Stewart B. Kirton

Prediction of binding modes for ligands in the cytochromes P450 and other heme-containing proteins

The cytochromes P450 (P450s) are a family of heme‐containing monooxygenase enzymes involved in a variety of functions, including the metabolism of endogenous and exogenous substances in the human body. During lead optimization, and in drug development, many potential drug candidates are rejected because of the affinity they display for drug‐metabolising P450s. Recently, crystal structures of human enzymes involved in drug metabolism have been determined, significantly augmenting the prospect of using structure‐based design to modulate the binding and metabolizing properties of compounds against P450 proteins. An important step in the application of structure‐based metabolic optimization is the accurate prediction of docking modes in heme binding proteins. In this paper we assess the performance of the docking program GOLD at predicting the binding mode of 45 heme‐containing complexes. We achieved success rates of 64% and 57% for Chemscore and Goldscore respectively; these success rates are significantly lower than the value of 79% observed with both scoring functions for the full GOLD validation set. Re‐parameterization of metal‐acceptor interactions and lipophilicity of planar nitrogen atoms in the scoring functions resulted in a significant increase in the percentage of successful dockings against the heme binding proteins (Chemscore 73%, Goldscore 65%). The modified scoring functions will be useful in docking applications on P450 enzymes and other heme binding proteins. Proteins 2005.

In silico methods for predicting ligand binding determinants of cytochromes P450.

A large number of computational methodologies have been used to predict, and thus help explain, the metabolism catalysed by the enzymes of the cytochrome P450 superfamily (P450s). A summary of the methodologies and resulting models is presented. This shows that investigations so far have focused on just a few of the many P450s, mainly those that are involved in drug metabolism. The models have evolved from simple comparisons of known substrates to more elaborate models requiring considerable computer power. These help to explain and, more importantly, predict the involvement of P450s in the metabolism of specific compounds.

Impact of incorporating the 2C5 crystal structure into comparative models of cytochrome P450 2D6

Cytochrome P450 2D6 (CYP2D6) metabolizes approximately one third of the drugs in current clinical use. To gain insight into its structure and function, we have produced four different sets of comparative models of 2D6: one based on the structures of P450s from four different microorganisms (P450 terp, P450 eryF, P450 cam, and P450 BM3), another on the only mammalian P450 (2C5) structure available, and the other two based on alternative amino acid sequence alignments of 2D6 with all five of these structures. Principal component analysis suggests that inclusion of the 2C5 crystal structure has a profound effect on the modeling process, altering the general topology of the active site, and that the models produced differ significantly from all of the templates. The four models of 2D6 were also used in conjunction with molecular docking to produce complexes with the substrates codeine and 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP); this identified Glu 216 [in the F‐helix; substrate recognition site (SRS) 2] as a key determinant in the binding of the basic moiety of the substrate. Our studies suggest that both Asp 301 and Glu 216 are required for metabolism of basic substrates. Furthermore, they suggest that Asp 301 (I‐helix, SRS‐4), a residue thought from mutagenesis studies to bind directly to the basic moiety of substrates, may play a key role in positioning the B′‐C loop (SRS‐1) and that the loss of activity on mutating Asp 301 may therefore be the result of an indirect effect (movement of the B′‐C loop) on replacing this residue. Proteins 2002;49:216–231.

Comparative modelling of cytochromes P450

The superfamily of enzymes known as the cytochromes P450 (P450s) comprises a wide-ranging class of proteins with diverse functions. They are known, amongst other things, to be involved in the hormonal regulation of metabolism and reproduction, as well as having a major clinical significance through their association with diseases such as cancer, diabetes and hepatitis. Knowledge of the three-dimensional (3D) structure of a protein gives insight into its function. The 3D structures of P450s are therefore of considerable scientific interest. A number of high-resolution structures of P450s have been determined by X-ray crystallography and studies of these structures have provided valuable insights into the mechanism of these enzymes. Only one of these structures is mammalian and as yet there is no structural information on human P450s in the public domain. Until such a structure is solved it is necessary to employ alternative methods to gain structural insight into how human P450s perform their biological function. Here we report on the use of comparative modelling to predict the structure of human P450s based on knowledge of their amino acid sequences plus the 3D structures of other (not human) P450s. As an illustrative example of these techniques we have modelled the structure of P450 2C5 using five bacterial P450 structures as templates. We examine the importance of selecting suitable templates, obtaining a good amino acid sequence alignment, and evaluating the models generated. To improve the quality of the models an iterative cycle of sequence alignment, model building, and model evaluation is employed. The result is a model with excellent stereochemistry, good amino acid side chain environment properties, and a Calpha trace similar to the crystal structure.

