Ismael Zamora

pH-dependent bidirectional transport of weakly basic drugs across Caco-2 monolayers: implications for drug-drug interactions.

AbstractPurpose. The purpose of this study was to investigate the pH-dependent passive and active transport of weakly basic drugs across the human intestinal epithelium. Methods. The bidirectional pH-dependent transport of weak bases was studied in Caco-2 cell monolayers in the physiologic pH range of the gastrointestinal tract. Results. A net secretion of atenolol and metoprolol was observed when a pH gradient was applied. However, the bidirectional transport of both compounds was equal in the nongradient system. Hence, at lower apical than basolateral pH a change in passive transport caused by an imbalance in the concentration of the uncharged drug species resulted in a “false” asymmetry (efflux ratio). Furthermore, a mixture of pH-dependent passive and active efflux was found for the P-glycoprotein (P-gp, MDR1, ABCB1) substrates, talinolol and quinidine, but not for the neutral drug, digoxin. However, the clinically important digoxin-quinidine interaction depended on the presence of a pH gradient. Hence, the degree of interaction depends on the amount of quinidine available at the binding site of the P-gp. Conclusions. Active efflux of weak bases can only be accounted for when the fraction of unionized drug species is equal in all compartments because the transport is biased by a pH-dependent passive component. However, this component may take part in vivo and contribute to drug-drug interactions involving P-gp.

COMPARISON OF METHODS FOR THE PREDICTION OF THE METABOLIC SITES FOR CYP3A4-MEDIATED METABOLIC REACTIONS

Predictions of the metabolic sites for new chemical entities, synthesized or only virtual, are important in the early phase of drug discovery to guide chemistry efforts in the synthesis of new compounds with reduced metabolic liability. This information can now be obtained from in silico predictions, and therefore, a thorough and unbiased evaluation of the computational techniques available is needed. Several computational methods to predict the metabolic hot spots are emerging. In this study, metabolite identification using MetaSite and a docking methodology, GLUE, were compared. Moreover, the published CYP3A4 crystal structure and computed CYP3A4 homology models were compared for their usefulness in predicting metabolic sites. A total of 227 known CYP3A4 substrates reported to have one or more metabolites adding up to 325 metabolic pathways were analyzed. Distance-based fingerprints and four-point pharmacophore derived from GRID molecular interaction fields were used to characterize the substrate and protein in MetaSite and the docking methodology, respectively. The CYP3A4 crystal structure and homology model with the reactivity factor enabled achieved a similar prediction success (78%) using the MetaSite method. The docking method had a relatively lower prediction success (∼57% for the homology model), although it still may provide useful insights for interactions between ligand and protein, especially for uncommon reactions. The MetaSite methodology is automated, rapid, and has relatively accurate predictions compared with the docking methodology used in this study.

Enhanced metabolite identification with MSE and a semi-automated software for structural elucidation

The identification of metabolites is almost exclusively done with liquid chromatography/tandem mass spectrometry (LC/MSMS) and despite the enormous progress in the development of these techniques and software for handling of data this is a time-consuming task. In this study the use of quadrupole time-of-flight (QTOF)-generated MS(E) and MS/MS data were compared with respect to rationalization of metabolites. In addition Mass-MetaSite, a semi-automated software for metabolite identification, was evaluated. The program combines the information from MS raw data, in the form of collision-induced dissociation spectra, with a prediction of the site of metabolism in order to assign the structure of a metabolite. The aim of the software is to mimic the rationalization of fragment ions performed by a biotransformation scientist in the process of structural elucidation. For this evaluation, metabolite identification in human liver microsomes was accomplished for 19 commercially available compounds and 15 in-house compounds. The results were very encouraging and for 96% of the metabolites the same structures were assigned using MS(E) compared with MSMS acquired data. The possibility of using MS(E) could considerably reduce the analysis time. Moreover, Mass-MetaSite performed well and the correct assigned structure, compared to manual inspection of the data, was picked in the first rank in ∼80% of the cases. In conclusion MS(E) could be successfully used for metabolite identification in order to reduce time of analysis and Mass-MetaSite could alleviate the work of a biotransformation scientist and decrease the workload by assigning the structure for a majority of the metabolites.

