Adam H. Steeves’s research while affiliated with Massachusetts Institute of Technology and other places

An understanding of protein stability requires capturing dynamic rearrangements and coupled properties over long lengthscales. Nevertheless, the extent of coupling in these systems has typically only been studied for classical degrees of freedom. To understand the potential benefit of extending such analysis to the coupling of electronic structure properties, we have carried out extensive semi-empirical quantum mechanical molecular dynamics of two Trp-cage variants. Small differences in the sequence of the two peptides lead to differences in their thermal stability that are revealed through electronic structure coupling analysis. In comparison, we find limited evidence that geometric coupling can distinguish the behavior of the two peptides. We show that Asp1 in the more stable variant shows significantly enhanced coupling to both sequence-adjacent and more sequence-distant residues. Non-nearest-neighbor couplings are stronger in the more stable variant, indicating a network of residues that help stabilize the protein. Our study highlights the complementary benefit of charge coupling analysis to interpret protein structure–function relationships.

An understanding of protein stability requires capturing dynamic rearrangements and coupled properties over long lengthscales. Nevertheless, the extent of coupling in these systems has typically only been studied for classical degrees of freedom. To understand the potential benefit of extending such analysis to the coupling of electronic structure properties, we have carried out extensive semi-empirical quantum mechanical molecular dynamics of two Trp-cage variants. Small differences in the sequence of the two peptides lead to differences in their thermal stability that are revealed through electronic structure coupling analysis. In comparison, we find limited evidence that geometric coupling can distinguish the behavior of the two peptides. We show that Asp1 in the more stable variant shows significantly enhanced coupling to both sequence-adjacent and more sequence-distant residues. Non-nearest-neighbor couplings are stronger in the more stable variant, indicating a network of residues that help stabilize the protein. Our study highlights the complementary benefit of charge coupling analysis to interpret protein structure¬¬¬–function relationships.

The Mo/W-containing metalloenzyme formate dehydrogenase (FDH) is an efficient and selective natural catalyst that reversibly converts CO2 to formate under ambient conditions. In this study, we investigate the impact of the greater protein environment on the electrostatic potential (ESP) of the active site. To model the enzyme environment, we used a combination of classical molecular dynamics and multiscale quantum-mechanical (QM)/molecular-mechanical (MM) simulations. We leverage charge shift analysis to systematically construct QM regions and analyze the electronic environment of the active site by evaluating the degree of charge transfer between the core active site and the protein environment. The contribution of the terminal chalcogen ligand to the ESP of the metal center is substantial and dependent on the chalcogen identity, with similar, less negative ESPs for Se and S terminal chalcogens in comparison to O regardless of whether the metal is Mo or W. The orientation of the side chains and conformations of the cofactor also affect the ESP, highlighting the importance of sampling dynamic fluctuations in the protein. Overall, our observations suggest that the terminal chalcogen ligand identity plays an important role in the enzymatic activity of FDH, suggesting opportunities for a rational bioinspired catalyst design.

Computational prediction of enzyme mechanism and protein function requires accurate physics-based models and suitable sampling. We discuss recent advances in large-scale quantum mechanical (QM) modeling of biochemical systems that have reduced the cost of high-accuracy models. Tradeoffs between sampling and accuracy have motivated modeling with molecular mechanics (MM) in a multiscale QM/MM or iterative approach. Limitations to both conventional density-functional theory and classical MM force fields remain for describing noncovalent interactions in comparison to experiment or wavefunction theory. Because predictions of enzyme action (i.e. electrostatics), free energy barriers, and mechanisms are sensitive to the protocol and embedding method in QM/MM, convergence tests and systematic methods for quantifying QM-level interactions are a needed, active area of development.

The Mo/W containing metalloenzyme formate dehydrogenase (FDH) is an efficient and selective natural catalyst which reversibly converts CO2 to formate under ambient conditions. A greater understanding of the role of the protein environment in determining the local properties of the FDH active site would enable rational bioinspired catalyst design. In this study, we investigate the impact of the greater protein environment on the electrostatic potential (ESP) of the active site. To model the enzyme environment, we used a combination of long-timescale classical molecular dynamics (MD) and multiscale quantum-mechanical/molecular-mechanical (QM/MM) simulations. We leverage the charge shift analysis method to systematically construct QM regions and analyze the electronic environment of the active site by evaluating the degree of charge transfer between the core active site and the protein environment. The contribution of the terminal chalcogen ligand to the ESP of the metal center is substantial and dependent on the chalcogen identity, with ESPs less negative and similar for Se and S terminal chalcogens than for O regardless of whether the Mo6+ or W6+ metal center is present. Our evaluation reveals that the orientation of the sidechains and ligand conformations will alter the relative trends in the ESP observed for a given metal center or terminal chalcogen, highlighting the importance of sampling dynamic fluctuations in the protein. Overall, our observations suggest that the terminal chalcogen ligand identity plays an important role in the enzymatic activity of FDH.

