4,804 research outputs found

    A comparative assessment of octanol-water partitioning and distribution constant estimation methods for perfluoroalkyl carboxylates and sulfonates

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    New experimental data is available in the literature regarding the octanol-water distribution behavior of representative straight chain perfluoroalkyl carboxylate (PFCA) and sulfonate (PFSA) congeners. The current study provides the first investigation into the predictive ability of various software programs for estimating the corresponding octanol-water partitioning (log P) and distribution (log D) constants of PFCAs and PFSAs. Wide predictive variation was found within and between the various methods. Several programs were able to accurately estimate the log P/D fragmental contributions of a -CF~2~- group for PFCAs, as well as the associated Gibbs free energies for partitioning into octanol from water due to the hydrophobic character of the perfluoroalkyl chain (Δ~hydrophobic~G~ow~). Only the SPARC log D method accurately predicted the electrostatic contributions of the carboxylate head group (Δ~electrostatic~G~ow~) towards octanol-water partitioning for PFCAs. Similar log D values and organic carbon normalized sediment-water partitioning coefficients (K~oc~) for PFCAs and PFSAs having equivalent perfluoroalkyl chain lengths suggests potentially equivalent Δ~electrostatic~G~ow~ and Δ~hydrophobic~G~ow~ contributions towards lipophilic partitioning for these two contaminant classes, regardless of head group identity. In contrast, there are potentially different Δ~electrostatic~G~ow~ and Δ~hydrophobic~G~ow~ contributions towards proteinophilic partitioning

    Chemical informatics uncovers a new role for moexipril as a novel inhibitor of cAMP phosphodiesterase-4 (PDE4)

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    PDE4 is one of eleven known cyclic nucleotide phosphodiesterase families and plays a pivotal role in mediating hydrolytic degradation of the important cyclic nucleotide second messenger, cyclic 3′5′ adenosine monophosphate (cAMP). PDE4 inhibitors are known to have anti-inflammatory properties, but their use in the clinic has been hampered by mechanism-associated side effects that limit maximally tolerated doses. In an attempt to initiate the development of better-tolerated PDE4 inhibitors we have surveyed existing approved drugs for PDE4-inhibitory activity. With this objective, we utilised a high-throughput computational approach that identified moexipril, a well tolerated and safe angiotensin-converting enzyme (ACE) inhibitor, as a PDE4 inhibitor. Experimentally we showed that moexipril and two structurally related analogues acted in the micro molar range to inhibit PDE4 activity. Employing a FRET-based biosensor constructed from the nucleotide binding domain of the type 1 exchange protein activated by cAMP, EPAC1, we demonstrated that moexipril markedly potentiated the ability of forskolin to increase intracellular cAMP levels. Finally, we demonstrated that the PDE4 inhibitory effect of moexipril is functionally able to induce phosphorylation of the Hsp20 by cAMP dependent protein kinase A. Our data suggest that moexipril is a bona fide PDE4 inhibitor that may provide the starting point for development of novel PDE4 inhibitors with an improved therapeutic window

    Physiology-based IVIVE predictions of tramadol from in vitro metabolism data

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    To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (SimcypA (R)). Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLint(H)) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution. Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis. IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults

    Review of QSAR Models and Software Tools for predicting Biokinetic Properties

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    In the assessment of industrial chemicals, cosmetic ingredients, and active substances in pesticides and biocides, metabolites and degradates are rarely tested for their toxicologcal effects in mammals. In the interests of animal welfare and cost-effectiveness, alternatives to animal testing are needed in the evaluation of these types of chemicals. In this report we review the current status of various types of in silico estimation methods for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their metabolites/degradation products. The review was performed in a broad sense, with emphasis on QSARs and rule-based approaches and their applicability to estimation of oral bioavailability, human intestinal absorption, blood-brain barrier penetration, plasma protein binding, metabolism and. This revealed a vast and rapidly growing literature and a range of software tools. While it is difficult to give firm conclusions on the applicability of such tools, it is clear that many have been developed with pharmaceutical applications in mind, and as such may not be applicable to other types of chemicals (this would require further research investigation). On the other hand, a range of predictive methodologies have been explored and found promising, so there is merit in pursuing their applicability in the assessment of other types of chemicals and products. Many of the software tools are not transparent in terms of their predictive algorithms or underlying datasets. However, the literature identifies a set of commonly used descriptors that have been found useful in ADME prediction, so further research and model development activities could be based on such studies.JRC.DG.I.6-Systems toxicolog

