화학공학소재연구정보센터
Journal of Physical Chemistry B, Vol.112, No.33, 10280-10290, 2008
Origins of the different metal preferences of Escherichia coli peptide deformylase and Bacillus thermoproteolyticus thermolysin: A comparative quantum mechanical/molecular mechanical study
The Escherichia coli peptide deformylase (PDF) and Bacillus the rinop roteol-17ticus thermolysin (TLN) are two representative metal-requiring peptidases having remarkably sirrfflar active centers but distinctively different metal preferences. Zinc is a competent catalytic cofactor for TLN but not for PDF. Reaction pathways and the associated energetics for both enzymes were determined using combined semiempirical and ab initio quantum mechanical/rnolecular mechanical modeling, without presurning reaction coordinates. The results confirmed that both enzymes catalyze via the sarne chemical steps, and reproduced their different preferences for zinc or iron as competent cofactors. Further analyses indicated that different feasibility of the nucleophilic attack step leads to different metal preferences of the two enzymes. In TLN, the substrate is strongly activated and can serve as the fifth coordination ligand of zinc prior to the chemical steps. In PDF, the substrate carbonyl is activated by the chemical step itself, and becomes the fifth coordination partner of zinc only in a later stage of the nucleophilic attack. These leads to a much mDre difficult nucleophilic attack in PDF than in TLN. Different from some earlier suggestions, zinc has no difficulty in accepting an activated substrate as the fifth ligand to switch from tetra- to penta-coordination in either PDF or TLN. When iron replaces zinc, its stronger interaction with the hydroxide ligand may lead to higher activation barrier in TLN. In PDF, the stronger interactions of iron with ligands allow iron-substrate coordination to take place either before or at a very early stage of the chemical step, leading to effective catalysis. Our calculations also show combined semiempirical and ab initio quantum mechanical modeling can be efficient approaches to explore complicated reaction pathways in enzyme systems.