Remigijus Didziapetris - Academia.edu (original) (raw)
Papers by Remigijus Didziapetris
Journal of Computer-Aided Molecular Design
Journal of Pharmaceutical Sciences, 2018
Caco-2 cell line is frequently used as a simplified in vitro model of intestinal absorption. In t... more Caco-2 cell line is frequently used as a simplified in vitro model of intestinal absorption. In this study, a database of 1366 Caco-2 permeability coefficients (P e) for 768 diverse drugs and drug-like compounds was compiled from public sources. The collected data represent permeation rates measured at varying experimental conditions (pH from 4.0 to 8.0, and stirring rates from 0 to >1000 rpm) that presumably account for passive diffusion across mucosal epithelium. These data were subjected to multistep nonlinear regression analysis using a minimal set of physicochemical descriptors (octanol-water log D, pKa, hydrogen bonding potential, and molecular size). The model was constructed in a mechanistic manner incorporating the following components: (i) a hydrodynamic equation of size-and chargespecific along with nonspecific diffusion across the paracellular pathway; (ii) transcellular diffusion represented by thermodynamic membrane/water partitioning ratio; (iii) stirring-dependent limit of maximum achievable permeability due to the presence of unstirred water layer. The obtained model demonstrates good accuracy of log P e predictions with a residual mean square error <0.5 log units for all training and validation sets. Given its robust performance and straightforward interpretation in terms of simple physicochemical properties, the proposed model may serve as a valuable tool to guide drug discovery efforts toward readily absorbable compounds.
Journal of Computer-Aided Molecular Design, 2016
A large and chemically diverse hERG inhibition data set comprised of 6690 compounds was construct... more A large and chemically diverse hERG inhibition data set comprised of 6690 compounds was constructed on the basis of ChEMBL bioactivity database and original publications dealing with experimental determination of hERG activities using patch-clamp and competitive displacement assays. The collected data were converted to binary format at 10 lM activity threshold and subjected to gradient boosting machine classification analysis using a minimal set of physicochemical and topological descriptors. The tested parameters involved lipophilicity (log P), ionization (pK a), polar surface area, aromaticity, molecular size and flexibility. The employed approach allowed classifying the compounds with an overall 75-80 % accuracy, even though it only accounted for non-specific interactions between hERG and ligand molecules. The observed descriptor-response profiles were consistent with common knowledge about hERG ligand binding site, but also revealed several important quantitative trends, as well as slight inter-assay variability in hERG inhibition data. The results suggest that even weakly basic groups (pK a \ 6) might substantially contribute to hERG inhibition potential, whereas the role of lipophilicity depends on the compound's ionization state, and the influence of log P decreases in the order of bases [ zwitterions [ neutrals [ acids. Given its robust performance and clear physicochemical interpretation, the proposed model may provide valuable information to direct drug discovery efforts towards compounds with reduced risk of hERG-related cardiotoxicity.
Quantitative Structure-Activity Relationships, 2002
... Our goal will be to (i) derive general equations for the constructionist∫ approach, and (ii)... more ... Our goal will be to (i) derive general equations for the constructionist∫ approach, and (ii) use the reductionist∫ approach to reduce the number of increments and accelerate development of new algorithms. 2.2.1 Generalized FM ...
SAR and QSAR in Environmental Research, 2010
This study presents a new type of acute toxicity (LD(50)) prediction that enables automated asses... more This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.
Mini-Reviews in Medicinal Chemistry, 2003
The current mini-review explains how fragmental methods (FMs) can be used in the analysis and pre... more The current mini-review explains how fragmental methods (FMs) can be used in the analysis and prediction of physicochemical properties and biological activities. The considered properties include log P, solubility, pK(a), intestinal permeability, P-gp substrate specificity and toxicity. The focus will be a description of a "mechanistic" approach, which implies a gradual reduction of alternative explanations for any property or activity. This means a flexible construction of fragmental parameters using large amounts of experimental data. Since biological activities involve multiple (unknown) target macromolecules with multiple binding modes, a stepwise classification (C-SAR) analysis is most useful. It involves the following procedures: (i). construction of physicochemical profiles using parameters that can be reliably predicted, (ii). identification of reactive functional groups and the largest active skeletons, (iii). generalization of these groups and skeletons in terms of "site-specific physicochemical profiling". This entails a dynamic construction of 2D pharmacophores that can be converted into 3D models.
