Criteria for assessing the reliability of toxicity predictions: I. TIMES Ames mutagenicity model

Risk-based in silico mutagenic assessment of benzodiazepine impurities using three QSAR tools

Benzodiazepines, widely prescribed psychoactive drugs, may contain DNA-reactive (mutagenic) impurities formed during synthesis, posing significant health risks. Owing to animal testing requirements, traditional in vitro and in vivo methods for assessing mutagenicity are time-consuming, costly, and ethically challenging. Computational approaches, particularly in silico (Q)SAR models, provide an efficient alternative for predicting toxicity based on chemical structure. This study evaluated the mutagenic potential of 88 benzodiazepine-related impurities using three freely accessible (Q)SAR tools: TOXTREE (Ames Test Alert by ISS), Toxicity Estimation Software Tool (TEST) with nearest neighbour and consensus models, and VEGA, a QSAR tool that integrates multiple mutagenicity prediction models, including the CAESAR Ames Mutagenicity Model. The tools were validated using a dataset of 99 chemicals with known Ames test results. TOXTREE exhibited the highest sensitivity (80.7 %) and accuracy (72.2 %) for predicting mutagenicity, whereas VEGA and TEST provided balanced accuracy (66.2 % and 66.7 %, respectively) and high specificity (74.5 % and 76.6 %, respectively). The risk assessment categorised 21 impurities as high risk, 11 as moderate-high risk, 28 as moderate-low risk, 22 as low risk, and 6 as equivocal, with expert review finalising classifications. The findings emphasise the integration of multiple (Q)SAR tools for early mutagenicity detection, regulatory compliance, and reduced reliance on animal testing. Further refinement of predictive models and additional computational approaches are recommended to enhance the accuracy of the risk assessment.

Molecular modelling of 6-oxo-5-Sulfanyl-1H-Pyridine-3-Carboxylic acid and its adsorption with the silver complex: Structural, optical, charge transference, dynamics and docking to nipah virus

This investigation employs DFT to evaluate the structural, molecular, and electronic feature variations of 6-oxo-5-sulfanyl-1H-pyridine-3-carboxylic acid in gas alongside various solvent media. The complex interactions occurring within the molecule are recognised using the Independent gradient model. The application of various electric fields are used to determine the electrical properties of the compound. The topographical inspection shows extreme electron-dense zones to display a good electron reception character of the molecule. The intense covalence nature is maximal between the aromatic zone's C-C and C-N regions. The compound possesses a maximum interaction with the (LP) → π∗ and π → π∗ transitions. The optical and absorbance property shows an upright enhancement in the addition of the solvents. The significant transference of charges inside the compound is signified using the D and H index values and heat maps. The thermal assessment established that the compound is sustainable at varied temperatures with the pressure at 1 atm. The carboxylate ion of 6O5S1HP3CA interacts with the Ag + clusters and its adsorption characteristics are confirmed by the SERS spectrum. The complex's stability is determined by the MD simulations at various speeds. The physiological scrutiny demonstrates that both the compound and complex are benign and the antiviral activities were studied for Nipah virus for the proteins 7pno and 7skt.

In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia

Stercularin is a coumarin, isolated from the ethyl acetate fraction of stem bark and leaves of S. diversifolia. Pharmacologically it is active against cancer, diabetes, and inflammation etc. The molecule is further screened for in vitro pharmacological activities. In addition, a detailed description on its drug likeness and pharmacokinetic profile has been established to further explore its fate as a drug candidate. Stercularin exhibited antiglycation, immunomodulatory, and leishmanicidal activity in three different in vitro models. The IC50 values obtained in these three assays were 80.22 ± 0.46 mg/ml, 12.8 ± 1.6 μg/ml, and 8.32 ± 0.42 μg/ml, respectively. In case of drug likeness evaluation, Stercularin has acceptable physicochemical properties and compliant with major drug likeness descriptors i.e., Lipinski rule, Pfizer rule, GSK rule, and "golden triangle". Accepting Lipinski rule implies the oral drug development of Stercularin. Pharmacokinetically, Stercularin is permeable to Caco-2 and MDCK cell lines. 'Boiled-egg' plot suggest intestinal route of absorption, blood brain barrier nonpermeating, and not affected by p-glycoprotein. Stercularin has high plasma protein binding with low free fraction circulating in the plasma. Stercularin proved to be the substrate and/or inhibitor of CYP 450 system with a moderate half-life and clearance rate to allow flexible dosing regimen. Finally, slight risk of toxicity exists for Stercularin, but not being limiting factors of drug knock out. A nature isolated Stercularin possess pharmacological activities and is predicted to have acceptable pharmacokinetic profile. Further drug development and in vivo studies are desirable for optimization.

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

Computational pharmacology and chemistry of drug-like properties along with pharmacokinetic studies have made it more amenable to decide or predict a potential drug candidate. 4-Hydroxyisoleucine is a pharmacologically active natural product with prominent antidiabetic properties. In this study, ADMETLab 2.0 was used to determine its important drug-related properties. 4-Hydroxyisoleucine is compliant with important drug-like physicochemical properties and pharma giants' drug-ability rules like Lipinski's, Pfizer, and GlaxoSmithKline (GSK) rules. Pharmacokinetically, it has been predicted to have satisfactory cell permeability. Blood-brain barrier permeation may add central nervous system (CNS) effects, while a very slight probability of being CYP2C9 substrate exists. None of the well-known toxicities were predicted in silico, being congruent with wet lab results, except for a "very slight risk" for respiratory toxicity predicted. The molecule is non ecotoxic as analyzed with common indicators such as bioconcentration and LC₅₀ for fathead minnow and daphnia magna. The toxicity parameters identified 4-hydroxyisoleucine as non-toxic to androgen receptors, PPAR-γ, mitochondrial membrane receptor, heat shock element, and p53. However, out of seven parameters, not even a single toxicophore was found. The density functional theory (DFT) study provided support to the findings obtained from drug-like property predictions. Hence, it is a very logical approach to proceed further with a detailed pharmacokinetics and drug development process for 4-hydroxyisoleucine.

Toward regulatory acceptance and improving the prediction confidence of in silico approaches: a case study of genotoxicity

Introduction: Genotoxicity is an imperative component of the human health safety assessment of chemicals. Its secure forecast is of the utmost importance for all health prevention strategies and regulations.Areas covered: We surveyed several types of alternative, animal-free approaches ((quantitative) structure-activity relationship (Q)SAR, read-across, Adverse Outcome Pathway, Integrated Approaches to Testing and Assessment) for genotoxicity prediction within the needs of regulatory frameworks, putting special emphasis on data quality and uncertainties issues.Expert opinion: (Q)SAR models and read-across approaches for in vitro bacterial mutagenicity have sufficient reliability for use in prioritization processes, and as support in regulatory decisions in combination with other types of evidence. (Q)SARs and read-across methodologies for other genotoxicity endpoints need further improvements and should be applied with caution. It appears that there is still large room for improvement of genotoxicity prediction methods. Availability of well-curated high-quality databases, covering a broader chemical space, is one of the most important needs. Integration of in silico predictions with expert knowledge, weight-of-evidence-based assessment, and mechanistic understanding of genotoxicity pathways are other key points to be addressed for the generation of more accurate and trustable results.