Lipophilicity Descriptors Research Articles

Study of the Lipophilicity and ADMET Parameters of New Anticancer Diquinothiazines with Pharmacophore Substituents.

Lipophilicity is one of the principal parameters that describe the pharmacokinetic behavior of a drug, including its absorption, distribution, metabolism, elimination, and toxicity. In this study, the lipophilicity and other physicochemical, pharmacokinetic, and toxicity properties that affect the bioavailability of newly synthesized dialkylaminoalkyldiquinothiazine hybrids as potential drug candidates are presented. The lipophilicity, as RM0, was determined experimentally by the RP-TLC method using RP18 plates and acetone-TRIS buffer (pH 7.4) as the mobile phase. The chromatographic parameters of lipophilicity were compared to computationally calculated partition coefficients obtained by various types of programs such as iLOGP, XLOGP3, WLOGP, MLOGP, SILCOS-IT, LogP, logP, and milogP. In addition, the selected ADMET parameters were determined in silico using the SwissADME and pkCSM platforms and correlated with the experimental lipophilicity descriptors. The results of the lipophilicity study confirm that the applied algorithms can be useful for the rapid prediction of logP values during the first stage of study of the examined drug candidates. Of all the algorithms used, the biggest similarity to the chromatographic value (RM0) for certain compounds was seen with iLogP. It was found that both the SwissADME and pkCSM web tools are good sources of a wide range of ADMET parameters that describe the pharmacokinetic profiles of the studied compounds and can be fast and low-cost tools in the evaluation of examined drug candidates during the early stages of the development process.

Nature-Inspired 1-Phenylpyrrolo[2,1-a]isoquinoline Scaffold for Novel Antiproliferative Agents Circumventing P-Glycoprotein-Dependent Multidrug Resistance.

Previous studies have shown that some lamellarin-resembling annelated azaheterocyclic carbaldehydes and related imino adducts, sharing the 1-phenyl-5,6-dihydropyrrolo[2,1-a]isoquinoline (1-Ph-DHPIQ) scaffold, are cytotoxic in some tumor cells and may reverse multidrug resistance (MDR) mediated by P-glycoprotein (P-gp). Herein, several novel substituted 1-Ph-DHPIQ derivatives were synthesized which carry carboxylate groups (COOH, COOEt), nitrile (CN) and Mannich bases (namely, morpholinomethyl derivatives) in the C2 position, as replacements of the already reported aldehyde group. They were evaluated for antiproliferative activity in four tumor cell lines (RD, HCT116, HeLa, A549) and for the ability of selectively inhibiting P-gp-mediated MDR. Lipophilicity descriptors and molecular docking calculations helped us in rationalizing the structure-activity relationships in the P-gp inhibition potency of the investigated 1-Ph-DHPIQs. As a main outcome, a morpholinomethyl Mannich base (8c) was disclosed which proved to be cytotoxic to all the tested tumor cell lines in the low micromolar range (IC50 < 20 μM) and to inhibit in vitro the efflux pumps P-gp and MRP1 responsible for MDR, with IC50s of 0.45 and 12.1 μM, respectively.

Microwave synthesis of novel chenodeoxycholic acid esters and comparative study of chromatographic behavior and lipophilicity

In this study, eco-friendly microwave-assisted esterification reactions of chenodeoxycholic acid with medium-chain diols (1,2-ethanediol, 1,4-butanediol, 1,6-hexanediol, 1,8-octanediol, and 1,10-decanediol) or tetraethylene glycol were accomplished. The synthesized bile acid esters were obtained with high yields (up to 81 %) and purity in a short reaction time (15 min). It is shown that the microwave technique is a suitable method for the preparation of chenodeoxycholic acid esters. In order to obtain detailed insight into the lipophilic behavior of the studied chenodeoxycholic acid esters, a comparative study of chromatographic behavior and lipophilicity was performed. Also, the present study deals with the estimation of pH – logD profiles in order to get an overview of the changes in lipophilicity related to the pH value changes. The obtained results indicate that studied compounds have logD values in the range acceptable for potential drug candidates. Chromatographic lipophilicity of synthesized chenodeoxycholic acid esters successfully correlate with in silico lipophilicity descriptors.

