The CO₂ reduction electrocatalyst [Fe₄N(CO)₁₂]^- (abbrev. 1^-) reduces CO₂ to HCO₂^- in a two-electron, one-proton catalytic cycle. Here, we employ ab initio calculations to estimate the first two redox potentials of 1^- and explore the pathway of a side reaction involving CO dissociation from 1^3-. Using the BP86 density functional approximation, the redox potentials were computed with a root mean squared error of 0.15 V with respect to experimental data. High temperature Born-Oppenheimer molecular dynamics was employed to discover a reaction pathway of CO dissociation from 1^3- with a reaction energy of +10.6 kcal mol^-1 and an activation energy of 18.8 kcal mol^-1; including harmonic free energy terms, this yields ΔG_sep = 1.4 kcal mol^-1 for fully separated species and ΔG^‡ = +17.4 kcal mol^-1, indicating CO dissociation is energetically accessible at ambient conditions. The analogous dissociation pathway from 1^2- has a reaction energy of 22.1 kcal mol^-1 and an activation energy of 22.4 kcal mol^-1 (ΔG_sep = 12.8 kcal mol^-1, ΔG^‡ = +18.1 kcal mol^-1). Our computed harmonic vibrational analysis of [Fe₄N(CO)₁₁]^3- or 2^3- reveals a distinct CO-stretching peak red-shifted from the main CO-stretching band, pointing to a possible vibrational signature of dissociation. Multi-reference CASSCF calculations are used to check the assumptions of the density functional approximations that were used to obtain the majority of the results.

Ab initio molecular dynamics is able to predict novel reaction mechanisms by directly observing the individual reaction events that occur in simulation trajectories. In this article, we describe an approach for detecting reaction events from simulation trajectories using a physically motivated model based on time series analysis of ab initio bond orders. We found that applying a threshold to the bond order was insufficient for accurate detection, whereas peak finding on the first time derivative resulted in significantly improved accuracy. The model is trained on a reference set of reaction events representing the ideal result given unlimited computing resources. Our study includes two model systems: a heptanylium carbocation that undergoes hydride shifts and an unsaturated iron carbonyl cluster that features CO ligand migration and bridging behavior. The results indicate a high level of promise for this analysis approach to be used in mechanistic analysis of reactive AIMD simulations more generally.

Putidaredoxin (Pdx) is the exclusive reductase and a structural effector for P450cam (CYP101A1). However, the mechanism of how Pdx modulates the conformational states of P450cam remains elusive. Here we report a putative communication pathway for the Pdx-induced conformational change in P450cam using results of double electron-electron resonance (DEER) spectroscopy and molecular dynamics simulations. Use of solution state DEER measurements allows us to observe subtle conformational changes in the internal helices in P450cam among closed, open, and P450cam-Pdx complex states. Molecular dynamics simulations and dynamic network analysis suggest that Pdx binding is coupled to small coordinated movements of several regions of P450cam, including helices C, B', I, G, and F. These changes provide a linkage between the Pdx binding site on the proximal side of the enzyme and helices F/G on the distal side and the site of the largest movement resulting from the Pdx-induced closed-to-open transition. This study provides a detailed rationale for how Pdx exerts its long-recognized effector function at the active site from its binding site on the opposite face of the enzyme.

The parameterization of torsional/dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields. Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms. To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values. However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses. In this paper, we propose a systematic and versatile workflow called TorsionDrive to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development. The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described. The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.

Phosphorylation is crucial in regulating various biological processes. However, comprehensive phosphoproteomic profiling in the termination of liver regeneration (LR) is still missing. Here, we used Tandem Mass Tag (TMT) labeling coupled with phosphopeptide enrichment and two-dimensional (2D) liquid chromatography-mass spectrometry (LC-MS)/MS analysis to establish a global phosphoproteomic map in the liver of mice at day 5 after partial hepatectomy (PH). Altogether, 9731 phosphosites from 3443 proteins were identified and 7802 phosphosites from 2980 proteins were quantified. Motif analysis of the identified phosphosites revealed a diverse array of consensus sequences, suggesting that multiple kinase families including ERK/MAPK, PKA/PKC, CaMK-II, CKII, and CDK may be involved in the termination of LR. Functional clustering analysis of proteins with dysregulated phosphosites showed that they mainly participate in metabolic pathways, DNA replication, and tight junction. More importantly, the deletion of PP2Acα in the liver remarkably changes the overall phosphorylation profile, indicating its critical role in regulating the termination of LR. Finally, several differentially phosphorylated sites were validated by co-immunoprecipitation and Western blot. Taken together, our data unravel the first comprehensive phosphoproteomic map in the termination of LR in mice, which greatly expands our knowledge in the complicated regulation of this process and provides new directions for the treatment of liver cancer using liver resection.

We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small-molecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein-ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entirely new force field with minimal human intervention.