Journal of Pharmaceutical Sciences, 2009
This study presents a mechanistic QSAR analysis of human intestinal absorption of drugs and drug-... more This study presents a mechanistic QSAR analysis of human intestinal absorption of drugs and drug-like compounds using a data set of 567 %HIA values. Experimental data represent passive diffusion across intestinal membranes, and are considered to be reasonably free of carrier-mediated transport or other unwanted effects. A nonlinear model was developed relating %HIA to physicochemical properties of drugs (lipophilicity, ionization, hydrogen bonding, and molecular size). The model describes ion-specific intestinal permeability of drugs by both transcellular and paracellular routes, and also accounts for unstirred water layer effects. The obtained model was validated on two external data sets consisting of in vivo human jejunal permeability coefficients (P eff) and absorption rate constants (K a). Validation results demonstrate good predictive power of the model (RMSE ¼ 0.35-0.45 log units for log K a and log P eff). High prediction accuracy together with clear physicochemical interpretation (log P, pK a) makes this model particularly suitable for use in property-based drug design. ß 2009
Journal of Pharmaceutical Sciences, 2009
This study presents a mechanistic QSAR analysis of passive blood-brain barrier permeability of dr... more This study presents a mechanistic QSAR analysis of passive blood-brain barrier permeability of drugs and drug-like compounds in rats and mice. The experimental data represented in vivo log PS (permeability-surface area product) from in situ perfusion, brain uptake index, and intravenous administration studies. A data set of 280 log PS values was compiled. A subset of 178 compounds was assumed to be driven by passive transport that is free of plasma protein binding and carrier-mediated effects. This subset was described in terms of nonlinear lipophilicity and ionization dependences, that account for multiple kinetic and thermodynamic effects: (i) drug&amp;amp;amp;amp;amp;#39;s kinetic diffusion, (ii) ion-specific partitioning between plasma and brain capillary endothelial cell membranes, and (iii) hydrophobic entrapment in phospholipid bilayer. The obtained QSAR model provides both good statistical significance (RMSE &amp;amp;amp;amp;amp;lt; 0.5) and simple physicochemical interpretations (log P and pKa), thus providing a clear route towards property-based design of new CNS drugs.
Journal of Pharmaceutical Sciences, 2011
The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is... more The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is the most frequently used parameter for characterizing central nervous system exposure of drugs and drug candidates. The aim of the current study was to propose a physicochemical QSAR model for log BB prediction. Model development involved the following steps: (i) A data set consisting of 470 experimental log BB values determined in rodents was compiled and verified to ensure that selected data represented drug disposition governed by passive diffusion across blood-brain barrier. (ii) Available log BB values were corrected for unbound fraction in plasma to separate the influence of drug binding to brain and plasma constituents. (iii) The resulting ratios of total brain to unbound plasma concentrations reflecting brain tissue binding were described by a nonlinear ionization-specific model in terms of octanol/water log P and pK(a). The results of internal and external validation demonstrated good predictive power of the obtained model as both log BB and brain tissue binding strength were predicted with residual mean square error of 0.4 log units. The statistical parameters were similar among training and validation sets, indicating that the model is not likely to be overfitted.
Journal of Pharmaceutical Sciences, 2003
AB/HIA is a ''soft'' filter for identifying compounds with poor intestinal membrane permeability.... more AB/HIA is a ''soft'' filter for identifying compounds with poor intestinal membrane permeability. The analyzed data set included over 1000 drug-like compounds with experimental human intestinal absorption (HIA) values. A sequence of recursive partitioning analyses based on multiple physicochemical and structural descriptors led to the derivation of the rule-based algorithm (filter). The obtained rules reveal a simple physicochemical model of intestinal permeability; they also account for the specific effects caused by quarternary nitrogens and biphosphonate groups. Comparison of the observed and predicted values revealed very low percent of disagreement (15% false-positives and 3% false-negatives). The unusual absorption of compounds that deviated from the predicted values was explained in terms of active transport, efflux, chemical stability, chelating ability, and solubility. Most of these effects can be accounted for by new, substructure-specific rules that can be added into the existing filter. This can lead to the development of a reliable theoretical model for predicting human intestinal absorption. If combined with other models for predicting first pass metabolism, the updated AB/ HIA filter can be very useful in predicting oral bioavailability.