Energetics of β-lactoglobulin–flavor compounds interactions

Interaction of bovine β-lactoglobulin (BLG) with several flavor compounds (FC) (2–methylpyrazine, vanillin, 2–acetylpyridine, 2– and 3–acetylthiophene, methyl isoamyl ketone, heptanone, octanone, and nonanone) was studied by high-sensitivity differential scanning calorimetry. The denaturation temperature, enthalpy, and heat capacity increment were determined at different FC concentrations. It was found that the denaturation temperature and heat capacity increment do not depend on the FC concentration, while the denaturation enthalpy decreases linearly with the FC concentration. These thermodynamic effects disclose the preferential FC binding to the unfolded form of BLG. By the obtained calorimetric data, the free energies of FC binding vs. the FC concentrations were calculated. These dependences were shown to be linear. Their slope relates closely to the overall FC affinity for the unfolded BLG in terms of the Langmuir binding model. The overall BLG affinity for FC varies from 20 M–1 (2-methylpyrazine) up to 360 M–1(nonanone). The maximal stoichiometry of the BLG–FC complexes was roughly estimated as a ratio of the length of the unfolded BLG to the molecular length of FC. Using these estimates, the apparent BLG–FC binding constants were determined. They are in the range of 0.3–8.0 M–1 and correlated strictly with the FC lipophilicity descriptor (logP).

Retention Behavior of Anticancer Thiosemicarbazides in Biomimetic Chromatographic Systems and In Silico Calculations.

Chromatographic methods, apart from in silico ones, are commonly used rapid techniques for the evaluation of certain properties of biologically active compounds used for their prediction of pharmacokinetic processes. Thiosemicarbazides are compounds possessing anticancer, antimicrobial, and other valuable biological activities. The aim of the investigation was to estimate the lipophilicity of 1-aryl-4-(phenoxy)acetylthiosemicarbazides, to predict their oral adsorption and the assessment of their % plasma-protein binding (%PPB). RP-HPLC chromatographic techniques with five diversified HPLC systems, including columns with surface-bonded octadecylsilanes (C-18), phosphatidylcholine (immobilized artificial membrane, IAM), cholesterol (Chol), and α1-acid glycoprotein (AGP) and human serum albumin (HSA), were applied. The measured lipophilicity of all investigated compounds was within the range recommended for potential drug candidates. However, some derivatives are strongly bonded to HSA (%PPB ≈ 100%), which may limit some pharmacokinetic processes. HPLC determined lipophilicity descriptors were compared with those obtained by various computational approaches.

Evaluation of the Usefulness of Topological Indices for Predicting Selected Physicochemical Properties of Bioactive Substances with Anti-Androgenic and Hypouricemic Activity.

Due to the observed increase in the importance of computational methods in determining selected physicochemical parameters of biologically active compounds that are key to understanding their ADME/T profile, such as lipophilicity, there is a great need to work on accurate and precise in silico models based on some structural descriptors, such as topological indices for predicting lipophilicity of certain anti-androgenic and hypouricemic agents and their derivatives, for which the experimental lipophilicity parameter is not accurately described in the available literature, e.g., febuxostat, oxypurinol, ailanthone, abiraterone and teriflunomide. Therefore, the following topological indices were accurately calculated in this paper: Gutman (M, Mν), Randić (0χ, 1χ, 0χν, 1χν), Wiener (W), Rouvray-Crafford (R) and Pyka (A, 0B, 1B) for the selected anti-androgenic drugs (abiraterone, bicalutamide, flutamide, nilutamide, leflunomide, teriflunomide, ailanthone) and some hypouricemic compounds (allopurinol, oxypurinol, febuxostat). Linear regression analysis was used to create simple linear correlations between the newly calculated topological indices and some physicochemical parameters, including lipophilicity descriptors of the tested compounds (previously obtained by TLC and theoretical methods). Our studies confirmed the usefulness of the obtained linear regression equations based on topological indices to predict ADME/T important parameters, such as lipophilicity descriptors of tested compounds with anti-androgenic and hypouricemic effects. The proposed calculation method based on topological indices is fast, easy to use and avoids valuable and lengthy laboratory experiments required in the case of experimental ADME/T studies.

