QM/MM Study of the Nitrogenase MoFe Protein Resting State: Broken-Symmetry States, Protonation States, and QM Region Convergence in the FeMoco Active Site

Nitrogenase is one of the most fascinating enzymes in nature, being responsible for all biological nitrogen reduction. Despite decades of research, it is among the enzymes in bioinorganic chemistry whose mechanism is the most poorly understood. The MoFe protein of nitrogenase contains an iron–molybdenum–sulfur cluster, FeMoco, where N2 reduction takes place. The resting state of FeMoco has been characterized by crystallography, multiple spectroscopic techniques, and theory (broken-symmetry density functional theory), and all heavy atoms are now characterized. The cofactor charge, however, has been controversial, the electronic structure has proved enigmatic, and little is known about the mechanism. While many computational studies have been performed on FeMoco, few have taken the protein environment properly into account. In this study, we put forward QM/MM models of the MoFe protein from Azotobacter vinelandii, centered on FeMoco. By a detailed analysis of the FeMoco geometry and comparison to the atomic resolution crystal structure, we conclude that only the [MoFe7S9C]1– charge is a possible resting state charge. Further, we find that of the three lowest energy broken-symmetry solutions of FeMoco, the BS7-235 spin isomer (where 235 refers to Fe atoms that are “spin-down”) is the only one that can be reconciled with experiment. This is revealed by a comparison of the metal–metal distances in the experimental crystal structure, a rare case of spin-coupling phenomena being visible through the molecular structure. This could be interpreted as the enzyme deliberately stabilizing a specific electronic state of the cofactor, possibly for tuning specific reactivity on specific metal atoms. Finally, we show that the alkoxide group on the Mo-bound homocitrate must be protonated under resting state conditions, the presence of which has implications regarding the nature of FeMoco redox states as well as for potential substrate reduction mechanisms.We thank Albert Th. Thórhallsson for useful discussions. R.B. acknowledges support from the Icelandic Research Fund, grant nos. 141218051 and 141218052, and the University of Iceland Research Fund. R.B. thanks Hannes Jónsson and Egill Skúlason for support.Peer Reviewe

Quantum Mechanics/Molecular Mechanics Study of Resting-State Vanadium Nitrogenase: Molecular and Electronic Structure of the Iron–Vanadium Cofactor

Publisher's version (útgefin grein)The nitrogenase enzymes are responsible for all biological nitrogen reduction. How this is accomplished at the atomic level, however, has still not been established. The molybdenum-dependent nitrogenase has been extensively studied and is the most active catalyst for dinitrogen reduction of the nitrogenase enzymes. The vanadium-dependent form, on the other hand, displays different reactivity, being capable of CO and CO2 reduction to hydrocarbons. Only recently did a crystal structure of the VFe protein of vanadium nitrogenase become available, paving the way for detailed theoretical studies of the iron-vanadium cofactor (FeVco) within the protein matrix. The crystal structure revealed a bridging 4-atom ligand between two Fe atoms, proposed to be either a CO32- or NO3- ligand. Using a quantum mechanics/molecular mechanics model of the VFe protein, starting from the 1.35 Å crystal structure, we have systematically explored multiple computational models for FeVco, considering either a CO32- or NO3- ligand, three different redox states, and multiple broken-symmetry states. We find that only a [VFe7S8C(CO3)]2- model for FeVco reproduces the crystal structure of FeVco well, as seen in a comparison of the Fe-Fe and V-Fe distances in the computed models. Furthermore, a broken-symmetry solution with Fe2, Fe3, and Fe5 spin-down (BS7-235) is energetically preferred. The electronic structure of the [VFe7S8C(CO3)]2- BS7-235 model is compared to our [MoFe7S9C]- BS7-235 model of FeMoco via localized orbital analysis and is discussed in terms of local oxidation states and different degrees of delocalization. As previously found from Fe X-ray absorption spectroscopy studies, the Fe part of FeVco is reduced compared to FeMoco, and the calculations reveal Fe5 as locally ferrous. This suggests resting-state FeVco to be analogous to an unprotonated E1 state of FeMoco. Furthermore, V-Fe interactions in FeVco are not as strong compared to Mo-Fe interactions in FeMoco. These clear differences in the electronic structures of otherwise similar cofactors suggest an explanation for distinct differences in reactivity.R.B. acknowledges support from the Icelandic Research Fund (Grants 141218051 and 162880051) and University of Iceland Research Fund. Open Access funding was provided by the Max Planck Society.Peer Reviewe