The design of bioinspired synthetic inorganic molecular complexes is challenging, due to a lack of understanding of enzyme action and the degree to which that action can be translated into mimics. Exemplary of this challenge is the reversible conversion of formate into CO2 by formate dehydrogenase (FDH) enzymes with Mo/W centers in large molybdopterin cofactors. Despite numerous efforts to synthesize Mo/W-containing molecular complexes, none have been demonstrated to reproduce the full reactivity of FDH. Here, we carry out a large-scale, high-throughput screening study on all mononuclear Mo/W complexes currently deposited in Cambridge Structural Database (CSD). Using density functional theory, we systematically investigate the individual effects of metal identity, ligand identity, oxidation state, and coordination number on structural, electronic and catalytic properties. We compare our results on molecular complexes with quantum mechanics/molecular mechanics simulations on a representative FDH enzyme to further elucidate the influence of the enzyme environment. These comparisons reveal that the enzyme environment primarily influences the metal-local geometry, and these metal-local structural variations can improve catalysis. Through a series of computational mutations on molecular complexes, we extend beyond the CSD structures to further identify the limits of varied chalcogen and metal identity. This broad set and comparison reveal relatively little variation of electronic properties of the metal center due to the presence of the enzyme environment or changes in metal-distant ligand chemistry. Instead, these properties are found to be much more sensitive to the identity of the metal and the nature of the bound terminal chalcogen.

The design of bioinspired synthetic inorganic molecular complexes is challenging, due to a lack of understanding of enzyme action and the degree to which that action can be translated into mimics. Exemplary of this challenge is the reversible conversion of formate into CO2 by formate dehydrogenase (FDH) enzymes with Mo/W centers in large molybdopterin cofactors. Despite numerous efforts to synthesize Mo/W-containing molecular complexes, none have been demonstrated to reproduce the full reactivity of FDH. Here, we carry out a large-scale, high-throughput screening study on all mononuclear Mo/W complexes currently deposited in Cambridge Structural Database (CSD). Using density functional theory, we systematically investigate the individual effects of metal identity, ligand identity, oxidation state, and coordination number on structural, electronic and catalytic properties. We compare our results on molecular complexes with quantum mechanics/molecular mechanics simulations on a representative FDH enzyme to further elucidate the influence of the enzyme environment. These comparisons reveal that the enzyme environment primarily influences the metal-local geometry, and these metal-local structural variations can improve catalysis. Through a series of computational mutations on molecular complexes, we extend beyond the CSD structures to further identify the limits of varied chalcogen and metal identity. This broad set and comparison reveal relatively little variation of electronic properties of the metal center due to the presence of the enzyme environment or changes in metal-distant ligand chemistry. Instead, these properties are found to be much more sensitive to the identity of the metal and the nature of the bound terminal chalcogen.

The Cover Feature shows a mutual information analysis of charge distributions in proteins. The presented study reveals that electronic couplings are long range in nature even between neutral amino acids. More information can be found in the Full Paper by Zhongyue Yang et al.

The delicate interplay of covalent and non‐covalent interactions in proteins is inherently quantum mechanical and highly dynamic in nature. To directly interrogate the evolving nature of the electronic structure of proteins, we carry out 100‐ps‐scale ab initio molecular dynamics simulations of three representative small proteins with range‐separated hybrid density functional theory. We quantify the nature and length‐scale of the coupling of residue‐specific charge probability distributions in these proteins. While some nonpolar residues exhibit expectedly narrow charge distributions, most polar and charged residues exhibit broad, multimodal distributions. Even for nonpolar residues, we observe sequence‐specific deviations corresponding to charge accumulation or depletion that would be challenging to capture in a fixed charge force field. We quantify the effect of residue‐residue interactions on charge distributions first with linear cross‐correlations. We then show how additional insight can be gained from evaluating the mutual information of charge distributions. We show that a significant number of residues couple most strongly with residues that are distant in both sequence and space over a range of secondary structures including α‐helical, β‐sheet, disulfide bridging, and lasso motifs. The mutual information analysis is necessary to capture coupling between some polar and charged residues that would be otherwise missed. Analysis of cross correlation and mutual information of by‐residue charge distributions in proteins reveals the long range nature of quantum mechanical charge coupling observed in the ab initio molecular dynamics of proteins.