Significance of Astragaloside IV from the Roots of Astragalus mongholicus as an Acetylcholinesterase Inhibitor-From the Computational and Biomimetic Analyses to the In Vitro and In Vivo Studies of Safety.

The main aim of the study was to assess the acetylcholinesterase-inhibitory potential of triterpenoid saponins (astragalosides) found in the roots of Astragalus mongholicus. For this purpose, the TLC bioautography method was applied and then the IC50 values were calculated for astragalosides II, III and IV (5.9 μM; 4.2 μM, and 4.0 μM, respectively). Moreover, molecular dynamics simulations were carried outto assess the affinity of the tested compounds for POPC and POPG-containing lipid bilayers, which in this case are the models of the blood-brain barrier (BBB). All determined free energy profiles confirmed that astragalosides exhibit great affinity for the lipid bilayer. A good correlation was obtained when comparing the logarithm of n-octanol/water partition coefficient (logPow) lipophilicity descriptor values with the smallest values of free energy of the determined 1D profiles. The affinity for the lipid bilayers changes in the same order as the corresponding logPow values, i.e.,: I > II > III~IV. All compounds exhibit a high and also relatively similar magnitude of binding energies, varying from ca. -55 to -51 kJ/mol. Apositive correlation between the experimentally-determined IC50 values and the theoretically-predicted binding energies expressed by the correlation coefficient value equal 0.956 was observed.

Linear quantitative structure-ecotoxicity relationship modeling of a series of symmetrical triazine derivatives based on physicochemical parameters

The present study reports the Quantitative Structure-Ecotoxicity Relationship (QSER) analysis of a series of 21 1,3,5-triazine derivatives based on multiple-linear regression (MLR) method. The ecotoxicity data were estimated by using in silico approach and included the following parameters: acute algae toxicity (AAT), acute daphnia toxicity (ADT), Daphnia Magna LC50 48h/EPA (DMepa) and Daphnia Magna LC50 48h/DEMETRA (DMdemetra). The ecotoxicity data were correlated with molecular descriptors selected by using the stepwise selection method. The considered molecular descriptors are lipophilicity descriptors (CrippenLogP, ALogp2), Autocorrelation Descriptor Mass (ATSm1, ATSm2, ATSm3, ATSm4), Autocorrelation Descriptor Charge (ATSc2), minimum E-states for (strong) hydrogen bond acceptors (minHBa), maximum E-states for (strong) hydrogen bond acceptors (maxHBa), second kappa shape index (Kier2), maximum atom-type E-State: ?:N:? (maxaaN), sum of path lengths starting from nitrogens (WTPT-5) and McGowan characteristic volume (McGowan_Volume). The modeling resulted in four statistically valid MLR models. The models were validated by the internal and external validation approaches. The external validation confirmed high predictive ability of the established MLRs.

Comparative Study of the Lipophilicity of Selected Anti-Androgenic and Blood Uric Acid Lowering Compounds.