Journal of Drug Targeting, 2003
Prediction of P-glycoprotein substrate specificity (S(PGP)) can be viewed as a constituent part o... more Prediction of P-glycoprotein substrate specificity (S(PGP)) can be viewed as a constituent part of a compound&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;pharmaceutical profiling&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; in drug design. This task is difficult to achieve due to several factors that raised many contradictory opinions: (i) the disparity between the S(PGP) values obtained in different assays, (ii) the confusion between Pgp substrates and inhibitors, (iii) the confusion between lipophilicity and amphiphilicity of Pgp substrates, and (iv) the dilemma of describing class-specific relationships when Pgp has no binding sites of high ligand specificity. In this work, we compiled S(PGP) data for 1000 compounds. All data were represented in a binary format, assigning S(PGP) = 1 for substrates and S(PGP) = 0 for non-substrates. Each value was ranked according to the reliability of experimental assay. Two data sets were considered. Set 1 included 220 compounds with S(PGP) from polarized transport across MDR1 transfected cell monolayers. Set 2 included the entire list of 1000 compounds, with S(PGP) values of generally lower reliability. Both sets were analysed using a stepwise classification structure-activity relationship (C-SAR) method, leading to derivation of simple rules for crude estimation of S(PGP) values. The obtained rules are based on the following factors: (i) compound&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s size expressed through molar weight or volume, (ii) H-accepting given by the Abraham&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s beta (that can be crudely approximated by the sum of O and N atoms), and (iii) ionization given by the acid and base pKa values. Very roughly, S(PGP) can be estimated by the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;rule of fours&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;. Compounds with (N + O) &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; or = 8, MW &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; 400 and acid pKa &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; 4 are likely to be Pgp substrates, whereas compounds with (N + O) &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; or = 4, MW &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 400 and base pKa &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 8 are likely to be non-substrates. The obtained results support the view that Pgp functioning can be compared to a complex &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;mini-pharmacokinetic&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; system with fuzzy specificity. This system can be described by a probabilistic version of Abraham&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s solvation equation, suggesting a certain similarity between Pgp transport and chromatographic retention. The chromatographic model does not work in the case of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;marginal&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; compounds with properties close to the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;global&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; physicochemical cut-offs. In the latter case various class-specific rules must be considered. These can be associated with the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;amphiphilicity&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; and &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;biological similarity&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; of compounds. The definition of class-specific effects entails construction of the knowledge base that can be very useful in ADME profiling of new drugs.
Journal of Computer-Aided Molecular Design, 2010
A new structure-activity relationship model predicting the probability for a compound to inhibit ... more A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for [800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC 50 threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis. Keywords Drug-drug interactions Á CYP3A4 inhibition Á QSAR Á GALAS model Á Model applicability domain Á Trainable model
Expert Opinion on Drug Metabolism & Toxicology, 2013
Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candi... more Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candidates regardless of their target location in the body. While good brain penetration is essential for CNS drugs, it may lead to serious side effects in case of peripherally-targeted molecules. Despite a high demand of computational methods for estimating brain transport early in drug discovery, achieving good prediction accuracy still remains a challenging task. This article reviews various measures employed to quantify brain delivery and recent advances in QSAR approaches for predicting these properties from the compound&amp;amp;amp;#39;s structure. Additionally, the authors discuss the classification models attempting to distinguish between permeable and impermeable chemicals. Recent research in the field of brain penetration modeling showed an increasing understanding of the processes involved in drug disposition, although most models of brain/plasma partitioning still rely on purely statistical considerations. Preferably, new models should incorporate mechanistic knowledge since it is the prerequisite for guiding drug design efforts in the desired direction. To increase the efficiency of computational tools, a broader view is necessary, involving rate and extent of brain penetration, as well as plasma and brain tissue binding strength, instead of relying on any single property.