    Bioinformatic Analysis, Structure Modeling and Active Site Prediction of Aquaporin Protein from Catfish Heteropneustes fossilis

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    Aquaporins (AQPs) are membrane channel proteins which facilitate the rapid transport of water across cellular membrane and are of fundamental importance to the control of cell volume and transcellular water traffic. In the present study using bioinformatic tools an in silico modeling and analysis of aquaporin protein sequences of catfish Heteropneustes fossilis was conducted. Primary structure prediction and physiochemical characterization were performed by computing theoretical isoelectric point (pI), molecular weight, extinction coefficient, instability index and aliphatic index. Secondary structure assessment of aquaporin protein of Indian catfish using GOR IV reveals greater percentage of residues as alpha helix and random coils against the beta sheets. After performing homology modeling using MODELLER, a 3D structure of aquaporin of Indian catfish have been predicted from its amino acid sequence. After the prediction structure has been validated through various validation tools. This homology modeling based structure will provide an insite to its functional aspect and further studies which are based on tertiary structure of protein. Active site of aquaporin protein has been predicted using DoGSite scorer. Analysis of aquaporin active site will provide an insight to more précised functional characterization of this protein. In future, present study will allow the designing of mutant and inhibitors for the study of physiological role of aquaporin protein in Heteropneustes fossilis

    COMPUTATIONAL APPROACHES RELATED TO DRUG DISPOSITION

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    Drug disposition connects with the movement of drug molecules inside the body after administration irrespective with the route of administration. After entering the system, drug molecule and internal body systems comes under various pharmacokinetic interactions followed by observation of suitable biological activity. In this exhaustive process, physicochemical nature of the chemical substance and physiological nature of system makes this movement competitive. In this view, pharmacokinetic and toxic properties of the molecule regulates the destination of the molecule. Various computational processes are available for in silico pharmacokinetic assessment of drug molecule after absorption through biological membrane, distributed throughout the system based on the percent ionization or partition coefficient factors followed by biologically transformed into an another entity in presence of microsomal enzymes and finally excrete out from system using various cellular transport systems as well as related cellular toxicity behavior. In this chapter, we ensemble all the possible information related with the drug movement and related computational tools to understand the possible chemical and pathophysiological changes. Here detailed knowledge on database expedition, establishment of pharmacophore model, homology modelling based on sequence similarity, molecular docking study (rigid and flexible docking) and QSAR/QSPR study (with detailed process and available softwares) are provided. These diversely united informations actually helps a researcher to understand the factual movement of a drug molecule inside the system

    ADME Profiling in Drug Discovery and a New Path Paved on Silica

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    The drug discovery and development pipeline have more and more relied on in vitro testing and in silico predictions to reduce investments and optimize lead compounds. A comprehensive set of in vitro assays is available to determine key parameters of absorption, distribution, metabolism, and excretion, for example, lipophilicity, solubility, and plasma stability. Such test systems aid the evaluation of the pharmacological properties of a compound and serve as surrogates before entering in vivo testing and clinical trials. Nowadays, computer-aided techniques are employed not just in the discovery of new lead compounds but embedded as part of the entire drug development process where the ADME profiling and big data analyses add a new layer of complexity to those systems. Herein, we give a short overview of the history of the drug development pipeline presenting state-of-the-art ADME in vitro assays as established in academia and industry. We will further introduce the underlying good practices and give an example of the compound development pipeline. In the next step, recent advances at in silico techniques will be highlighted with special emphasis on how pharmacogenomics and in silico PK profiling can enhance drug monitoring and individualization of drug therapy
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