Revisiting the General Solubility Equation : In Silico Prediction of Aqueous Solubility Incorporating the Effect of Topographical Polar Surface Area

The General Solubility Equation (GSE) is a QSPR model based on the melting point and log P of a chemical substance. It is used to predict the aqueous solubility of nonionizable chemical compounds. However, its reliance on experimentally derived descriptors, particularly melting point, limits its applicability to virtual compounds. The studies presented show that the GSE is able to predict, to within 1 log unit, the experimental aqueous solubility (log S) for 81% of the compounds in a data set of 1265 diverse chemical structures (-8.48 < log S < 1.58). However, the predictive ability of the GSE is reduced to 75% when applied to a subset of the data (1160 compounds -6.00 < log S < 0.00), which discounts those compounds occupying the sparsely populated regions of data space. This highlights how sparsely populated extremities of data sets can significantly skew results for linear regression-based models. Replacing the melting point descriptor of the GSE with a descriptor which accounts for topographical polar surface area (TPSA) produces a model of comparable quality to the GSE (the solubility of 81% of compounds in the full data set predicted accurately). As such, we propose an alternative simple model for predicting aqueous solubility which replaces the melting point descriptor of the GSE with TPSA and hence can be applied to virtual compounds. In addition, incorporating TPSA into the GSE in addition to log P and melting point gives a three descriptor model that improves accurate prediction of aqueous solubility over the GSE by 5.1% for the full and 6.6% for the reduced data set, respectively.

Objective Structured Clinical Examinations (OSCEs) compared With traditional assessment methods

Objectives. To compare objective structured clinical examinations (OSCEs) and traditional assessment methods among recent pharmacy graduates. Methods. Individual student performance in OSCEs was compared with performance on traditional pharmacy-practice examinations at the same level of program study. Results. A moderate correlation was found between individual attainment in OSCE examinations and on traditional pharmacy practice examinations at the same level. Conclusions. OSCEs add value to traditional methods of assessment because the 2 evaluation methods measure different competencies.

De novo ligand design to partially flexible active sites : Application of the Reflex algorithm to carboxypeptidase A, acetylcholinesterase, and the estrogen receptor

Reflex is a recent algorithm in the de novo ligand design software, SkelGen, that allows the flexibility of amino acid side chains in a protein to be taken into account during the drug-design process. In this paper the impact of flexibility on the solutions generated by the de novo design algorithm, when applied to carboxypeptidase A, acetylcholinesterase, and the estrogen receptor (ER), is investigated. The results for each of the targets indicate that when allowing side-chain movement in the active site, solutions are generated that were not accessible from the multiple static protein conformations available for these targets. Furthermore, an analysis of structures generated in a flexible versus a static ER active site suggests that these additional solutions are not merely noise but contain many interesting chemotypes.

SkelGen: a general tool for structure-based de novo ligand design

The recent lapse in productivity in the pharmaceutical industry has facilitated the emergence of experimental and in silico structure-based design methodologies, based on identification of biologically active low molecular weight fragments that can be exploited to produce potential drug candidates with diverse chemistries. SkelGen, an in silico example of this methodology, is reviewed. The ability of this algorithm to identify chemically diverse low molecular weight fragments that would potentially bind to DNA gyrase is recounted, as is the first purely de novo structure-based design of five compounds that show at least micromolar activity against the estrogen receptor. The ability of the algorithm to incorporate partial protein flexibility during its design of compounds to the estrogen receptor is discussed, and an opinion as to the near and long-term futures for de novo design algorithms is expressed.

New inhibitor targeting human transcription factor HSF1: effects on the heat shock response and tumor cell survival

Abstract Comparative modeling of the DNA-binding domain of human HSF1 facilitated the prediction of possible binding pockets for small molecules and definition of corresponding pharmacophores. In silico screening of a large library of lead-like compounds identified a set of compounds that satisfied the pharmacophoric criteria, a selection of which compounds was purchased to populate a biased sublibrary. A discriminating cell-based screening assay identified compound 001, which was subjected to systematic analysis of structure–activity relationships, resulting in the development of compound 115 (IHSF115). IHSF115 bound to an isolated HSF1 DNA-binding domain fragment. The compound did not affect heat-induced oligomerization, nuclear localization and specific DNA binding but inhibited the transcriptional activity of human HSF1, interfering with the assembly of ATF1-containing transcription complexes. IHSF115 was employed to probe the human heat shock response at the transcriptome level. In contrast to earlier studies of differential regulation in HSF1-naïve and -depleted cells, our results suggest that a large majority of heat-induced genes is positively regulated by HSF1. That IHSF115 effectively countermanded repression in a significant fraction of heat-repressed genes suggests that repression of these genes is mediated by transcriptionally active HSF1. IHSF115 is cytotoxic for a variety of human cancer cell lines, multiple myeloma lines consistently exhibiting high sensitivity.

Intended and Unintended Use of Cathinone Mixtures

Cathinones are one of the most popular categories of new psychoactive substances (NPS) consumed. Cathinones have different pharmacological activities and receptor selectivity for monoamine transporters based on their chemical structures. They are incorporated into NPS mixtures and used with other NPS or ‘traditional’ drugs. Cathinone use represents significant health risks to individuals and is a public health burden.