QSAR

The United States Environmental Protection Agency (USEPA) uses the lethal dose 50% (LD50 ) value from in vivo rat acute oral toxicity studies for pesticide product label precautionary statements and environmental risk assessment (RA). The Collaborative Acute Toxicity Modeling Suite (CATMoS) is a quantitative structure-activity relationship (QSAR)-based in silico approach to predict rat acute oral toxicity that has the potential to reduce animal use when registering a new pesticide technical grade active ingredient (TGAI)...

BACKGROUND: Serum transaminases, alkaline phosphatase and bilirubin are common parameters used for DILI diagnosis, classification, and prognosis. However, the relevance of clinical examination, histopathology and drug chemical properties have not been fully investigated. As cholestasis is a frequent and complex DILI manifestation, our goal was to investigate the relevance of clinical features and drug properties to stratify drug-induced cholestasis (DIC) patients, and to develop a prognosis model to identify patients at risk and high-concern drugs...

Fuchsine acid serves as a supramolecular dye in Masson's trichrome stain, finding extensive applications in histology. It is also utilized with picric acid in Van Gieson's method to reveal red collagen fibers and in Masson's trichrome to highlight smooth muscle in contrast to collagen. Beyond these applications, it plays a crucial role in electronic fields and photonic devices as an organic semiconductor. Therefore, investigating and predicting the complex molecular structure of fuchsine acid becomes essential, serving as the foundation for understanding its physicochemical features...

Models of toxicity to tadpoles have been developed as single parameters based on special descriptors which are sums of correlation weights, molecular features, and experimental conditions. This information is presented by quasi-SMILES. Fragments of local symmetry (FLS) are involved in the development of the model and the use of FLS correlation weights improves their predictive potential. In addition, the index of ideality correlation ( IIC ) and correlation intensity index ( CII ) are compared. These two potential predictive criteria were tested in models built through Monte Carlo optimization...

This study developed multi-linear regression (MLR) quantitative structure-activity relationships (QSARs) to predict n -TiO2 aggregation in the presence of high concentrations of representative emerging organic contaminants (EOCs), which presented favorable conditions to interaction with n -TiO2 . The largest diameter change (Δ 517 nm at 0 h and Δ 1164 nm at 12 h) of n -TiO2 was observed by estrone, while the smallest diameter change (Δ -114 nm at 0 h and - 4 nm at 12 h) was observed by lincomycin during experimental periods...

Simulation of the physicochemical and biochemical behavior of nanomaterials has its own specifics. However, the main goal of modeling for both traditional substances and nanomaterials is the same. This is an ecologic risk assessment. The universal indicator of toxicity is the n-octanol/water partition coefficient. Mutagenicity indicates the possibility of future undesirable environmental effects, possibly greater than toxicity. Models have been proposed for the octanol/water distribution coefficient of gold nanoparticles and the mutagenicity of silver nanoparticles...

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0...

Cyclooctane is a cycloalkane consisting of carbon and hydrogen atoms arranged in a closed ring structure. Cyclooctane chains can be found in various organic compounds and are significant in the field of organic chemistry due to their diverse reactivity and properties. The atom-bond connectivity index ( <mml:math xmlns:mml="https://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>A</mml:mi> <mml:mi>B</mml:mi> <mml:mi>C</mml:mi></mml:mrow> </mml:math> ), the geometric-arithmetic index ( <mml:math xmlns:mml="https://www...

Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life is of great significance in drug design. In this study, we emplo<u>yed</u> eXtreme Gradient Boosting (XGboost), randomForest (RF), gradient boosting machine (GBM), and supporting vector machine (SVM) to build quantitative structure-activity relationship (QSAR) models on 3512 compounds and evaluated model performance by using root-mean-square error (RMSE), R 2 , and mean absolute error (MAE) metrics and interpreted features by SHapley Additive exPlanation (SHAP)...

Sophoridine, which is derived from the Leguminous plant Sophora alopecuroides L., has certain pharmacological activity as a new anticancer drug. Herein, a series of novel N-substituted sophoridine derivatives was designed, synthesized and evaluated with anticancer activity. Through QSAR prediction models, it was discovered that the introduction of a benzene ring as a main pharmacophore and reintroduced into a benzene in para position on the phenyl ring in the novel sophoridine derivatives improved the anticancer activity effectively...