Brassinosteroids: A new way to define the structural requirements

Abstract The synthesis of four new brassinosteroid analogs is reported. Two of them elicited high activity as plant growth promoters. Also a new way to define the structural requirements, that can explain the relative high activity of these compounds, is presented.

Impact of Extracellular Protein Binding on Passive and Active Drug Transport Across Caco-2 Cells

AimThe objective of the study is to evaluate the mechanism behind alterations in passive and active transport of drugs in the presence of basolaterally applied extracellular protein using the Caco-2 cell model.MethodsThe permeation across Caco-2 monolayers of two groups of compounds, transported either solely by passive diffusion or partly also by active transport in the secretory direction, was studied at two donor concentrations in the absence or presence of bovine serum albumin (BSA, 0–4%). Each group contained compounds with high or low protein binding (PB) capabilities and high or low absorption in humans (fraction absorbed, fa). The unbound fraction (fu) of each compound was determined by ultrafiltration.ResultsThe transport rate of the passively permeating compounds was the same in both apical-to-basolateral (absorptive) and basolateral-to-apical (secretory) directions in the absence of BSA. Basolaterally applied BSA increased the transport rate in the absorptive direction and decreased it in the secretory direction for all compounds, in direct proportion to the extent of PB. The efflux ratios for the actively transported compounds were reduced in the presence of BSA.ConclusionsBasolaterally applied BSA, which mimics in vivo PB, alters both passive and active drug transport in the Caco-2 cell model. Using Cu in the calculations of transport rate allowed elucidation of the different mechanisms behind these alterations. Our data also suggest that active secretory transport for highly protein-bound compounds might have less effect in vivo than predicted from traditional Caco-2 cell models (without BSA).

Virtual Screening and Scaffold Hopping Based on GRID Molecular Interaction Fields

In this study, a set of strategies for structure-based design using GRID molecular interaction fields (MIFs) to derive a pharmacophoric representation of a protein is reported. Thrombin, one of the key enzymes involved in the blood coagulation cascade, was chosen as the model system since abundant published experimental data are available related to both crystal structures and structurally diverse sets of inhibitors. First, a virtual screening methodology was developed either using a pharmacophore representation of the protein based on GRID MIFs or using GRID MIFs from the 3D structure of a set of chosen thrombin inhibitors. The search was done in a 3D multiconformation version of the Available Chemical Directory (ACD) database, which had been spiked with 262 known thrombin inhibitors (multiple conformers available per compound). The model managed to find 80% of the known thrombin inhibitors among the 74,291 conformers in the ACD by only searching 5% of the database; hence, a 15-fold enrichment of the library was achieved. Second, a scaffold hopping methodology was developed using GRID MIFs, giving the scaffold interaction pattern and the shape of the scaffold, together with the distance between the anchor points. The scaffolds reported by Dolle in the Journal of Combinatorial Chemistry summaries (2000 and 2001) and scaffolds built or derived from ligands cocomplexed with the thrombin enzyme were parameterized using a new set of descriptors and saved into a searchable database. The scaffold representation from the database was then compared to a template scaffold (from a thrombin crystal structure), and the thrombin-derived scaffolds included in the database were found among the top solutions. To validate the usefulness of the methodology to replace the template scaffold, the entire molecule was built (scaffold and side chains) and the resulting compounds were docked into the active site of thrombin. The docking solutions showed the same binding pattern as the cocomplexed compound, hence, showing that this method can be a valuable tool for medicinal chemists to select interchangeable core structures (scaffolds) in an easy manner and retaining the binding properties from the original ligand.

Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates.

AbstractA number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds. Abbreviations: ADME – absorption, distribution, metabolism and excretion; CYP – cytochrome P450; MIFs – molecular interaction fields; HTS – high throughput screening; DDI – drug-drug interactions; 3D – three-dimensional; PCA – principal components analysis; CPCA – consensus principal components analysis; PLS – partial least squares; PLSD – partial least squares discriminant; GRIND – grid independent descriptors; GRID – software originally created and developed by Professor Peter Goodford.

Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors

This study describes the use of alignment-independent descriptors for obtaining qualitative and quantitative predictions of the competitive inhibition of CYP2C9 on a serie of highly structurally diverse compounds. This was accomplished by calculating alignment independent descriptors in ALMOND. These GRid INdependent Descriptors (GRIND) represent the most important GRID-interactions as a function of the distance instead of the actual position of each grid-point. The experimental data was determined under uniform conditions. The inhibitor data set consists of 35 structurally diverse competitive stereospecific inhibitors of the cytochrome P450 2C9 and the non -inhibitor data set of 46 compounds. In a PLS discriminant analysis 21 inhibitors and 21 non-inhibitors (1 and 0 as activities) were analyzed using the ALMOND program obtaining a model with an r2 of 0.74 and a cross-validation value (q2) of 0.64. The model was externally validated with 39 compounds (14 inhibitors/25 non-inhibitors). 74% of the compounds were correctly predicted and an additional 13% was assigned to a borderline cluster. Thereafter, a model for quantitative predictions was generated by a PLS analysis of the GRIND descriptors using the experimental Ki-value for 21 of the competitive inhibitors (r2=0.77, q2=0.60). The model was externally validated using 12 compounds and predicted 11 out of 12 of the Ki-values within 0.5 log units. The discriminant model will be useful in screening for CYP2C9 inhibitors from large compound collections. The 3D-QSAR model will be used during lead optimization to avoid chemistry that result in inhibition of CYP2C9.

Suitability of GRIND-Based Principal Properties for the Description of Molecular Similarity and Ligand-Based Virtual Screening

The information provided by the alignment-independent GRid Independent Descriptors (GRIND) can be condensed by the application of principal component analysis, obtaining a small number of principal properties (GRIND-PP), which is more suitable for describing molecular similarity. The objective of the present study is to optimize diverse parameters involved in the obtention of the GRIND-PP and validate their suitability for applications, requiring a biologically relevant description of the molecular similarity. With this aim, GRIND-PP computed with a collection of diverse settings were used to carry out ligand-based virtual screening (LBVS) on standard conditions. The quality of the results obtained was remarkable and comparable with other LBVS methods, and their detailed statistical analysis allowed to identify the method settings more determinant for the quality of the results and their optimum. Remarkably, some of these optimum settings differ significantly from those used in previously published applications, revealing their unexplored potential. Their applicability in large compound database was also explored by comparing the equivalence of the results obtained using either computed or projected principal properties. In general, the results of the study confirm the suitability of the GRIND-PP for practical applications and provide useful hints about how they should be computed for obtaining optimum results.

The challenges of in silico contributions to drug metabolism in lead optimization

Importance of the field: The site of metabolism (SOM) predictions by CYP 3A4 are extremely important during the drug discovery process especially during the lead discovery or library design phases. With the ability to rapidly characterize metabolites from these enzymes, the challenges facing in silico contribution change during the drug optimization phase. Some of the challenges are addressed in this article. Some aspects of the SOM prediction software and methodology are discussed in this opinion article and examples of software utility in overcoming metabolic instability in drug optimization are shown. Areas covered in this review: SOM prediction by various approaches is discussed. Two ways of overcoming metabolic instability, blocking the metabolic softspots and rational modification of the instable molecule to avoid interaction with the CYP pocket, are discussed. The contribution plot in MetaSite and its use are discussed. What the reader will gain: The reader will gain an understanding of possible approaches to either blocking the metabolic softspot or rationally modifying the molecule using MetaSite software or docking approaches. Blocking metabolism using fluorination has risks especially introducing multifluorinated benzene rings in the molecule. Take home message: During the lead optimization phase of drug discovery, when metabolic instability is an issue in a series, in silico approaches can be used to modify the molecule in order to decrease clearance due to metabolism, even that due to CYP3A4.