases, arthritis, and other diseases [24].…”

Section: Introductionmentioning

confidence: 99%

Improved estimation of ligand–macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods

Khandelwal

Baláž

2007

J Comput Aided Mol Des

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Structure-based predictions of binding affinities of ligands binding to proteins by coordination bonds with transition metals, covalent bonds, and bonds involving charge re-distributions are hindered by the absence of proper force fields. This shortcoming affects all methods which use force-field-based molecular simulation data on complex formation for affinity predictions. One of the most frequently used methods in this category is the Linear Response (LR) approach of Åquist, correlating binding affinities with van der Waals and electrostatic energies, as extended by Jorgensen's inclusion of solvent-accessible surface areas. All these terms represent the differences, upon binding, in the ensemble averages of pertinent quantities, obtained from molecular dynamics (MD) or Monte Carlo simulations of the complex and of single components. Here we report a modification of the LR approach by: (1) the replacement of the two energy terms through the single-point QM/MM energy of the time-averaged complex structure from an MD simulation; and (2) a rigorous consideration of multiple modes (mm) of binding. The first extension alleviates the force-field related problems, while the second extension deals with the ligands exhibiting large-scale motions in the course of an MD simulation. The second modification results in the correlation equation that is nonlinear in optimized coefficients, but does not lead to an increase in the number of optimized coefficients. The application of the resulting mm QM/MM LR approach to the inhibition of zinc-dependent gelatinase B (matrix metalloproteinase 9) by 28 hydroxamate ligands indicates a significant improvement of descriptive and predictive abilities.

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New Type of Metalloproteinase Inhibitor: Design and Synthesis of New Phosphonamide-Based Hydroxamic Acids

Cited by 120 publications

References 33 publications

Similarity of Binding Sites of Human Matrix Metalloproteinases

Similarity of Binding Sites of Human Matrix Metalloproteinases

Processing Multimode Binding Situations in Simulation-Based Prediction of Ligand−Macromolecule Affinities

Improved estimation of ligand–macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods

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