Euzébio Guimarães Barbosa

LQTA-QSAR: A New 4D-QSAR Methodology

A novel 4D-QSAR approach which makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package is presented in this study. This new methodology, named LQTA-QSAR (LQTA, Laboratório de Quimiometria Teórica e Aplicada), has a module (LQTAgrid) that calculates intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. The comparison of the proposed methodology to other 4D-QSAR and CoMFA formalisms was performed using a set of forty-seven glycogen phosphorylase b inhibitors (data set 1) and a set of forty-four MAP p38 kinase inhibitors (data set 2). The QSAR models for both data sets were built using the ordered predictor selection (OPS) algorithm for variable selection. Model validation was carried out applying y-randomization and leave-N-out cross-validation in addition to the external validation. PLS models for data set 1 and 2 provided the following statistics: q(2) = 0.72, r(2) = 0.81 for 12 variables selected and 2 latent variables and q(2) = 0.82, r(2) = 0.90 for 10 variables selected and 5 latent variables, respectively. Visualization of the descriptors in 3D space was successfully interpreted from the chemical point of view, supporting the applicability of this new approach in rational drug design.

Application of thermal analysis to the study of antituberculosis drugs-excipient compatibility

First-line drugs (rifampicin, RIF; isoniazid, INH; ethambutol, ETA; and pyrazinamide, PZA) recommended in conventional treatment of tuberculosis were analyzed in 1:1 w/w binary mixtures with microcrystalline cellulose MC 101 (CEL) and lactose supertab® (LAC) by differential scanning calorimetry (DSC), thermogravimetry (TG), differential thermal analysis (DTA), and Fourier transformed infrared analysis (FTIR) as part of development of fixed dose combination (FDC) tablets. Evidence of interaction between drug and pharmaceutical excipients was supposed when peaks disappearance or shifting were observed on DTA and DSC curves, as well as decreasing of decomposition temperature onset and TG profiles, comparing to pure species data submitted to the same conditions. LAC was showed to interact with RIF (absence of drug fusion and recrystallization events on DSC/DTA curves); INH (thermal events of the mixtures different from those observed for drug and excipient pure in DSC/DTA curves); PZA (decrease on drug fusion peak in DSC/DTA curves), and ETA (shift on drug onset fusion and absence of pure LAC events on DSC/DTA curves). In all cases, an important decrease on the temperature of drug decomposition was verified for the mixtures (TG analysis). However, FTIR analysis showed good correlation between theoretical and experimental drug-LAC spectra except for INH–LAC mixture, evidencing high incompatibility between these two species and suggesting that those interactions with PZA and RIF were thermally induced. No evidence of incompatibilities in CEL mixtures was observed to any of the four-studied drugs.

4D-LQTA-QSAR and docking study on potent gram-negative specific LpxC inhibitors: a comparison to CoMFA modeling

A quasi 4D-QSAR has been carried out on a series of potent Gram-negative LpxC inhibitors. This approach makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. This new methodology is based on the generation of a conformational ensemble profile, CEP, for each compound instead of only one conformation, followed by the calculation intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are independent variables employed in a QSAR analysis. The comparison of the proposed methodology to comparative molecular field analysis (CoMFA) formalism was performed. This methodology explores jointly the main features of CoMFA and 4D-QSAR models. Step-wise multiple linear regression was used for the selection of the most informative variables. After variable selection, multiple linear regression (MLR) and partial least squares (PLS) methods used for building the regression models. Leave-N-out cross-validation (LNO), and Y-randomization were performed in order to confirm the robustness of the model in addition to analysis of the independent test set. Best models provided the following statistics :

Molecular approaches for structural characterization of a new potassium channel blocker from Tityus stigmurus venom: cDNA cloning, homology modeling, dynamic simulations and docking

{{R}^{2}= 0.943, {q}^{2}_{\rm LOO}= 0.802, {q}^{2}_{\rm LNO}= 0.798, {R}^{2}_{\rm Pred}= 0.936}

Digital Filters for Molecular Interaction Field Descriptors

(PLS) and

Compatibility study between ferulic acid and excipients used in cosmetic formulations by TG/DTG, DSC and FTIR

{{R}^{2 }= 0.948, {q}^{2}_{\rm LOO}= 0.823, {q}^{2}_{\rm LNO}= 0.818, {R}^{2}_{\rm Pred} = 0.928}