Journal of Computer-Aided Molecular Design
Journal of Pharmaceutical Sciences, 2018
Caco-2 cell line is frequently used as a simplified in vitro model of intestinal absorption. In t... more Caco-2 cell line is frequently used as a simplified in vitro model of intestinal absorption. In this study, a database of 1366 Caco-2 permeability coefficients (P e) for 768 diverse drugs and drug-like compounds was compiled from public sources. The collected data represent permeation rates measured at varying experimental conditions (pH from 4.0 to 8.0, and stirring rates from 0 to >1000 rpm) that presumably account for passive diffusion across mucosal epithelium. These data were subjected to multistep nonlinear regression analysis using a minimal set of physicochemical descriptors (octanol-water log D, pKa, hydrogen bonding potential, and molecular size). The model was constructed in a mechanistic manner incorporating the following components: (i) a hydrodynamic equation of size-and chargespecific along with nonspecific diffusion across the paracellular pathway; (ii) transcellular diffusion represented by thermodynamic membrane/water partitioning ratio; (iii) stirring-dependent limit of maximum achievable permeability due to the presence of unstirred water layer. The obtained model demonstrates good accuracy of log P e predictions with a residual mean square error <0.5 log units for all training and validation sets. Given its robust performance and straightforward interpretation in terms of simple physicochemical properties, the proposed model may serve as a valuable tool to guide drug discovery efforts toward readily absorbable compounds.
Journal of Computer-Aided Molecular Design, 2016
A large and chemically diverse hERG inhibition data set comprised of 6690 compounds was construct... more A large and chemically diverse hERG inhibition data set comprised of 6690 compounds was constructed on the basis of ChEMBL bioactivity database and original publications dealing with experimental determination of hERG activities using patch-clamp and competitive displacement assays. The collected data were converted to binary format at 10 lM activity threshold and subjected to gradient boosting machine classification analysis using a minimal set of physicochemical and topological descriptors. The tested parameters involved lipophilicity (log P), ionization (pK a), polar surface area, aromaticity, molecular size and flexibility. The employed approach allowed classifying the compounds with an overall 75-80 % accuracy, even though it only accounted for non-specific interactions between hERG and ligand molecules. The observed descriptor-response profiles were consistent with common knowledge about hERG ligand binding site, but also revealed several important quantitative trends, as well as slight inter-assay variability in hERG inhibition data. The results suggest that even weakly basic groups (pK a \ 6) might substantially contribute to hERG inhibition potential, whereas the role of lipophilicity depends on the compound's ionization state, and the influence of log P decreases in the order of bases [ zwitterions [ neutrals [ acids. Given its robust performance and clear physicochemical interpretation, the proposed model may provide valuable information to direct drug discovery efforts towards compounds with reduced risk of hERG-related cardiotoxicity.
Quantitative Structure-Activity Relationships, 2002
... Our goal will be to (i) derive general equations for the constructionist∫ approach, and (ii)... more ... Our goal will be to (i) derive general equations for the constructionist∫ approach, and (ii) use the reductionist∫ approach to reduce the number of increments and accelerate development of new algorithms. 2.2.1 Generalized FM ...
SAR and QSAR in Environmental Research, 2010
This study presents a new type of acute toxicity (LD(50)) prediction that enables automated asses... more This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.
Mini-Reviews in Medicinal Chemistry, 2003
The current mini-review explains how fragmental methods (FMs) can be used in the analysis and pre... more The current mini-review explains how fragmental methods (FMs) can be used in the analysis and prediction of physicochemical properties and biological activities. The considered properties include log P, solubility, pK(a), intestinal permeability, P-gp substrate specificity and toxicity. The focus will be a description of a "mechanistic" approach, which implies a gradual reduction of alternative explanations for any property or activity. This means a flexible construction of fragmental parameters using large amounts of experimental data. Since biological activities involve multiple (unknown) target macromolecules with multiple binding modes, a stepwise classification (C-SAR) analysis is most useful. It involves the following procedures: (i). construction of physicochemical profiles using parameters that can be reliably predicted, (ii). identification of reactive functional groups and the largest active skeletons, (iii). generalization of these groups and skeletons in terms of "site-specific physicochemical profiling". This entails a dynamic construction of 2D pharmacophores that can be converted into 3D models.