A model for dinitrogen binding in the E4 state of nitrogenase

Publisher's version (útgefin grein)Molybdenum nitrogenase is one of the most intriguing metalloenzymes in nature, featuring an exotic iron-molybdenum-sulfur cofactor, FeMoco, whose mode of action remains elusive. In particular, the molecular and electronic structure of the N2-binding E4 state is not known. In this study we present theoretical QM/MM calculations of new structural models of the E4 state of molybdenum-dependent nitrogenase and compare to previously suggested models for this enigmatic redox state. We propose two models as possible candidates for the E4 state. Both models feature two hydrides on the FeMo cofactor, bridging atoms Fe2 and Fe6 with a terminal sulfhydryl group on either Fe2 or Fe6 (derived from the S2B bridge) and the change in coordination results in local lower-spin electronic structure at Fe2 and Fe6. These structures appear consistent with the bridging hydride proposal put forward from ENDOR studies and are calculated to be lower in energy than other proposed models for E4 at the TPSSh-QM/MM level of theory. We critically analyze the DFT method dependency in calculations of FeMoco that has resulted in strikingly different proposals for this state. Importantly, dinitrogen binds exothermically to either Fe2 or Fe6 in our models, contrary to others, an effect rationalized via the unique ligand field (from the hydrides) at the Fe with an empty coordination site. A low-spin Fe site is proposed as being important to N2 binding. Furthermore, the geometries of these states suggest a feasible reductive elimination step that could follow, as experiments indicate. Via this step, two electrons are released, reducing the cofactor to yield a distorted 4-coordinate Fe2 or Fe6 that partially activates N2. We speculate that stabilization of an N2-bound Fe(i) at Fe6 (not found for Fe2 model) via reductive elimination is a crucial part of N2 activation in nitrogenases, possibly aided by the apical heterometal ion (Mo or V). By using protons from the sulfhydryl group (to regenerate the sulfide bridge between Fe2 and Fe6) and the nearby homocitrate hydroxy group, we calculate a plausible route to yield a diazene intermediate. This is found to be more favorable with the Fe6-bound model than the Fe2-bound model; however, this protonation is uphill in energy, suggesting protonation of N2 might occur later in the catalytic cycle or via another mechanism.RB acknowledges support from the Icelandic Research Fund, Grants No. 141218051 and 162880051 and the University of Iceland Research Fund. The Max Planck society is acknowledged for funding. Serena DeBeer is thanked for support. Some of the computations were performed on resources provided by the Icelandic High Performance Computing Centre at the University of Iceland.Peer Reviewe

Materials Funnel 2.0 - Data-driven hierarchical search for exploration of vast chemical spaces

Innovating ways to explore the materials phase space accelerates functional materials discovery. For breakthrough materials, faster exploration of larger phase spaces is a key goal. High-throughput computational screening (HTCS) is widely used to rapidly search for materials with the desired functional property. This article redefines the HTCS methods to combine multiple deep learning models and physics-based simulation to explore much larger chemical spaces than possible by pure physics-driven HTCS. Deep generative models are used to autonomously create materials libraries with a high likelihood of desired properties, inverting the standard design paradigm. Additionally, machine-learned surrogates enable the next layer of screening to prune the set further so that high-quality quantum-mechanical simulations can be performed. With organic photovoltaic (OPV) molecules as a test bench, the power of this redesigned HTCS approach is shown in the inverse design of OPV molecules with very limited computational expense using only 1% of the original physics-based screening dataset

Structural correlations of nitrogenase active sites using nuclear resonance vibrational spectroscopy and QM/MM calculations

International audiencehe biological conversion of N-2 to NH3 is accomplished by the nitrogenase family, which is collectively comprised of three closely related but unique metalloenzymes. In the present study, we have employed a combination of the synchrotron-based technique of Fe-57 nuclear resonance vibrational spectroscopy together with DFT-based quantum mechanics/molecular mechanics (QM/MM) calculations to probe the electronic structure and dynamics of the catalytic components of each of the three unique M N(2)ase enzymes (M = Mo, V, Fe) in both the presence (holo-) and absence (apo-) of the catalytic FeMco clusters (FeMoco, FeVco and FeFeco). The results described herein provide vibrational mode assignments for important fingerprint regions of the FeMco clusters, and demonstrate the sensitivity of the calculated partial vibrational density of states (PVDOS) to the geometric and electronic structures of these clusters. Furthermore, we discuss the challenges that are faced when employing NRVS to investigate large, multi-component metalloenzymatic systems, and outline the scope and limitations of current state-of-the-art theory in reproducing complex spectra