Computer-aided drug design and ADMET predictions for identification and evaluation of novel potential farnesyltransferase inhibitors in cancer therapy

We have used various computational methodologies including molecular dynamics, density functional theory, virtual screening, ADMET predictions and molecular interaction field studies to design and analyze four novel potential inhibitors of farnesyltransferase (FTase). Evaluation of two proposals regarding their drug potential as well as lead compounds have indicated them as novel promising FTase inhibitors, with theoretically interesting pharmacotherapeutic profiles, when Compared to the very active and most cited FTase inhibitors that have activity data reported, which are launched drugs or compounds in clinical tests. One of our two proposals appears to be a more promising drug candidate and FTase inhibitor, but both derivative molecules indicate potentially very good pharmacotherapeutic profiles in comparison with Tipifarnib and Lonafarnib, two reference pharmaceuticals. Two other proposals have been selected with virtual screening approaches and investigated by LIS, which suggest novel and alternatives scaffolds to design future potential FTase inhibitors. Such compounds can be explored as promising molecules to initiate a research protocol in order to discover novel anticancer drug candidates targeting farnesyltransferase, in the fight against cancer. (C) 2009 Elsevier Inc. All rights reserved.

Influence of Plasma Protein Binding on Pharmacodynamics: Estimation of In Vivo Receptor Affinities of beta Blockers Using a New Mechanism-Based PK-PD Modelling Approach

The objective of this investigation was to examine in a systematic manner the influence of plasma protein binding on in vivo pharmacodynamics. Comparative pharmacokinetic-pharmacodynamic studies with four beta blockers were performed in conscious rats, using heart rate under isoprenaline-induced tachycardia as a pharmacodynamic endpoint. A recently proposed mechanism-based agonist-antagonist interaction model was used to obtain in vivo estimates of receptor affinities (K(B),(vivo)). These values were compared with in vitro affinities (K(B),(vitro)) on the basis of both total and free drug concentrations. For the total drug concentrations, the K(B),(vivo) estimates were 26, 13, 6.5 and 0.89 nM for S(-)-atenolol, S(-)-propranolol, S(-)-metoprolol and timolol. The K(B),(vivo) estimates on the basis of the free concentrations were 25, 2.0, 5.2 and 0.56 nM, respectively. The K(B),(vivo)-K(B),(vitro) correlation for total drug concentrations clearly deviated from the line of identity, especially for the most highly bound drug S(-)-propranolol (ratio K(B),(vivo)/K(B),(vitro) similar to 6.8). For the free drug, the correlation approximated the line of identity. Using this model, for beta-blockers the free plasma concentration appears to be the best predictor of in vivo pharmacodynamics. (C) 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:3816-3828, 2009

Quantum-chemical, NMR and X-ray diffraction studies on (+/-)-1-[3,4-(methylenedioxy)phenyl]-2-methylaminopropane

Time-averaged conformations of (+/-)-1-[3,4-(methylenedioxy)phenyl]-2-methylaminopropane hydrochloride (MDMA, ""ecstasy"") in D(2)O, and of its free base and trifluoroacetate in CDCl(3), were deduced from their (1)H NMR spectra and used to calculate their conformer distribution. Their rotational potential energy surface (PES) was calculated at the RHF/6-31G(d,p), 133LYP/6-31G(d,p), B3LYP/cc-pVDZ and AM1 levels. Solvent effects were evaluated using the polarizable continuum model. The NMR and theoretical studies showed that, in the free base, the N-methyl group and the ring are preferentially trans. This preference is stronger in the salts and corresponds to the X-ray structure of the hydrochloride. However, the energy barriers separating these forms are very low. The X-ray diffraction crystal structures of the anhydrous salt and its monohydrate differed mainly in the trans or cis relationship of the N-methyl group to the a-methyl, although these two forms interconvert freely in solution. (C) 2007 Elsevier Inc. All rights reserved.

Molecular dynamics, flexible docking, virtual screening, ADMET predictions, and molecular interaction field studies to design novel potential MAO-B inhibitors

Monoamine oxidase is a flavoenzyme bound to the mitochondrial outer membranes of the cells, which is responsible for the oxidative deamination of neurotransmitter and dietary amines. It has two distinct isozymic forms, designated MAO-A and MAO-B, each displaying different substrate and inhibitor specificities. They are the well-known targets for antidepressant, Parkinson`s disease, and neuroprotective drugs. Elucidation of the x-ray crystallographic structure of MAO-B has opened the way for the molecular modeling studies. In this work we have used molecular modeling, density functional theory with correlation, virtual screening, flexible docking, molecular dynamics, ADMET predictions, and molecular interaction field studies in order to design new molecules with potential higher selectivity and enzymatic inhibitory activity over MAO-B.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

Molecular sieve silica membranes for H2/CO separation

Efficient separation of fuel gas (H2) from other gases in reformed gas mixtures is becoming increasingly important in the development of alternative energy systems. A highly efficient and new technology available for these separations is molecular sieve silica (MSS) membranes derived from tetraethyl-orthosilicate (TEOS). A permeation model is developed from an analogous electronic system and compared to transport theory to determine permeation, selectivity and apparent activation of energy based on experimental values. Experimental results for high quality membranes show single gas permselectivity peaking at 57 for H2/CO at 150°C with a H2 permeation of 5.14 x 10^-8 mol.m^-2.s^-1.Pa^-1. Higher permeance was also achieved, but at the expense of selectivity. This is the case for low quality membranes with peak H2 permeation at 1.78 x 10-7 mol.m-2.s-1.Pa-1 at 22°C and H2/CO permselectivity of 4.5. High quality membranes are characterised with positive apparent activation energy while the low quality membranes have negative values. The model had a good fit of r-squared of 0.99-1.00 using the experimental data.