Journal of Pharmaceutical Sciences, 2009
This study presents a mechanistic QSAR analysis of human intestinal absorption of drugs and drug-... more This study presents a mechanistic QSAR analysis of human intestinal absorption of drugs and drug-like compounds using a data set of 567 %HIA values. Experimental data represent passive diffusion across intestinal membranes, and are considered to be reasonably free of carrier-mediated transport or other unwanted effects. A nonlinear model was developed relating %HIA to physicochemical properties of drugs (lipophilicity, ionization, hydrogen bonding, and molecular size). The model describes ion-specific intestinal permeability of drugs by both transcellular and paracellular routes, and also accounts for unstirred water layer effects. The obtained model was validated on two external data sets consisting of in vivo human jejunal permeability coefficients (P eff) and absorption rate constants (K a). Validation results demonstrate good predictive power of the model (RMSE ¼ 0.35-0.45 log units for log K a and log P eff). High prediction accuracy together with clear physicochemical interpretation (log P, pK a) makes this model particularly suitable for use in property-based drug design. ß 2009
Journal of Pharmaceutical Sciences, 2009
This study presents a mechanistic QSAR analysis of passive blood-brain barrier permeability of dr... more This study presents a mechanistic QSAR analysis of passive blood-brain barrier permeability of drugs and drug-like compounds in rats and mice. The experimental data represented in vivo log PS (permeability-surface area product) from in situ perfusion, brain uptake index, and intravenous administration studies. A data set of 280 log PS values was compiled. A subset of 178 compounds was assumed to be driven by passive transport that is free of plasma protein binding and carrier-mediated effects. This subset was described in terms of nonlinear lipophilicity and ionization dependences, that account for multiple kinetic and thermodynamic effects: (i) drug&amp;amp;amp;amp;amp;#39;s kinetic diffusion, (ii) ion-specific partitioning between plasma and brain capillary endothelial cell membranes, and (iii) hydrophobic entrapment in phospholipid bilayer. The obtained QSAR model provides both good statistical significance (RMSE &amp;amp;amp;amp;amp;lt; 0.5) and simple physicochemical interpretations (log P and pKa), thus providing a clear route towards property-based design of new CNS drugs.
Journal of Pharmaceutical Sciences, 2011
The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is... more The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is the most frequently used parameter for characterizing central nervous system exposure of drugs and drug candidates. The aim of the current study was to propose a physicochemical QSAR model for log BB prediction. Model development involved the following steps: (i) A data set consisting of 470 experimental log BB values determined in rodents was compiled and verified to ensure that selected data represented drug disposition governed by passive diffusion across blood-brain barrier. (ii) Available log BB values were corrected for unbound fraction in plasma to separate the influence of drug binding to brain and plasma constituents. (iii) The resulting ratios of total brain to unbound plasma concentrations reflecting brain tissue binding were described by a nonlinear ionization-specific model in terms of octanol/water log P and pK(a). The results of internal and external validation demonstrated good predictive power of the obtained model as both log BB and brain tissue binding strength were predicted with residual mean square error of 0.4 log units. The statistical parameters were similar among training and validation sets, indicating that the model is not likely to be overfitted.
Journal of Pharmaceutical Sciences, 2003
AB/HIA is a ''soft'' filter for identifying compounds with poor intestinal membrane permeability.... more AB/HIA is a ''soft'' filter for identifying compounds with poor intestinal membrane permeability. The analyzed data set included over 1000 drug-like compounds with experimental human intestinal absorption (HIA) values. A sequence of recursive partitioning analyses based on multiple physicochemical and structural descriptors led to the derivation of the rule-based algorithm (filter). The obtained rules reveal a simple physicochemical model of intestinal permeability; they also account for the specific effects caused by quarternary nitrogens and biphosphonate groups. Comparison of the observed and predicted values revealed very low percent of disagreement (15% false-positives and 3% false-negatives). The unusual absorption of compounds that deviated from the predicted values was explained in terms of active transport, efflux, chemical stability, chelating ability, and solubility. Most of these effects can be accounted for by new, substructure-specific rules that can be added into the existing filter. This can lead to the development of a reliable theoretical model for predicting human intestinal absorption. If combined with other models for predicting first pass metabolism, the updated AB/ HIA filter can be very useful in predicting oral bioavailability.