This study aimed to evaluate the lipophilicity of a series substances lowering the concentration of uric acid in blood and anti-androgen drugs by thin-layer chromatography in reversed-phase systems (RP-TLC, RP-HPTLC) and computational methods. The chromatographic parameter of lipophilicity (RMW) of tested compounds was determined on three stationary phases, i.e., RP18F254, RP18WF254 and RP2F254, using ethanol-water, propan-2-ol-water and acetonitrile-water in various volume compositions as mobile phases. The chromatographic analysis led to determining the experimental value of the lipophilicity parameter for each of the tested compounds, including those for which the experimental value of the partition coefficient (logPexp) as a measure of lipophilicity is not well described in available databases, such as febuxostat, oxypurinol, ailanthone, abiraterone and teriflunomide. The chromatographic parameters of lipophilicity were compared with the logP values obtained with various software packages, such as AClogP, AlogPs, AlogP, MlogP, XlogP2, XlogP3, ACD/logP and logPKOWWIN. The obtained results indicate that, among selected chromatographic parameters of lipophilicity, both experimental and calculated logP values gave similar results, and these RP-TLC or RP-HPTLC systems can be successfully applied to estimate the lipophilicity of studied heterocyclic compounds belonging to two different pharmacological groups. This work also illustrates the similarity and difference existing between the tested compounds under study using the chemometric methods, such as principal component analysis (PCA) and cluster analysis (CA). In addition, a relatively new approach based on the sum of ranking differences (SRD) was used to compare the chromatographically obtained and theoretical lipophilicity descriptors of studied compounds.

A Study of Absorption and Selected Molecular Physicochemical Properties of Some Antipsychotic Drugs

Abstract Antipsychotic drugs are commonly prescribed for different mental disorders and can be classified into two main groups: the first which contain originally developed antipsychotics of the first generation or typical antipsychotics and the other group with newly developed antipsychotics or atypical antipsychotics of the second generation. In this study, eleven antipsychotic drugs (chlorpromazine, flupentixol, haloperidol, zuclopenthixol, aripiprazole, clozapine, olanzapine, quetiapine, risperidone, sertindole, ziprasidone) were investigated to evaluate significance of their molecular physicochemical properties (lipophilicity, aqueous solubility, polar surface area, molecular weight, volume value and acidity) for their bioavailability. Relationships between literature available intestinal absorption data of antipsychotic drugs and their lipophilicity descriptor with one additional molecular descriptor, investigated using multiple linear regression analysis provided high correlations for molecular descriptors, Mw, Vol, pKa, as additional independent variables. Values of correlation coefficients (R2) were ranged from 0.951 (for Vol) above 0.944 (for Mw) to 0.923 (for pKa).

Feasibility study of separation and purification of bile acid derivatives by HPLC on C18 and F5 columns

Organic synthesis could be very demanding, usually due to difficulties related to the separation of main reaction products from by-products. Steroidal compounds could have similar lipophilicity, which is mostly based on the lipophilicity of the steroidal core. This causes many problems during purification, i.e. in obtaining a pure single steroidal compound. In this research, a group of bile acid derivatives were subjected to HPLC analysis using four experimental systems, which presented combinations of C18 and F5 columns with methanol-water and acetonitrile-water as mobile phases. Retention parameters and retention order of the compounds were established and indicated that all experimental systems could be applicable in order to separate and/or purify some individual compounds or a mixture of a few compounds. However, the only experimental system that could separate a mixture of all investigated derivatives proved to be a C18 column with acetonitrile-water as a mobile phase. Since complex interactions between F5 column and the analytes exist, molecular surface polarity (MSP) was tested as a lipophilicity parameter, and also compared with logP using multivariate statistics. Retention parameters obtained on F5 column were used as descriptors, both with MSP and with logP, concluding that logP has shown to be a better lipophilicity descriptor.

