Homology modeling and molecular dynamics of CYP1A1 and CYP2B1 to explore the metabolism of aryl derivatives by docking and experimental assays

Structure-Based Drug Design for Cytochrome P450 Family 1 Inhibitors

Cytochromes P450 are a class of metalloproteins which are responsible for electron transfer in a wide spectrum of reactions including metabolic biotransformation of endogenous and exogenous substrates. The superfamily of cytochromes P450 consists of families and subfamilies which are characterized by a specific structure and substrate specificity. Cytochromes P450 family 1 (CYP1s) play a distinctive role in the metabolism of drugs and chemical procarcinogens. In recent decades, these hemoproteins have been intensively studied with the use of computational methods which have been recently developed remarkably to be used in the process of drug design by the virtual screening of compounds in order to find agents with desired properties. Moreover, the molecular modeling of proteins and ligand docking to their active sites provide an insight into the mechanism of enzyme action and enable us to predict the sites of drug metabolism. The review presents the current status of knowledge about the use of the computational approach in studies of ligand-enzyme interactions for CYP1s. Research on the metabolism of substrates and inhibitors of CYP1s and on the selectivity of their action is particularly valuable from the viewpoint of cancer chemoprevention, chemotherapy, and drug-drug interactions.

Analysis of Species-Selectivity of Human, Mouse and Rat Cytochrome P450 1A and 2B Subfamily Enzymes using Molecular Modeling, Docking and Dynamics Simulations

Cytochrome P450 (CYP) 1A and 2B subfamily enzymes are important drug metabolizing enzymes, and are highly conserved across species in terms of sequence homology. However, there are major to minor structural and macromolecular differences which provide for species-selectivity and substrate-selectivity. Therefore, species-selectivity of CYP1A and CYP2B subfamily proteins across human, mouse and rat was analyzed using molecular modeling, docking and dynamics simulations when the chiral molecules quinine and quinidine were used as ligands. The three-dimensional structures of 17 proteins belonging to CYP1A and CYP2B subfamilies of mouse and rat were predicted by adopting homology modeling using the available structures of human CYP1A and CYP2B proteins as templates. Molecular docking and dynamics simulations of quinine and quinidine with CYP1A subfamily proteins revealed the existence of species-selectivity across the three species. On the other hand, in the case of CYP2B subfamily proteins, no role for chirality of quinine and quinidine in forming complexes with CYP2B subfamily proteins of the three species was indicated. Our findings reveal the roles of active site amino acid residues of CYP1A and CYP2B subfamily proteins and provide insights into species-selectivity of these enzymes across human, mouse, and rat.

Drug Metabolism in Preclinical Drug Development: A Survey of the Discovery Process, Toxicology, and Computational Tools

BACKGROUND

While establishing efficacy in translational models and humans through clinically-relevant endpoints for disease is of great interest, assessing the potential toxicity of a putative therapeutic drug is critical. Toxicological assessments in the pre-clinical discovery phase help to avoid future failure in the clinical phases of drug development. Many in vitro assays exist to aid in modular toxicological assessment, such as hepatotoxicity and genotoxicity. While these methods have provided tremendous insight into human toxicity by investigational new drugs, they are expensive, require substantial resources, and do not account for pharmacogenomics as well as critical ADME properties. Computational tools can fill this niche in toxicology if in silico models are accurate in relating drug molecular properties to toxicological endpoints as well as reliable in predicting important drug-target interactions that mediate known adverse events or adverse outcome pathways (AOPs).

METHODS

We undertook an unstructured search of multiple bibliographic databases for peer-reviewed literature regarding computational methods in predictive toxicology for in silico drug discovery. As this review paper is meant to serve as a survey of available methods for the interested reader, no focused criteria were applied. Literature chosen was based on the writers' expertise and intent in communicating important aspects of in silico toxicology to the interested reader.

CONCLUSION

This review provides a purview of computational methods of pre-clinical toxicologic assessments for novel small molecule drugs that may be of use for novice and experienced investigators as well as academic and commercial drug discovery entities.

