Validation of Toxtree and SciQSAR in silico predictive software using a publicly available benchmark mutagenicity database and their applicability for the qualification of impurities in pharmaceuticals

The draft ICH M7 guidance (US FDA, 2013) recommends that the computational assessment of bacterial mutagenicity for the qualification of impurities in pharmaceuticals be performed using an expert rule-based method and a second statistically-based (Q)SAR method. The public nonproprietary 6489 compound Hansen benchmark mutagenicity data set was used as an external validation data set for Toxtree, a free expert rule-based SAR software. This is the largest known external validation of Toxtree. The Toxtree external validation specificity, sensitivity, concordance and false negative rate for this mutagenicity data set was 66%, 80%, 74% and 20%, respectively.This mutagenicity data set was also used to create a statistically-based SciQSAR-Hansen mutagenicity model. In a 10% leave-group-out internal cross validation study the specificity, sensitivity, concordance and false negative rate for the SciQSAR mutagenicity model was 71%, 83%, 77% and 17%, respectively. Combining Toxtree and SciQSAR predictions and scoring a positive finding in either software as a positive mutagenicity finding reduced the false negative rate to 7% and increased sensitivity to 93% at the expense of specificity which decreased to 53%.The results of this study support the applicability of Toxtree, and the SciQSAR-Hansen mutagenicity model for the qualification of impurities in pharmaceuticals.     

Immune Suppression as Related to Toxicology

Abstract

During the past 30 years, thousands of quantitative structure-activity relationships (QSAR) have been published for all sorts of chemicals acting on many forms of life or parts thereof (DNA, enzymes, organelles, etc.). Very little effort has been made to show the relationship among these equations. In this report, we discuss two examples, the toxicity of phenols to rats and the effect of aniline mustards on a variety of living systems, where the electronic effects in the QSAR can be correlated to QSAR from physical organic chemistry. This enables one to make better mechanistic deductions about the biological structure-activity relationships. From this, it is concluded that radicals formed from the phenols cause birth defects.     

Fragment-based QSAR strategies in drug design

Recently, fragment-based drug design has been established as a crucial strategy for hit identification and lead generation, which has strongly encouraged the development of approaches to specifically recognize and evaluate molecular fragments or structural scaffolds that preferentially interact with particular sites of important biological targets. In this context, fragment-based quantitative structure–activity relationship (FB-QSAR) has emerged as a versatile tool to explore the chemical and biological space of data sets of compounds. FB-QSAR approaches have evolved from a classical use in the generation of standard QSAR models into advanced drug design tools for database mining, pharmacokinetic property prediction and optimization of multiple parameters. This paper provides a brief perspective on the evolution and current status of FB-QSAR, highlighting new opportunities in drug design.     

Synthesis and Quantitative Structure‐activity Relationships Study for Arylpropenamide Derivatives as Inhibitors of Hepatitis B Virus Replication

A series of new arylpropenamide derivatives containing different aryl groups were synthesized, characterized, and evaluated for their anti‐hepatitis B virus (HBV) activities. A new high accuracy QSAR model of arylpropenamide was constructed based on a more completely activities data and calculation parameter. The 2D‐QSAR equations, by using DFT and multiple linear regression analysis methods, revealed that higher value of thermal energy (TE) and lower entropy (S^?) increase the anti‐HBV activities of the arylpropenamide molecules. Predictive 3D‐QSAR models were established by SYBYL multifit molecular alignment rule. The optimum models were all statistically significant with cross‐validated and conventional coefficients, indicating that they were reliable enough for activity prediction.     

Influence of substrate structure on substrate binding to the renal organic cation/H+ exchanger