Comparative chemometric analysis, ranking and selection of lipophilicity parameters of 6-chloro-1,3,5-triazine derivatives with acyclic and cyclic substituents

In the present paper, the chemometric analysis, ranking and selection of the most suitable in silico lipophilicity parameters of eight alkyl and cycloalkyl s-triazine derivatives were carried out. The lipophilicity parameters were calculated using various computational approaches and computer programs. The conducted analysis is the basis for further studies aimed to define, compare and examine the influence of alkyl and cycloalkyl substituents, introduced in 6-chloro-1,3,5-triazine-2,4-diamine structure, on molecular lipophilicity and bioactivity. The chemometric methods used in the study are pattern recognition methods, such as hierarchical cluster analysis (HCA) and sum of ranking differences (SRD). The obtained ranking results indicate that the following in silico lipophilicity descriptors can be chosen as the most suitable for interpretation of lipophilicity of the studied series of s-triazine derivatives: AlogP, MlogP, WLOGP, logPKLOP and logPPHYS. The lipophilicity descriptor iLOGP was marked as the least suitable lipophilicity descriptor of the studied series of compounds. The ranking results were validated by 7-fold cross-validation approach and by comparison of ranks by random numbers (CRRN).

Synthesis and Biological Evaluation of Dantrolene-Like Hydrazide and Hydrazone Analogues as Multitarget Agents for Neurodegenerative Diseases.

Dantrolene, a drug used for the management of malignant hyperthermia, had been recently evaluated for prospective repurposing as multitarget agent for neurodegenerative syndromes, including Alzheimer's disease (AD). Herein, twenty‐one dantrolene‐like hydrazide and hydrazone analogues were synthesized with the aim of exploring structure‐activity relationships (SARs) for the inhibition of human monoamine oxidases (MAOs) and acetylcholinesterase (AChE), two well‐established target enzymes for anti‐AD drugs. With few exceptions, the newly synthesized compounds exhibited selectivity toward MAO B over either MAO A or AChE, with the secondary aldimine 9 and phenylhydrazone 20 attaining IC50 values of 0.68 and 0.81 μM, respectively. While no general SAR trend was observed with lipophilicity descriptors, a molecular simplification strategy allowed the main pharmacophore features to be identified, which are responsible for the inhibitory activity toward MAO B. Finally, further in vitro investigations revealed cell protection from oxidative insult and activation of carnitine/acylcarnitine carrier as concomitant biological activities responsible for neuroprotection by hits 9 and 20 and other promising compounds in the examined series.

A hybrid modeling approach for assessing mechanistic models of small molecule partitioning in vivo using a machine learning-integrated modeling platform

Prediction of the first-in-human dosing regimens is a critical step in drug development and requires accurate quantitation of drug distribution. Traditional in vivo studies used to characterize clinical candidate’s volume of distribution are error-prone, time- and cost-intensive and lack reproducibility in clinical settings. The paper demonstrates how a computational platform integrating machine learning optimization with mechanistic modeling can be used to simulate compound plasma concentration profile and predict tissue-plasma partition coefficients with high accuracy by varying the lipophilicity descriptor logP. The approach applied to chemically diverse small molecules resulted in comparable geometric mean fold-errors of 1.50 and 1.63 in pharmacokinetic outputs for direct tissue:plasma partition and hybrid logP optimization, with the latter enabling prediction of tissue permeation that can be used to guide toxicity and efficacy dosing in human subjects. The optimization simulations required to achieve these results were parallelized on the AWS cloud and generated outputs in under 5 h. Accuracy, speed, and scalability of the framework indicate that it can be used to assess the relevance of other mechanistic relationships implicated in pharmacokinetic-pharmacodynamic phenomena with a lower risk of overfitting datasets and generate large database of physiologically-relevant drug disposition for further integration with machine learning models.