A study of the structural properties and thermal stability of human Bcl-2 by molecular dynamics simulations

The anti-apoptotic B-cell lymphoma 2 (Bcl-2) protein interacts with several proteins that regulate the apoptotic properties of cells. In this research, we conduct several all-atom molecular dynamics (MD) simulations under high-temperature unfolding conditions, from 400 to 800 K, for 25 ns. These simulations were performed using a model of an engineered Bcl-2 human protein (Bcl-2-Δ22Σ3), which lacks 22 C-terminal residues of the transmembrane domain. The aim of this study is to gain insight into the structural behavior of Bcl-2-Δ22Σ3 by mapping the conformational movements involved in Bcl-2 stability and its biological function. To build a Bcl-2-Δ22Σ3 three-dimensional model, the protein core was built by homology modeling and the flexible loop domain (FLD, residues 33-91) by ab initio methods. Further, the entire protein model was refined by MD simulations. Afterwards, the production MD simulations showed that the FLD at 400 and 500 K has several conformations reaching into the protein core, whereas at 600 K some of the alpha-helices were lost. At 800 K, the Bcl-2 core is destabilized suggesting a possible mechanism for protein unfolding, where the alpha helices 1 and 6 were the most stable, and a reduction in the number of hydrogen bonds initially occurs. In conclusion, the structural changes and the internal protein interactions suggest that the core and the FLD are crucial components of Bcl-2 in its function of regulate ng access to the recognition sites of kinases and caspases.

Cytochrome P450 1A1-mediated anticancer drug discovery: in silico findings

INTRODUCTION

Target-specific drugs may offer fewer side/adverse effects in comparison with other anticancer agents and thus save normal healthy cells to a greater extent. The selective overexpression of cytochrome P450 1A1 (CYP1A1) in tumor cells induces the metabolism of benzothiazole and aminoflavone compounds to their reactive species, which are responsible for DNA adduct formation and cell death. This review encompasses the novelty of CYP1A1 as an anticancer drug target and explores the possible in silico strategies that would be applicable in the discovery and development of future antitumor compounds.

AREAS COVERED

This review highlights the various ligand-based and target-based in silico methodologies that were efficiently used in exploration of CYP1A1 as a novel antitumor target. These methodologies include electronic structure analysis, CoMFA studies, homology modeling, molecular docking, molecular dynamics analysis, pharmacophore mapping and quantitative structure activity relationship (QSAR) studies. It also focuses on the various approaches used in the development of the lysyl amide prodrug of 5F-203 (NSC710305) and dimethanesulfonate salt of 5-aminoflavone (NSC710464) as clinical candidates from their less potent analogues.

EXPERT OPINION

Selective overexpression of CYP1A1 in cancer cells offers tumor-specific drug design to ameliorate the current adverse effects associated with existing antitumor agents. Medicinal chemistry and in vitro driven approaches, in combination with knowledge-based drug design and by using the currently available tools of in silico methodologies, would certainly make it possible to design and develop novel anticancer compounds targeting CYP1A1.

7-Ethynylcoumarins: selective inhibitors of human cytochrome P450s 1A1 and 1A2

To discover new selective mechanism-based P450 inhibitors, eight 7-ethynylcoumarin derivatives were prepared through a facile two-step synthetic route. Cytochrome P450 activity assays indicated that introduction of functional groups in the backbone of coumarin could enhance the inhibition activities toward P450s 1A1 and 1A2, providing good selectivity against P450s 2A6 and 2B1. The most potent product 7-ethynyl-3,4,8-trimethylcoumarin (7ETMC) showed IC(50) values of 0.46 μM and 0.50 μM for P450s 1A1 and 1A2 in the first six minutes, respectively, and did not show any inhibition activity for P450s 2A6 and 2B1 even at the dose of 50 μM. All of the inhibitors except 7-ethynyl-3-methyl-4-phenylcoumarin (7E3M4PC) showed mechanism-based inhibition of P450s 1A1 and 1A2. In order to explain this mechanistic difference in inhibitory activities, X-ray crystallography data were used to study the difference in conformation between 7E3M4PC and the other compounds studied. Docking simulations indicated that the binding orientations and affinities resulted in different behaviors of the inhibitors on P450 1A2. Specifically, 7E3M4PC with its two-plane structure fits into the P450 1A2's active site cavity with an orientation leading to no reactive binding, causing it to act as a competitive inhibitor.

