Proteins: Structure, Function and Bioinformatics 1998-04-01

Modeling of inhibitor-metalloenzyme interactions and selectivity using molecular mechanics grounded in quantum chemistry.

D R Garmer, N Gresh, B P Roques

Index: Proteins 31 , 42-60, (1998)

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Abstract

We investigated the binding properties of the metalloprotease inhibitors hydroxamate, methanethiolate, and methylphosphoramidate to a model coordination site occurring in several Zn2+ metalloproteases, including thermolysin. This was carried out using both the SIBFA (sum of interactions between fragments ab initio-computed) molecular mechanics and the SCF/MP2 procedures for the purpose of evaluating SIBFA as a metalloenzyme modeling tool. The energy-minimized structures were closely similar to the X-ray crystallographic structures of related thermolysin-inhibitor complexes. We found that selectivity between alternative geometries and between inhibitors usually stemmed from multiple interaction components included in SIBFA. The binding strength sequence is hydroxamate > methanethiolate > or = methylphosphoramidate from multiple interaction components included in SIBFA. The trends in interaction energy components, rankings, and preferences for mono- or bidentate binding were consistent in both computational procedures. We also compared the Zn2+ vs. Mg2+ selectivities in several other polycoordinated sites having various "hard" and "soft" qualities. This included a hexahydrate, a model representing Mg2+/Ca2+ binding sites, a chlorophyll-like structure, and a zinc finger model. The latter three favor Zn2+ over Mg2+ by a greater degree than the hydrated state, but the selectivity varies widely according to the ligand "softness." SIBFA was able to match the ab initio binding energies by < 2%, with the SIBFA terms representing dispersion and charge-transfer contributing the most to Zn2+/Mg2+ selectivity. These results showed this procedure to be a very capable modeling tool for metalloenzyme problems, in this case giving valuable information about details and limitations of "hard" and "soft" selectivity trends.