Template-dependent conformational remodeling induced by matched mutation sets in an artificial metalloenzyme

Stability engineering can extend enzyme operating ranges, but mutations that increase thermal robustness may also reshape folded-state conformational ensembles relevant to catalysis. Whether such responses are transferable between related protein templates or conditioned by the parent ensemble remains unclear. Here, we used microsecond-scale all-atom molecular dynamics (MD) simulations to compare three matched mutation sets in the A100C and V83C cofactor-attachment templates of a sterol carrier protein type 2-like domain (SCP-2L) artificial rhodium metalloenzyme, interpreting the sampled ensembles alongside published stability and turnover data. A100C exhibited lower pooled Cα positional dispersion and maintained a more contact-rich modeled holo protein-cofactor interface, whereas V83C showed greater dispersion and progressive interface loosening. Against these distinct baselines, the matched mutation sets produced markedly different folded-state responses. N31D-E81K and S56D-E81K yielded nearly identical apparent melting-temperature (T_m) gains across templates, yet, relative to their respective parents, A100C-derived variants showed lower mean correlation among retained pocket edges and lower network persistence but greater pocket-shell integration, whereas V83C-derived variants showed the reciprocal mean pattern. N31D-S56D exhibited the largest cross-template separation in local network persistence, coinciding with its divergent apparent T_m shifts (-1 °C and +12 °C on A100C and V83C, respectively). Contact remodeling extended across structural elements framing the cofactor tunnel rather than remaining confined to mutation sites or producing uniform rigidification. Thus, phenotypic convergence in apparent thermal stability did not imply convergence of folded-state remodeling. These results support an ensemble-based model in which pre-existing conformational organization shapes how the protein responds to the matched mutations and argue that stability-engineering mutations should be evaluated in the context of the parent ensemble.