Predicting the membrane permeability of organic fluorescent probes by the deep neural network based lipophilicity descriptor DeepFl-LogP

Light microscopy has become an indispensable tool for the life sciences, as it enables the rapid acquisition of three-dimensional images from the interior of living cells/tissues. Over the last decades, super-resolution light microscopy techniques have been developed, which allow a resolution up to an order of magnitude higher than that of conventional light microscopy. Those techniques require labelling of cellular structures with fluorescent probes exhibiting specific properties, which are supplied from outside and therefore have to surpass cell membranes. Currently, major efforts are undertaken to develop probes which can surpass cell membranes and exhibit the photophysical properties required for super-resolution imaging. However, the process of probe development is still based on a tedious and time consuming manual screening. An accurate computer based model that enables the prediction of the cell permeability based on their chemical structure would therefore be an invaluable asset for the development of fluorescent probes. Unfortunately, current models, which are based on multiple molecular descriptors, are not well suited for this task as they require high effort in the usage and exhibit moderate accuracy in their prediction. Here, we present a novel fragment based lipophilicity descriptor DeepFL-LogP, which was developed on the basis of a deep neural network. DeepFL-LogP exhibits excellent correlation with the experimental partition coefficient reference data (R2 = 0.892 and MSE = 0.359) of drug-like substances. Further a simple threshold permeability model on the basis of this descriptor allows to categorize the permeability of fluorescent probes with 96% accuracy. This novel descriptor is expected to largely simplify and speed up the development process for novel cell permeable fluorophores.

Assessment of Lipophilicity Descriptors of Selected NSAIDs Obtained at Different TLC Stationary Phases.

Lipophilicity study of selected NSAIDs, the group of the bioactive compounds usually used in humans and animals medicine, with the use of experimental and calculation methods was evaluated. LogP values are proposed and compared as descriptors of the lipophilicity of eleven compounds (from oxicams and coxibs). Obtained data were designated by thin-layer chromatography (TLC) in various chromatographic conditions, with stationary phases with different properties. The mobile phase systems were prepared by mixing the respective amounts of water and organic modifier, methanol and acetone, in the range of 30 to 80% (v/v) in 5% increments. Retention parameters (RF, RM and RM0) were calculated and statistically evaluated to establish correlations. All experimentally determined RM0 values were compared with partition coefficients obtained by computational methods using linear regression analysis. Moreover, in order to extract information about the lipophilicity of compounds from large retention datasets, two chemometric approaches, namely principal component analysis (PCA) and cluster analysis (CA) were carried out. Established models of lipophilicity may have the potential to predict the biological activity of a number of drugs. The presented knowledge may also be of use during drug discovery processes, broadening the knowledge of potential ways to modify the physicochemical properties of chemical compounds.

Biomembrane Modelling in Planar Chromatographic Determination of Lipophilicity Using Olive and Castor Oils

BackgroundLipophilicity is a crucial physicochemical parameter that predicts in vivo pharmacokinetics and should be reliably estimated in early stage drug discovery to reduce incidence of attrition. Previous methodologies for its measurement often lead to technically incorrect decisions due to simplistic architecture and poor biomimetic attributes. Significantly, a certain seed oil, used for biomembrane modelling on planar chromatographic platform, was reported to be sufficiently biomimetic and fit for purpose.ObjectivesTo evaluate olive oil (OL) and olive-castor oil (OL-C) equi-mixture as lipids for biomembrane simulation on planar chromatographic platform.Material and MethodRetention behavior of nabumetone, a model compound was used to optimize these potential lipid membranes using a thin film engineered from 5% Liquid paraffin (LP) as benchmark, while halofantrine, nabumetone , α-naphthol and β-naphthol representing varying molecular polarities, were used for validation studies. The validation involved 2-way analysis of variance (ANOVA) associated with variability in Basic lipophilicity parameter (Rmw), and Specific hydrophobic surface area (SHSA) for the optimized surfaces, relative to LP and octadecylsilane (ODS) Further validation entailed correlation of the lipophilicity descriptor i.e. isocratic chromatographic hydrophobicity index (ICHI) on OL, OL-C, ODS and LP with experimental Log P(octanol/water).ResultsOptimized film thicknesses were produced by 5% OL and 1.25% OL-C (p &gt; 0.05). The 2-way ANOVA revealed great variability in performance characteristics of the surfaces (p &lt; 0.0001), and the new surfaces also gave poorer correlation with Log P values (R2= 0.502 and 0.449 respectively).ConclusionThe 1.25 % OL-C demonstrated a higher biomimetic attribute and warrants further validation studies to ascertain biorelevance, of lipophilicity measurement on this platform, in predicting oral drug absorption.&#x0D; Keywords: Lipophilicity, Reversed-phase Thin Layer Chromatography, Retention behaviour, Olive oil, Castor oil