Molecular Sieve Silica (MSS) Membranes for Gas Separation and Reaction Processes

Weakly branched silica films formed by the two-step sol-gel process allow for the formation of high selectivity membranes for gas separation. 29Si NMR and gas permeation showed that reduced crosslinking leads to He/CH4 selectivity improvement from 300 to 1000. Applied in membrane reactor for cyclohexane conversion to benzene, conversions were achieved at 14 fold higher than a conventional reactor at 250°C. Hydrothermal stability studies showed that carbon templating of silica is required for hydrothermally stable membranes. From our work it was shown that with correct application of chemistry, practical membrane systems can be built to suit gas separation (e. g. hydrogen fuel) and reactor systems.

Hydrothermal stable templated molecular sieve silica (TMSS) membranes for gas separation

In this work we compare the hydrothermal stability performance of a Templated Molecular Sieve Silica (TMSS) membrane against a standard, non-templated Molecular Sieve Silica (MSS) membrane. The tests were carried under dry and wet (steam) conditions for single gas (He, H2, CO and CO2) at 1-2 atm membrane pressure drop at 200oC. Single gas TMSS membrane H2, permeance and H2/CO permselectivity was found to be 2.05 x 10-8 mols.m-2.s-1.Pa-1 and 15, respectively. The MSS membrane showed similar selectivity, but increased overall flux. He permeance through membranes decayed at a rate of 4-5 x 10-10 mols.m-2.s-1.Pa-1 per day regardless of membrane ambience (dry or wet). Although H2/CO permselectivity of the TMSS membrane slightly improved from 15 to 18 after steam testing, the MSS membrane resulted in significant reduction from 16 to 8.3. In addition, membrane regeneration after more than 50 days resulted in the TMSS membrane reverting to its original permeation levels while no significant improvements were observed for the MSS membra ne. Results showed that the TMSS membrane had enhanced hydrothermal stability and regeneration ability.

Hydrothermal Stability Analysis of Carbonised Template Molecular Sieve Silica Membranes

For fuel cell CO clean up application, the presence of water with silica membranes greatly reduces their selectivity to CO. We show results of a new functional carbonised template membrane of around 13nm thickness which offered hydrothermal stability with no compromise to the membrane’s H2/CO permselectivity of 16. Lost permeance was also regenerated.

Hydrostability and Scaling Up Molecular Sieve Silica (MSS) Membranes for H2/CO Separation in Fuel Cell Systems

MSS membranes are a good candidate for CO cleanup in fuel cell fuel processing systems due to their ability to selectively permeate H2 over CO via molecular sieving. Successfully scaled up tubular membranes were stable under dry conditions to 400°C with H2 permeance as high as 2 x 10-6 mol.m-2.s^-1.Pa^-1 at 200 degrees C and H2/CO selectivity up to 6.4, indicating molecular sieving was the dominant mechanism. A novel carbonised template molecular sieve silica (CTMSS) technology gave the scaled up membranes resilience in hydrothermal conditions up to 400 degrees C in 34% steam and synthetic reformate, which is required for use in fuel cell CO cleanup systems.

Adsorption in mesopores: A molecular-continuum model with application to MCM-41

The classical model of surface layering followed by capillary condensation during adsorption in mesopores, is modified here by consideration of the adsorbate solid interaction potential. The new theory accurately predicts the capillary coexistence curve as well as pore criticality, matching that predicted by density functional theory. The model also satisfactorily predicts the isotherm for nitrogen adsorption at 77.4 K on MCM-41 material of various pore sizes, synthesized and characterized in our laboratory, including the multilayer region, using only data on the variation of condensation pressures with pore diameter. The results indicate a minimum mesopore diameter for the surface layering model to hold as 14.1 Å, below which size micropore filling must occur, and a minimum pore diameter for mechanical stability of the hemispherical meniscus during desorption as 34.2 Å. For pores in-between these two sizes reversible condensation is predicted to occur, in accord with the experimental data for nitrogen adsorption on MCM-41 at 77.4 K.

Improved constraints on possible variation of physical constants from HI 21-cm and molecular QSO absorption lines

Quasar (QSO) absorption spectra provide an extremely useful probe of possible cosmological variation in various physical constants. Comparison of H i 21-cm absorption with corresponding molecular (rotational) absorption spectra allows us to constrain variation in , where α is the fine-structure constant and gp is the proton g-factor. We analyse spectra of two QSOs, PKS 1413+135 and TXS 0218+357, and derive values of at absorption redshifts of and 0.6847 by simultaneous fitting of the H i 21-cm and molecular lines. We find and respectively, indicating an insignificantly smaller y in the past. We compare our results with other constraints from the same two QSOs given recently by Drinkwater et al. and Carilli et al., and with our recent optical constraints, which indicated a smaller α at higher redshifts.

Superchemistry: dynamics of coupled atomic and molecular Bose condensates

We analyze the dynamics of a dilute, trapped Bose-condensed atomic gas coupled to a diatomic molecular Bose gas by coherent Raman transitions. This system is shown to result in a new type of “superchemistry,” in which giant collective oscillations between the atomic and the molecular gas can occur. The phenomenon is caused by stimulated emission of bosonic atoms or molecules into their condensate phases.

Superconductivity mediated by charge fluctuations in layered molecular crystals

We consider the competition between superconducting, charge ordered, and metallic phases in layered molecular crystals with the theta and beta" structures. Applying slave-boson theory to the relevant extended Hubbard model, we show that the superconductivity is mediated by charge fluctuations and the Cooper pairs have d(xy) symmetry. This is in contrast to the kappa-(BEDT-TTF)(2)X family, for which theoretical calculations give superconductivity mediated by spin fluctuations and with d(x)2(-y)2 symmetry. We predict several materials that should become superconducting under pressure.

Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.