P Rani,K Dutta,V Kumar
P Rani
Malignant diseases are considered the most prominent and widespread causes of death affecting populations globally. Synergistic drug combinations have shown beneficial therapeutic results in the treatment of malignant diseases. Although tec...
Ionic liquids as emerging environmental contaminants: a critical review of fate, toxicity mechanisms, and sustainable design strategies [0.03%]
离子液体新兴环境污染物本体：命运、毒性机制及可持续设计策略批判性评述
D Wang,H Ren,H Liu
D Wang
Ionic liquids (ILs) are increasingly detected in various environments, raising profound concerns regarding their ecological impacts and long-term sustainability. While their tunability offers immense application potential, it concurrently i...
Integrated chemometric modelling of histamine H3 receptor for the identification of ligands from a natural product repository [0.03%]
整合化学计量学模型组胺H3受体识别来自天然产品仓库配体
N S Jandali,L A Samuor,K Tawaha et al.
N S Jandali et al.
The histamine H3 receptor (H3R) is a GPCR that regulates the release of multiple neurotransmitters and has emerged as an attractive target for CNS disorders. An integrated computational workflow was applied to identify H3R ligands from natu...
Linear models, quantum molecular descriptors, and DSSC efficiency: an approach for evaluating potential new sensitizing dyes [0.03%]
线性模型、量子分子描述符和DSSC效率：评估潜在新敏化染料的一种方法
E F S Mattos,I F Vieira,G S Mendonça et al.
E F S Mattos et al.
The growing energy demand has accelerated the search for renewable energy sources, with dye-sensitized solar cells (DSSCs) emerging as promising candidates. To streamline the experimental process and reduce associated costs, we developed pr...
QSPR models for water solubility of organic compounds using correlation intensity index and Las Vegas algorithm [0.03%]
基于相关强度指数和拉斯维加斯算法的有机物水溶性QSAR模型研究
A P Toropova,A A Toropov,G Selvestrel et al.
A P Toropova et al.
Water solubility is an important factor in environmental and toxicological science because it determines the mobility, bioavailability, and potential for absorption by living organisms. Higher solubility often correlates with greater enviro...
Mitigating silent failures in toxicity prediction: a conformalized heteroscedastic Bayesian framework [0.03%]
一种异方差贝叶斯框架下的毒性预测隐蔽失效的缓解方法
B Özlüer Başer
B Özlüer Başer
Accurate uncertainty quantification is a prerequisite for reliable toxicity assessments in drug discovery. Traditional QSAR models provide point estimates but fail to communicate prediction reliability, particularly for structurally complex...
Network toxicology and molecular docking elucidation of oligoasthenospermia induced by bisphenol analogues: a comparative study of BPA, BPS, BPF, and BPAF [0.03%]
双酚类化合物所致弱畸精子症的网络毒理学及分子对接阐释：以BPA、BPS、BPF和BPAF为例比较研究
H He,J Li,J Liu et al.
H He et al.
Bisphenol A (BPA) substitutes are increasingly prevalent in consumer products, yet their potential to induce oligoasthenospermia (OAS) remains poorly understood. This study combined network toxicology, molecular docking, and 500-ns molecula...
Optima: a GUI-based toolkit for developing and validating interpretable machine learning based supervised classification QSAR models [0.03%]
Optima：一个基于GUI的工具包，用于开发和验证可解释的机器学习QSAR分类模型
I Dasgupta,R Roy,S Gayen
I Dasgupta
The rapid advancement of ML algorithms and the increasing availability of large datasets have significantly transformed the landscape of predictive modelling in scientific research. In this context, we introduce Optima (OPTimized Interpreta...
Prediction of acetylcholinesterase inhibition associated with Alzheimer's disease using hybrid descriptor and graph-based machine learning models [0.03%]
基于混合描述符和图神经网络的乙酰胆碱酯酶抑制剂预测模型用于阿尔茨海默氏症研究
R U Laskar,B S Meena,A Roy et al.
R U Laskar et al.
Accurate prediction of acetylcholinesterase (AChE) inhibitory activity is important in drug discovery and environmental toxicology because AChE inhibition represents a key mechanism underlying neurotoxicity associated with pharmaceuticals a...
Systematic evaluation of data preprocessing and model selection strategies for reliable pIC50 prediction of acetylcholinesterase inhibitors [0.03%]
E Delibaş,H I Güler
E Delibaş
Predicting acetylcholinesterase (AChE) inhibitory activity is important in drug discovery. This study evaluates molecular descriptor - based machine learning models to predict AChE activity as pIC50 values. The primary objective was to comp...