Curcumin (C21 H20 O6 ) is a polyphenol found in the plant Curcuma longa . Even though it possesses many pharmacological effects, owing to its limited intestinal absorption, solubility, and oral bioavailability, it is more often used as a health supplement than as a lead chemical. The poly(amido)amine (PAMAM) dendrimer (nanostructure) is utilized to enhance the stability and targeted delivery of drugs. Recently, curcumin was conjugated with the PAMAM dendrimer and analyzed for its photostability. Further investigation into the physiochemical characteristics of different generations can facilitate curcumins' targeted delivery for many diseases, including cancer...

The dopamine transporter (DAT) plays a critical role in the central nervous system and has been implicated in numerous psychiatric disorders. The ligand-based approaches are instrumental to decipher the structure-activity relationship (SAR) of DAT ligands, especially the quantitative SAR (QSAR) modeling. By gathering and analyzing data from literature and databases, we systematically assemble a diverse range of ligands binding to DAT, aiming to discern the general features of DAT ligands and uncover the chemical space for potential novel DAT ligand scaffolds...

VEGFR-2 kinase inhibitors are clinically approved drugs that can effectively target cancer angiogenesis. However, such inhibitors have adverse effects such as skin toxicity, gastrointestinal reactions and hepatic impairment. In this study, machine learning and Topomer CoMFA, which is an alignment-dependent, descriptor-based method, were employed to build structural activity relationship models of potentially new VEGFR-2 inhibitors. The prediction ac-curacy of the training and test sets of the 2D-SAR model were 82...

BACKGROUND: The significant public health effect of breast cancer is demonstrated by its high global prevalence and the potential for severe health consequences. The suppression of the proliferative effects facilitated by the estrogen receptor alpha (ERα) in the MCF-7 cell line is significant for breast cancer therapy. OBJECTIVE: The current work involves in-silico techniques for identifying potential inhibitors of ERα. METHODS: The method combines QSAR models based on machine learning with molecular docking to identify potential binders for the ERα...

To increase the structural diversity of insecticides and meet the needs of effective integrated insect management, the structure of chlorantraniliprole was modified based on a previously established three-dimensional quantitative structure-activity relationship (3D-QSAR) model. The pyridinyl moiety in the structure of chlorantraniliprole was replaced with a 4-fluorophenyl group. Further modifications of this 4-fluorophenyl group by introducing a halogen atom at position 2 and an electron-withdrawing group (e...

Asparagine (Asn) deamidation and aspartic acid (Asp) isomerization are common degradation pathways that affect the stability of therapeutic antibodies. These modifications can pose a significant challenge in the development of biopharmaceuticals. As such, the early engineering and selection of chemically stable monoclonal antibodies (mAbs) can substantially mitigate the risk of subsequent failure. In this study, we introduce a novel in silico approach for predicting deamidation and isomerization sites in therapeutic antibodies by analyzing the structural environment surrounding asparagine and aspartate residues...

Understanding the features of compounds that determine their high serotonergic activity and selectivity for specific receptor subtypes represents a pivotal challenge in drug discovery, directly impacting the ability to minimize adverse events while maximizing therapeutic efficacy. Up to now, this process has been a puzzle and limited to a few serotonergic targets. One approach represented in the literature focuses on receptor structure whereas in this study, we followed another strategy by creating AI-based models capable of predicting serotonergic activity and selectivity based on ligands' representation by molecular descriptors...

Machine learning techniques are extensively employed in drug discovery, with a significant focus on developing QSAR models that interpret the structural information of potential drugs. In this study, the pre-trained natural language processing (NLP) model, ChemBERTa, was utilized in the drug discovery process. We proposed and evaluated four core model architectures as follows: deep neural network (DNN), encoder, concatenation (concat), and pipe. The DNN model processes physicochemical properties as input, while the encoder model leverages the simplified molecular input line entry system (SMILES) along with NLP techniques...

The farnesoid X receptor (FXR) has been recognized as a potential drug target for the treatment of non-alcoholic fatty liver disease (NAFLD). FXR agonists benefit NAFLD by modulating bile acid synthesis and transport, lipid metabolism, inflammation, and fibrosis pathways. However, there are still great challenges involved in developing safe and effective FXR agonists. To investigate the critical factors contributing to their activity on the FXR, 3D-QSAR molecular modeling was applied to a series of isoxazole derivatives, using comparative molecular field analysis (CoMFA (q2 = 0...

No abstract text is available yet for this article.