 The carrier-mediated exchange of H⁺ for organic cations (”OC/H⁺ exchange”) is the active step in OC secretion in renal proximal tubules. Although hydrophobicity is known to be an important criterion for binding of substrates to this transporter, the degree to which steric parameters of substrate structure influence binding to the exchanger is unclear. We examined this issue by measuring the inhibition of OC/H⁺ exchange produced by a group of quaternary ammonium compounds which share a common structural motif: an N ¹-pyridinium residue. Activity of the OC/H⁺ exchanger was determined by measuring transport of [¹⁴C]tetraethylammonium (TEA) in brush-border membrane vesicles (BBMV) from rabbit renal cortex. Transport was measured in the presence of a pH gradient (pH_in 6.0; pH_out 7.5) to maximize TEA/H⁺ exchange. Apparent inhibitory constants (K _i values) for each test agent were measured. The test agents included 4-phenylpyridiniums and 3-phenylpyridiniums, quinoliniums and acridiniums. The planar structure of these compounds permits a direct test of whether the presence of planar hydrophobic mass in different orientations relative to the pyridinium motif exerts a systematic effect on substrate binding to the OC/H⁺ exchanger. The hydrophobicity of each group of compounds was systematically varied by addition of different substituents at the quaternary nitrogen. Whereas decreases in K _i proved to be proportional to hydrophobicity, the position of the phenyl-ring substituent(s) had no effect on substrate interaction with the exchanger. The results led to the development of a preliminary quantitative structure–activity relationship (QSAR) correlating substrate hydrophobicity and substrate binding to the OC/H⁺ exchanger. This QSAR was used to predict the binding of 1-methyl-4-phenylpyridinium (MPP⁺), (+) and (–)nicotine, (+) and (–)ephedrine, quinine and quinidine to the OC/H⁺ exchanger. Molecular graphics representation of the 3D structures of the test agents was used to develop a working model of a hydrophobic, planar receptor surface on the OC/H⁺ exchanger against which substrates are suggested to interact during binding. Development of the QSAR and receptor surface model open the way to quantitative tests of the specific physical and structural determinants of substrate selectivity by the renal OC/H⁺ exchanger. Received: 20 July 1998 / Received after revision and accepted: 19 October 1998     

How Predictable Are Human Stratum Corneum Lipid/Water Partition Coefficients? Assessment and Useful Correlations for Dermal Absorption

Partition coefficients between human stratum corneum lipids and water (K^sclip/w) are collected or deduced from a variety of sources in a manner that approximately doubles the available data compared to the current state-of-the-art model (Hansen et al., Adv Drug Deliv Rev. 2013;65(2):251-264). An additional datum for water itself in porcine SC that considerably extends the molecular size and lipophilicity range of the data set is considered. The data are analyzed in terms of an extended linear free energy relationship involving octanol/water partition coefficients, Abraham solvation parameters, and a secondary, power law molecular weight dependence. The optimum fit to log K^sclip/w for the full data set reduces the standard error of prediction from 0.50 for a Hansen-like model to 0.39; corresponding multiplicative errors in K^sclip/w are reduced from a factor of 3.1 to one of 2.5. The difference in performance is driven by the water datum, which requires a more complex dependence on molecular size than that afforded by Abraham parameters. In the absence of the water value, the Hansen-like model, which does not include a dependence on molecular size, is essentially optimum. A comparison is presented to fluid-phase phospholipid–water systems, which have a demonstrably different structure–property relationship.     

Pharmacophore modeling, 3D-QSAR studies, and in-silico ADME prediction of pyrrolidine derivatives as neuraminidase inhibitors

Neuraminidase (NA) is a major glycoprotein of influenza virus which is essential for viral infection. It offers a potential target for antiviral drug development. To develop potent NA inhibitors, pharmacophore models were generated by genetic algorithm with linear assignment for hypermolecular alignment of data sets. 3D-QSAR studies were carried out on 49 molecules. Both comparative molecular field analysis (q(2) = 0.720 and r(2) = 0.947) and comparative molecular similarity indices analysis (q(2) = 0.644 and r(2) = 0.885) yielded reasonable results. A preliminary pharmacokinetic profile of these neuraminidase inhibitors was predicted using Volsurf module.     

Quantitative Structure–Activity Relationships (QSARs) of Pyrimidine Nucleosides as HIV-1 Antiviral Agents

The structural requirements for the antiviral activity of pyrimidine nucleosides against HIV-1 virus was evaluated with the Hansch SAR analysis. Antiviral activity is best related to the hydrophobicity and steric (L and B3) properties of the substituent at the C5 of pyrimidine ring. Further, the antiviral activity is related to B4 of the substituent at position 3' of the sugar ring with a positive slope. The activity of both uracil and cytosine derivatives can be related to their structure by the same equations, which indicates that the SARs are similar in these two groups of congeners. These results suggest that compounds with a small substituent at the 5 position of the pyrimidine ring and a flat substituent at the 3' position of the sugar ring will be the most active compounds against HIV-1 virus.