Assessing biodegradability potential of organic chemicals in aquatic and soil environment through classification-based machine learning models developed in accordance with OECD standards.

Information on the biodegradation potential of organic chemicals in the ecosystem helps us analyze their persistence, bioaccumulation, and toxicity (PBT) behaviour. The environment is exposed to many chemicals from various sources, both intentionally and unintentionally. A preliminary assessment of chemical biodegradation prospects allows for early screening of their persistence and further analysis of their bioaccumulation potential and toxicity hazards.

Quantitative read-across structure-property relationship (q-RASPR)-based lipid-normalized dietary biomagnification (BMF) prediction: A framework for evaluating biomagnification potential of organic chemicals in the aquatic ecosystem.

The persistence, bioaccumulation and toxicity (PBT) potential of organic chemicals is used to assess the hazards associated with them. Predicting the biomagnification potential of chemicals in fish reflects their persistence or accumulation in the organisms of the upper trophic levels. The quantitative read-across structure-property relationship (q-RASPR) methodology has evolved in recent years and showcased its effective predictive potential through combining the advantages of both quantitative structure-property relationship (QSPR) and read-across (RA).

Molecular Mechanisms Underlying the Spectral Shift in Zebrafish Cone Opsins.

Visual pigments are essential for converting light into electrical signals during vision. Composed of an opsin protein and a retinal-based chromophore, pigments in vertebrate rods (Rh1) and cones (Rh2) have different spectral sensitivities, with distinct peak absorption wavelengths determined by the shape and composition of the chromophore binding pocket. Despite advances in understanding Rh1 pigments such as bovine rhodopsin, the molecular basis of spectral shifts in Rh2 cone opsins has been less studied, particularly the E122Q mutation, which accounts for about half of the observed spectral shift in these pigments.

Enhanced catabolism of glycine betaine and derivatives provides improved osmotic stress protection in PA1.

Integration of metabolites into the overall metabolic network of a cell requires careful coordination dependent upon the ultimate usage of the metabolite. Different stoichiometric needs, and thus pathway fluxes, must exist for compounds destined for diverse uses, such as carbon sources, nitrogen sources, or stress-protective agents. Herein, we expand upon our previous work that highlighted the nature of glycine betaine (GB) metabolism in Methylobacteria to examine the utilization of GB-derivative compounds dimethylglycine (DMG) and sarcosine into in different metabolic capacities, including as sole nitrogen and/or carbon sources.

Artificial intelligence and machine learning for protein toxicity prediction using proteomics data.

Instead of only focusing on the targeted drug delivery system, researchers have a great interest in developing peptide-based therapies for the procurement of numerous class of diseases. The main idea behind this is to anchor the properties of the receptor to design peptide-based therapeutics. As these macromolecules have distinct physicochemical properties over small molecules, it becomes an obligatory field for the treatment of diseases.