Docking and QSAR comparative studies of polycyclic aromatic hydrocarbons and other procarcinogen interactions with cytochromes P450 1A1 and 1B1

To obtain chemical clues on the process of bioactivation by cytochromes P450 1A1 and 1B1, some QSAR studies were carried out based on cellular experiments of the metabolic activation of polycyclic aromatic hydrocarbons and heterocyclic aromatic compounds by those enzymes. Firstly, the 3D structures of cytochromes 1A1 and 1B1 were built using homology modelling with a cytochrome 1A2 template. Using these structures, 32 ligands including heterocyclic aromatic compounds, polycyclic aromatic hydrocarbons and corresponding diols, were docked with LigandFit and CDOCKER algorithms. Binding mode analysis highlighted the importance of hydrophobic interactions and the hydrogen bonding network between cytochrome amino acids and docked molecules. Finally, for each enzyme, multilinear regression and artificial neural network QSAR models were developed and compared. These statistical models highlighted the importance of electronic, structural and energetic descriptors in metabolic activation process, and could be used for virtual screening of ligand databases. In the case of P450 1A1, the best model was obtained with artificial neural network analysis and gave an r (2) of 0.66 and an external prediction [Formula: see text] of 0.73. Concerning P450 1B1, artificial neural network analysis gave a much more robust model, associated with an r (2) value of 0.73 and an external prediction [Formula: see text] of 0.59.

Factors affecting phase I stereoselective biotransformation of chiral polychlorinated biphenyls by rat cytochrome P-450 2B1 isozyme

In vitro incubations of rat cytochrome P-450 (CYP) 2B1 isozyme with three chiral polychlorinated biphenyl (PCB) congeners (PCBs 45, 95, and 132) were performed to investigate factors affecting phase I stereoselective biotransformation. Rat CYP2B1 preferentially biotransformed the second-eluting atropisomers of PCBs 45 and 95 at low substrate concentration ranges (≤15 μM). Biotransformation competition by different congeners was also observed, with increasing competition at higher chlorination. Competition decreased the biotransformation rates of each congener stereoselectively, affecting atropisomeric composition. No atropisomeric enrichment was observed for PCB 132 upon incubation of the racemate. However, under the same conditions, significant differences in biotransformation kinetics were observed in individual atropisomer incubations, indicating that (+)-PCB 132 and (-)-PCB 132 were competitively biotransformed. Homology modeling and docking studies suggested that each atropisomer had different interactions with rat CYP2B1 and could dock with the isozyme at different locations. This is one possible explanation for stereoselective biotransformation and competition of chiral PCBs at the molecular level. Our results suggest that the lack of predictive capability for stereoselectivity of PCBs and other chiral pollutants in biota may be due to competitive and/or inhibitory activities of different substrates, including individual enantiomers of the same compound.

The effects of nitrogen-heme-iron coordination on substrate affinities for cytochrome P450 2E1

A descriptor based computational model was developed for cytochrome P450 2E1 (CYP2E1) based on inhibition constants determined for inhibition of chlorzoxazone, or 4-nitrophenol, metabolism. An empirical descriptor for type II binding was developed and tested for a series of CYP2E1 inhibitors. Inhibition constants where measured for 51 different compounds. A fast 2-dimensional predictive model was developed based on 40 compounds, and tested on 8 compounds of diverse structure. The trained model (n=40) had an r(2) value of 0.76 and an RMSE of 0.48. The correlation between the predicted and actual pK(i) values of the test set of compounds not included in the model gives an r(2) value of 0.78. The features that described binding include heme coordination (type II binding), molecular volume, octanol/water partition coefficient, solvent accessible surface area, and the sum of the atomic polarizabilities. The heme coordination parameter assigns an integer between 0 and 6 depending on structure, and is a new descriptor, based on simple quantum chemical calculations with correction for steric effects. The type II binding parameter was found to be important in obtaining a good correlation between predicted and experimental inhibition constants increasing the r(2) value from 0.38 to 0.77.