Journal of Drug Targeting, 2003
Prediction of P-glycoprotein substrate specificity (S(PGP)) can be viewed as a constituent part o... more Prediction of P-glycoprotein substrate specificity (S(PGP)) can be viewed as a constituent part of a compound&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;pharmaceutical profiling&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; in drug design. This task is difficult to achieve due to several factors that raised many contradictory opinions: (i) the disparity between the S(PGP) values obtained in different assays, (ii) the confusion between Pgp substrates and inhibitors, (iii) the confusion between lipophilicity and amphiphilicity of Pgp substrates, and (iv) the dilemma of describing class-specific relationships when Pgp has no binding sites of high ligand specificity. In this work, we compiled S(PGP) data for 1000 compounds. All data were represented in a binary format, assigning S(PGP) = 1 for substrates and S(PGP) = 0 for non-substrates. Each value was ranked according to the reliability of experimental assay. Two data sets were considered. Set 1 included 220 compounds with S(PGP) from polarized transport across MDR1 transfected cell monolayers. Set 2 included the entire list of 1000 compounds, with S(PGP) values of generally lower reliability. Both sets were analysed using a stepwise classification structure-activity relationship (C-SAR) method, leading to derivation of simple rules for crude estimation of S(PGP) values. The obtained rules are based on the following factors: (i) compound&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s size expressed through molar weight or volume, (ii) H-accepting given by the Abraham&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s beta (that can be crudely approximated by the sum of O and N atoms), and (iii) ionization given by the acid and base pKa values. Very roughly, S(PGP) can be estimated by the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;rule of fours&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;. Compounds with (N + O) &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; or = 8, MW &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; 400 and acid pKa &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; 4 are likely to be Pgp substrates, whereas compounds with (N + O) &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; or = 4, MW &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 400 and base pKa &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 8 are likely to be non-substrates. The obtained results support the view that Pgp functioning can be compared to a complex &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;mini-pharmacokinetic&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; system with fuzzy specificity. This system can be described by a probabilistic version of Abraham&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s solvation equation, suggesting a certain similarity between Pgp transport and chromatographic retention. The chromatographic model does not work in the case of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;marginal&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; compounds with properties close to the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;global&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; physicochemical cut-offs. In the latter case various class-specific rules must be considered. These can be associated with the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;amphiphilicity&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; and &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;biological similarity&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; of compounds. The definition of class-specific effects entails construction of the knowledge base that can be very useful in ADME profiling of new drugs.
Journal of Computer-Aided Molecular Design, 2010
A new structure-activity relationship model predicting the probability for a compound to inhibit ... more A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for [800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC 50 threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis. Keywords Drug-drug interactions Á CYP3A4 inhibition Á QSAR Á GALAS model Á Model applicability domain Á Trainable model
Expert Opinion on Drug Metabolism & Toxicology, 2013
Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candi... more Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candidates regardless of their target location in the body. While good brain penetration is essential for CNS drugs, it may lead to serious side effects in case of peripherally-targeted molecules. Despite a high demand of computational methods for estimating brain transport early in drug discovery, achieving good prediction accuracy still remains a challenging task. This article reviews various measures employed to quantify brain delivery and recent advances in QSAR approaches for predicting these properties from the compound&amp;amp;amp;#39;s structure. Additionally, the authors discuss the classification models attempting to distinguish between permeable and impermeable chemicals. Recent research in the field of brain penetration modeling showed an increasing understanding of the processes involved in drug disposition, although most models of brain/plasma partitioning still rely on purely statistical considerations. Preferably, new models should incorporate mechanistic knowledge since it is the prerequisite for guiding drug design efforts in the desired direction. To increase the efficiency of computational tools, a broader view is necessary, involving rate and extent of brain penetration, as well as plasma and brain tissue binding strength, instead of relying on any single property.