Homoprotocatechuate (HPCA) dioxygenases are enzymes that take part in the catabolism of aromatic compounds in the environment. They use molecular oxygen to perform the ring cleavage of ortho-dihydroxylated aromatic compounds. A theoretical investigation of the catalytic cycle for HPCA 2,3-dioxygenase isolated from Brevibacterium fuscum (Bf 2,3-HPCD) was performed using hybrid DFT with the B3LYP functional, and a reaction mechanism is suggested. Models of different sizes were built from the crystal structure of the enzyme and were used in the search for intermediates and transition states. It was found that the enzyme follows a reaction pathway similar to that for other non-heme iron dioxygenases, and for the manganese-dependent analog MndD, although with different energetics. The computational results suggest that the rate-limiting step for the whole reaction of Bf 2,3-HPCD is the protonation of the activated oxygen, with an energy barrier of 17.4 kcal/mol, in good agreement with the experimental value of 16 kcal/mol obtained from the overall rate of the reaction. Surprisingly, a very low barrier was found for the O-O bond cleavage step, 11.3 kcal/mol, as compared to 21.8 kcal/mol for MndD (sextet spin state). This result motivated additional studies of the manganese-dependent enzyme. Different spin coupling between the unpaired electrons on the metal and on the evolving substrate radical was observed for the two enzymes, and therefore the quartet spin state potential energy surface of the MndD reaction was studied. The calculations show a crossing between the sextet and the quartet surfaces, and it was concluded that a spin transition occurs and determines a barrier of 14.4 kcal/mol for the O-O bond cleavage, which is found to be the rate-limiting step in MndD. Thus the two 83% identical enzymes, using different metal ions as co-factors, were found to have similar activation energies (in agreement with experiment), but different rate-limiting steps.

Human homogentisate dioxygenase is an Fe(II)-dependent enzyme responsible for aromatic ring cleavage. The mechanism of its catalytic reaction has been investigated with the hybrid density functional method B3LYP. A relatively big model of the active site was first used to determine the substrate binding mode. It was found that binding of the substrate dianion with a vacant position trans to Glu341 is most favorable. The model was then truncated to include only the most relevant parts of the active-site residues involved in iron coordination and substrate binding. Thus, methylimidazole was used to model His292, His335, His365, and His371, while propionate modeled Glu341. The computational results suggest that the catalytic reaction of homogentisate dioxygenases involves three major chemical steps: formation of the peroxo intermediate, homolytic cleavage of the O-O bond leading to an arene oxide radical, and finally, cleavage of the six-membered ring. Calculated barriers for alternative reaction paths are markedly higher than for the proposed mechanism, and thus the computational results successfully explain the product specificity of the enzyme. Interestingly, the results indicate that the type of ring scission, intra or extra with respect to the substituents coordinating to iron, is controlled by the barrier heights for the decay of the arene oxide radical intermediate.

BackgroundDocking and scoring large libraries of ligands against target proteins forms the basis of structure-based virtual screening. The problem is trivially parallelizable, and calculations are generally carried out on computer clusters or on large workstations in a brute force manner, by docking and scoring all available ligands.ContributionIn this study we propose a strategy that is based on iteratively docking a set of ligands to form a training set, training a ligand-based model on this set, and predicting the remainder of the ligands to exclude those predicted as ‘low-scoring’ ligands. Then, another set of ligands are docked, the model is retrained and the process is repeated until a certain model efficiency level is reached. Thereafter, the remaining ligands are docked or excluded based on this model. We use SVM and conformal prediction to deliver valid prediction intervals for ranking the predicted ligands, and Apache Spark to parallelize both the docking and the modeling.ResultsWe show on 4 different targets that conformal prediction based virtual screening (CPVS) is able to reduce the number of docked molecules by 62.61% while retaining an accuracy for the top 30 hits of 94% on average and a speedup of 3.7. The implementation is available as open source via GitHub (https://github.com/laeeq80/spark-cpvs) and can be run on high-performance computers as well as on cloud resources.

A unified proteochemometric (PCM) model for the prediction of the ability of drug-like chemicals to inhibit five major drug metabolizing CYP isoforms (i.e. CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) was created and made publicly available under the Bioclipse Decision Support open source system at www.cyp450model.org. In regards to the proteochemometric modeling we represented the chemical compounds by molecular signature descriptors and the CYP-isoforms by alignment-independent description of composition and transition of amino acid properties of their protein primary sequences. The entire training dataset contained 63 391 interactions and the best PCM model was obtained using signature descriptors of height 1, 2 and 3 and inducing the model with a support vector machine. The model showed excellent predictive ability with internal AUC = 0.923 and an external AUC = 0.940, as evaluated on a large external dataset. The advantage of PCM models is their extensibility making it possible to extend our model for new CYP isoforms and polymorphic CYP forms. A key benefit of PCM is that all proteins are confined in one single model, which makes it generally more stable and predictive as compared with single target models. The inclusion of the model in Bioclipse Decision Support makes it possible to make virtual instantaneous predictions (∼100 ms per prediction) while interactively drawing or modifying chemical structures in the Bioclipse chemical structure editor.

The enzymatic ring-cleavage of catechol derivatives is catalyzed by two groups of dioxygenases, extradiol-and intradiol-cleaving dioxygenases. Although having a different oxidation state of their non-heme iron site and a different ligand coordination, both groups of enzymes involve a common peroxy intermediate in their catalytic cycle. The factors that lead to either extradiol cleavage resulting in 2-hydroxymuconaldehyde, or intradiol cleavage resulting in muconic acid, are not fully understood. Well characterized model compounds that mimic the functionality of these enzymes offer a basis for direct comparison to theoretical results. In this study the mechanism of a biomimetic iron complex is investigated with Density Functional Theory (DFT). This complex catalyzes the ring opening of catecholate with exclusive formation of the intradiol cleaved product. Several spin states are possible for the transition metal system, with the quartet state found to be of main importance during the reaction course. The mechanism investigated provides an explanation for the observed selectivity of the complex. First, a bridging peroxide is formed, which decomposes to an alkoxy-radical by O-O homolysis. In contrast to the subsequent barrier-free intradiol C-C bond cleavage, the extradiol pathway proceeds via the formation of an epoxide, which requires an additional activation barrier.