Flavonoids are a group of naturally occurring antioxidants, which over the past years have gained tremendous interest because of their possible therapeutic applicability. The mechanism of their antioxidant activity has been extensively studied over several decades. However, there is still much confusion about the molecular mechanism of radical scavenging and the relationship between structure and activity. Therefore, we have calculated the heat of formation and the geometry of both the parent compound and the corresponding radical using the ab initio program GAMESS. We have compared their differences in energy in order to gain insight into the stability of the radical and the ease with which it is formed. We have also investigated the spin density of the radical, to determine the delocalization possibilities. These calculated data were compared with experimental data from ESR (hyperfine coupling constants) and electrochemical oxidation (Ep/2) and were found to be in good agreement. By comparing the geometries of several flavonoids, we were able to explain the structural dependency of the antioxidant action of these compounds. The extremely good antioxidant activity of the flavonols could be explained by the formation of an intramolecular hydrogen bond.

Block of human ether-a-go-go related gene (HERG) Kϩ channels by a variety of medications has been linked to acquired long QT syndrome, a disorder of cardiac repolarization that predisposes to lethal arrhythmias. The drug-binding site is composed of residues that face into the central cavity of the channel. Two aromatic residues located on the S6 domain (Tyr652 and Phe656) are particularly important structural determinants of drug block. The role of pore helix residues (Thr623, Ser624, Val625) is less clear. In this study, we compared the pharmacological properties of two structurally related compounds, ibutilide and clofilium. Both compounds are charged amines with a single phenyl ring. Clofilium, a chlorobenzene derivative, is a potent blocker of HERG channels, but has a remarkably slower time course for recovery from block than ibutilide, a methanesulfonanilide. The difference in the rate of recovery from block can be explained simply by variation in drug trapping. There is little recovery from clofilium block with D540K HERG channels that permit untrapping at hyperpolarized potentials. Alanine-scanning mutagenesis of the S6 domain and a portion of the pore helix revealed that the binding site residues were the same for both compounds. However, S624A, located at the base of the pore helix, was the only HERG mutation that enabled rapid recovery from clofilium block. In summary, the pore helix residues are important components of the HERG drug binding site, and may be particularly important for drugs with polar substituents, such as a halogen (e.g., clofilium) or a methanesulfonamide (e.g., ibutilide).

A combined protein and pharmacophore model for cytochrome P450 2D6 (CYP2D6) has been derived using various computational chemistry techniques. A combination of pharmacophore modeling (using 40 substrates), protein modeling, and molecular orbital calculations was necessary to derive a model which incorporated steric, electronic, and chemical stability properties. The initial pharmacophore and protein models used to construct the combined model were derived independently and showed a high level of complementarity. The combined model is in agreement with experimental results concerning the substrates used to derive the model, with site-directed mutagenesis data available for the CYP2D6 protein, and takes into account the site-directed mutagenesis results for a variety of other 2-family P450s.

Cytochrome P450 enzymes (P450s) are important in drug metabolism and have been linked to adverse drug reactions. P450s display broad substrate reactivity, and prediction of metabolites is complex. QM/MM studies of P450 reactivity have provided insight into important details of the reaction mechanisms and have the potential to make predictions of metabolite formation. Here we present a comprehensive study of the oxidation of three widely used pharmaceutical compounds (S-ibuprofen, diclofenac, and S-warfarin) by one of the major drug-metabolizing P450 isoforms, CYP2C9. The reaction barriers to substrate oxidation by the iron-oxo species (Compound I) have been calculated at the B3LYP-D/CHARMM27 level for different possible metabolism sites for each drug, on multiple pathways. In the cases of ibuprofen and warfarin, the process with the lowest activation energy is consistent with the experimentally preferred metabolite. For diclofenac, the pathway leading to the experimentally observed metabolite is not the one with the lowest activation energy. This apparent inconsistency with experiment might be explained by the two very different binding modes involved in oxidation at the two competing positions. The carboxylate of diclofenac interacts strongly with the CYP2C9 Arg108 side chain in the transition state for formation of the observed metabolite—but not in that for the competing pathway. We compare reaction barriers calculated both in the presence and in the absence of the protein and observe a marked improvement in selectivity prediction ability upon inclusion of the protein for all of the substrates studied. The barriers calculated with the protein are generally higher than those calculated in the gas phase. This suggests that active-site residues surrounding the substrate play an important role in controlling selectivity in CYP2C9. The results show that inclusion of sampling (particularly) and dispersion effects is important in making accurate predictions of drug metabolism selectivity of P450s using QM/MM methods.

The ability to cross the blood brain barrier (BBB), sometimes expressed as BBB+ and BBB-, is a very important property in drug design. Several computational methods have been employed for the prediction of BBB-penetrating (BBB+) and nonpenetrating (BBB-) compounds with overall accuracies from 75 to 97%. However, most of these models use a large number of descriptors (67-199), and it is not easy to implement the models in order to predict values of BBB+/-. In this work, 19 simple molecular descriptors calculated from Algorithm Builder and fragmentation schemes were used for the analysis of 1593 BBB+/- data. The results show that hydrogen-bonding properties of compounds play a very important role in modeling BBB penetration. Several BBB models based on hydrogen-bonding properties, such as Abraham descriptors, polar surface area (PSA), and number of hydrogen bonding donors and acceptors, have been built using binomial-PLS analysis. The results show that the overall classification accuracy for a training set is over 90%, and overall prediction accuracy for a test set is over 95%.