No abstract

Machine learning models for site of metabolism (SoM) prediction offer the ability to identify metabolic soft spots in low-molecular-weight drug molecules at low computational cost and enable data-based reactivity prediction. SoM prediction is an atom classification problem. Successful construction of machine learning models requires atom representations that capture the reactivity-determining features of a potential reaction site. We have developed a descriptor scheme that characterizes an atom's steric and electronic environment and its relative location in the molecular structure. The partial charge distributions were obtained from fast quantum mechanical calculations. We successfully trained machine learning classifiers on curated cytochrome P450 metabolism data. The models based on the new atom descriptors showed sustained accuracy for retrospective analyses of metabolism optimization campaigns and lead optimization projects from Bayer Pharmaceuticals. The results obtained demonstrate the practicality of quantum-chemistry-supported machine learning models for hit-to-lead optimization.

Oxygen activation at the active sites of [FeFe] hydrogenases has been proposed to be the initial step of irreversible oxygen-induced inhibition of these enzymes. On the basis of a first theoretical study into the thermodynamics of O2 activation [Inorg. Chem. 2009, 48, 7127] we here investigate the kinetics of possible reaction paths at the distal iron atom of the active site by means of density functional theory. A sequence of steps is proposed to either form a reactive oxygen species (ROS) or fully reduce O2 to water. In this reaction cascade, two branching points are identified where water formation directly competes with harmful oxygen activation reactions. The latter are water formation by O-O bond cleavage of a hydrogen peroxide-bound intermediate competing with H2O2 dissociation and CO2 formation by a putative iron-oxo species competing with protonation of the iron-oxo species to form a hydroxyo ligand. Furthermore, we show that proton transfer to activated oxygen is fast and that proton supply to the active site is vital to prevent ROS dissociation. If sufficiently many reduction equivalents are available, oxygen activation reactions are accelerated, and oxygen reduction to water becomes possible.

When investigating the mode of hydrogen activation by [Fe] hydrogenases, not only the chemical reactivity at the active site is of importance but also the large-scale conformational change between the so-called open and closed conformations, which leads to a special spatial arrangement of substrate and iron cofactor. To study H2 activation, a complete model of the solvated and cofactor-bound enzyme in complex with the substrate methenyl-H4MPT + was constructed. Both the closed and open conformations were simulated with classical molecular dynamics on the 100 ns time scale. Quantum-mechanics/molecular-mechanics calculations on snapshots then revealed the features of the active site that enable the facile H2 cleavage. The hydroxyl group of the pyridinol ligand can easily be deprotonated. With the deprotonated hydroxyl group and the structural arrangement in the closed conformation, H2 coordinated to the Fe center is subject to an ionic and orbital push-pull effect and can be rapidly cleaved with a concerted hydride transfer to methenyl-H4MPT

[Fe] hydrogenase is a hydrogen activating enzyme that features a monoiron active site, which can be well characterized by Mössbauer spectroscopy. Mössbauer spectra have been measured of the CO and CN(-) inhibited species as well as under turnover conditions [Shima, S. et al., J. Am. Chem. Soc., 2005, 127, 10430]. This study presents calculated Mössbauer parameters for various active-site models of [Fe] hydrogenase to provide structural information about the species observed in experiment. Because theoretical Mössbauer spectroscopy requires the parametrization of observables from first-principles calculations (i.e., electric-field gradients and contact densities) to the experimental observables (i.e., quadrupole splittings and isomer shifts), nonrelativistic and relativistic density functional theory methods are parametrized against a reference set of Fe complexes specifically selected for the application to the Fe center in [Fe] hydrogenase. With this methodology, the measured parameters for the CO and CN(-) inhibited complexes can be reproduced. Evidence for the protonation states of the hydroxyl group in close proximity to the active site and for the thiolate ligand, which could participate in proton transfer, is obtained. The unknown resting state measured in the presence of the substrate and under pure H2 atmosphere is identified to be a water-coordinated complex. Consistent with previous assignments based on infrared and X-ray absorption near-edge spectroscopy, all measured Mössbauer data can be reproduced with the active site's iron atom being in oxidation state +2.