Zhang Y, Lukacova V, Bartus V, Balaz S. Structural determinants of binding of aromates to extracellular matrix: a multi-species multi-mode CoMFA study.
Chem Res Toxicol 2007;
20:11-9. [PMID:
17226922 PMCID:
PMC2896058 DOI:
10.1021/tx060188l]
[Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
For small molecules acting in tissues, including signaling peptides, effectors, inhibitors, and other drug candidates, nonspecific binding to the extracellular matrix (ECM) is a critical phenomenon affecting their disposition, toxicity, and other effects. A commercially available ECM mimic, forming a solidified layer at the bottom of the vials, was used to measure the association constants of 25 simple aromatic compounds to two forms of ECM proteins, solidified (s-ECM) and dissolved (d-ECM) in the buffer during the incubation. Except for small homologous series, the binding data did not correlate with the lipophilicity and acidity of the compounds, contrary to a common expectation for nonspecific binding. To elucidate the putative structures of averaged binding sites of s-ECM and d-ECM, comparative molecular field analysis (CoMFA) was applied in a modified version taking into consideration that multiple modes and multiple species may be involved. The method shapes a receptor site model from a set of grid points in which the interaction energies between a probe atom and superimposed ligands are calculated. Electrostatic and steric energies in the grid points are characterized by regression coefficients. The forward-selection nonlinear regression analysis was used to optimize the coefficients in the novel multi-species, multi-mode CoMFA models. These models showed satisfactory descriptive and predictive abilities for both s-ECM and d-ECM binding data, which were better than those obtained with the standard, one-mode CoMFA analysis. The calibrated models, defining the electrostatic and van der Waals regions of putative binding sites, are suitable for the prediction of ECM binding for untested chemicals.
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