The analysis of chromatographic behavior of homoandrostane derivatives in reversed-phase ultra-high performance liquid chromatography

Homoandrostane derivatives, as compounds with significant bioactivity, were studied in terms of their chromatographic behavior in reversed-phase ultra-high performance liquid chromatography (RP-UHPLC). In the present study, five androstane derivatives from the series of homoandrostanes were analyzed, including: 3?-hydroxy-17-oxa-17a-homoandrost-5-en-16-one, 3?,5?-dihydroxy-17- oxa-17a-homoandrostane-6,16-dione, 17-oxa-5?,6?-epoxy-17a-homoandrostane-3,16-dione, 5?-hydroxy- 17-oxa-17a-homoandrostane-6,16-dione-3?-yl acetate and 3?-hydroxy-17-oxa-5?,6?-epoxy-Dhomoandrostan- 16-one. The compounds were analyzed by applying methanol-water mobile phases with different volume fractions of methanol, as a polar protic solvent, and logk0 parameters of each compound were determined. The outstanding correlations between in silico logP descriptors and logk0 parameters were obtained, as well as between in silico logD descriptors and logk0 parameters. The logk0 parameters are very well correlated with polar surface area (PSA) descriptor as well. The studied compounds and lipophilicity descriptors (including the chromatographic lipophilicity parameters - logk0) were clustered applying hierarchical cluster analysis (HCA) in the form of clustered heat map known as double dendrogram. Furthermore, the sum of ranking differences (SRD) method was used for the ranking of the lipophilicity measures of the analyzed homoandrostane derivatives so the most suitable lipophilicity measures of this series of compounds can be selected.

QSAR modeling the toxicity of pesticides against Americamysis bahia

The widespread use of pesticides has received increasing attention in regulatory agencies because their extensive overuse and various adverse effects on all living organisms. Organizations such as EPA and ECHA have published laws that pesticides should be fully evaluated before bring them to market. In the present study, we evaluated the pesticides toxicity using the Quantitative Structural-Activity Relationship (QSAR) method. The models for the single class pesticides (herbicides, insecticides and fungicides) as well as the general class pesticides (the combined dataset plus some microbicides, molluscicides, etc.) were developed using the Genetic Algorithm and Multiple Linear Regression method. The internal and external validation results suggested that all the obtained models were stable and predictive. According to the modeling descriptors, the lipophilic descriptors contributed positively while all the electrotopological state descriptors showed a negative contribution, their presences in every model verified the conspicuous influence of molecular lipophilicity and hydrophilicity on the pesticides toxicity. However, the influence of topological structure descriptors was different and varies with the physiochemical information they encode. Finally, the models presented in this paper would help assess the pesticides toxicity against Americamysis bahia, shorten test time, and reduce the cost of pesticides risk assessment.

Cornea-PAMPA as an Orthogonal in Vitro Physicochemical Model of Corneal Permeability

The present study was aimed to investigate the relationships between permeability and membrane retention values (logPe and MR) of the in vitro non-cellular permeability assay, corneal-PAMPA in comparison with experimental Caco-2 permeability data and calculated physicochemical properties (MW, clogP, clogD7.4 , TPSA). For the investigation, 50 structurally and physicochemically diverse drugs were selected and measured in PAMPA model optimized for corneal permeability. The results showed corneal-PAMPA model's orthogonality in terms of passive diffusion to the FDA approved Caco-2 as a gastrointestinal absorption model, while the comparison with physicochemical properties revealed trends between logPe , MR and the lipophilicity descriptors and TPSA.