The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR

Abstract

The design of Artificial Metalloenzymes (ArMs), which result from the incorporation of organometallic cofactors into biological structures, has grown steadily in the last two decades and important new-to-Nature reactions have been reached. These type of exercises could greatly benefit from an understanding of the structural impact that the inclusion of organometallic moieties may have on the biological host. To date though, our understanding of this phenomenon is highly partial. This lack of knowledge is one of the elements that condition that first-generation ArMs generally display relatively poor catalytic profiles. In this work, we approach this matter by assessing the dynamics and stability of a series of ArMs resulting from the inclusion, via different anchoring strategies, of a variety of organometallic cofactors into the Lactococcal multidrug resistance regulator (LmrR) protein. To this aim, we coupled standard force field-based techniques such as Protein-Ligand Docking and Molecular Dynamics simulations with a variety of trajectory convergence analyses, capable of assessing both the stability and flexibility of the different systems under study upon the binding of cofactors. Together with the experimental evidence obtained in other studies, we provide an overview on how these changes can affect the catalytic outcomes obtained from the different ArMs. Fundamentally, our results show that the convergence analysis used in this work can assess how the inclusion of synthetic metallic cofactors in proteins can condition different structural modulations of their host. Those conformational modifications are key to the success of the desired catalytic activity and their proper identification can be wisely used to improve the quality and the rate of success of the ArMs.

Unlocking Iminium Catalysis in Artificial Enzymes to Create a Friedel–Crafts Alkylase

“…Since the asparagine mutation at position M89 also introduces a new side chain with hydrogen-bond-accepting properties this residue plausibly cooperates with R18 during iminium ion formation. Mutation of the S95 residue to glycine involves a significant shift in helical propensity 54 and thus may perturb the secondary structure in the particularly dynamic α4 helix, 37 , 55 thus shifting the conformational ensemble toward more catalytically productive states. 56 , 57 …”

Investigating Potential Inhibitory Effect of Uncaria tomentosa (Cat’s Claw) against the Main Protease 3CLpro of SARS‐CoV‐2 by Molecular Modeling

“…We assessed the quality of our MD experiment by using four different criteria: (1) root mean square deviation of the backbone (RMSD), (2) all-to-all RMSD, (3) principal component analysis (PCA), and (4) cluster counting. This combination of analytical tools has previously proven to be a reliable assessment methodology of protein structural convergence [ 87 ]. Moreover, ligand and protein flexibility were assessed by calculation of RMSF analysis.…”

Unlocking Iminium Catalysis in Artificial Enzymes to Create a Friedel-Crafts Alkylase

“…Since the asparagine mutation at position M89 also introduces a new sidechain with hydrogen accepting properties this residue plausibly cooperates with R18 during iminium ion formation. Mutation of the S95 residue to glycine involves a significant shift in helical propensity 53 and thus may perturb the secondary structure in the particularly dynamic α4 helix, 36,54 thus shifting the conformational ensemble toward more catalytically productive states. 55,56…”