Deep active learning with high structural discriminability for molecular mutagenicity prediction.

The assessment of mutagenicity is essential in drug discovery, as it may lead to cancer and germ cells damage. Although in silico methods have been proposed for mutagenicity prediction, their performance is hindered by the scarcity of labeled molecules. However, experimental mutagenicity testing can be time-consuming and costly.

SERS-active immunoassay kit for SARS-CoV‑2 mediated by the cooperative chemical and electromagnetic effects of MXene modified with gold nanowires.

Surface-enhanced Raman scattering (SERS) technique with high sensitivity, reliable specificity, and rapid recognition ability exhibits attractive promise for the effective fast-monitoring of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, a novel SERS-active immunoassay kit for SARS-CoV-2 nucleocapsid (N) protein was prepared by in-situ growing gold (Au) nanowire forests (NFs) onto TiCT, which was then modified onto polymethyl methacrylate (PMMA) matrix and encapsulated into kit. It was noted that the Au nanowires with fibrous structures which vertically anchored on TiCT served as perfect channels to promote photo-induced charge transfer.

Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications.

Introduction: Castor bean or ricin-induced intoxication or terror events have threatened public security and social safety. Potential resources or materials include beans, raw extraction products, crude toxins, and purified ricin. The traceability of the origins of castor beans is thus essential for forensic and anti-terror investigations.

TOXRIC: a comprehensive database of toxicological data and benchmarks.

The toxic effects of compounds on environment, humans, and other organisms have been a major focus of many research areas, including drug discovery and ecological research. Identifying the potential toxicity in the early stage of compound/drug discovery is critical. The rapid development of computational methods for evaluating various toxicity categories has increased the need for comprehensive and system-level collection of toxicological data, associated attributes, and benchmarks.

Rapid and highly selective colorimetric detection of mercury(II) ions in water sources based on a ribavirin functionalized AuNP sensor.

Solvated mercuric ions (Hg), a toxic and harmful water pollutant, can easily accumulate in organisms and cause serious damage to the kidney, liver, and central nervous system. To realize rapid and efficient detection of mercury (II) ions in water sources, a kind of new colorimetric sensor of gold nanoparticles (AuNPs) functionalized with ribavirin (Rib-AuNPs) was proposed and characterized by TEM, DLS, XRD, and UV-vis in this work. The color of the Rib-AuNP solution rapidly changed from wine-red to gray-blue with the addition of Hg based on the aggregation mechanism.

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning.

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI.

Computational methods, databases and tools for synthetic lethality prediction.

Synthetic lethality (SL) occurs between two genes when the inactivation of either gene alone has no effect on cell survival but the inactivation of both genes results in cell death. SL-based therapy has become one of the most promising targeted cancer therapies in the last decade as PARP inhibitors achieve great success in the clinic. The key point to exploiting SL-based cancer therapy is the identification of robust SL pairs.