The paper investigates the process of degumming substandard soybean oil using an enzyme complex of phospholipases to prepare it as a feedstock for biodiesel production. Dehumidification is an important refining step aimed at reducing the phosphorus content, which exceeds the permissible limits according to ASTM, EN, and ISO standards, by re-moving phospholipids. The enzyme complex of phospholipases includes phospholipase C, which specifically targets phosphatidylinositol, and phospholipase A2, which catalyzes the hydrolysis of phospholipids into water-soluble phosphates and lysophospholipids. This process contributes to the efficient removal of phospholipids, increased neutral oil yield, and reduced residual oil in the humic phase. The use of an enzyme complex of phospholipases provides an innovative, cost-effective, and environmentally friendly method of oil purification. The results of the study demonstrate the high efficiency of using the phospholipase enzyme complex in the processing of substandard soybean oil, which allows reducing the content of total phosphorus to 0.001% by weight, turning it into a high-quality raw material for biodiesel production. The proposed approach contributes to increasing the profitability of agricultural raw materials and the introduction of environmentally friendly technologies in the field of renewable energy.

Surfactin is an amphiphilic lipopeptide, composed of a cyclic heptapeptide linked to a β-hydroxy fatty acid. This structural configuration gives rise to its remarkable biosurfactant properties. The synthesis is performed by a non-ribosomal peptide synthesis mechanism that involves surfactin synthetase, a multi-enzyme complex encoded by the srfA operon. The expression of this operon and surfactin synthetase activity are regulated by quorum sensing pathways such as Rap-Phr and ComXQPA controlling natural competence, YcxA and YerP efflux pumps, sporulation phosphorelay and degradative enzymes as well as surfactin-regulated pathways. The objective of this manuscript is to review well-studied regulatory metabolic pathways of Bacillus subtilis that control surfactin biosynthesis and to construct a global metabolic regulatory network in order to design the most efficient metabolic engineering strategies to improve surfactin production while maintaining strain stability. The surfactin synthesis regulatory network was built using KEGG pathway maps for two-component systems, quorum sensing, bacterial secretion, and ABC transporters. Most genes and interactions were based on Bacillus subtilis subsp. subtilis str. 168. Gene details were obtained from the NCBI database. The network map was created manually using Canva’s flowchart tool. Modifications in amino acid and fatty acid precursor pathways did not have a significant impact on surfactin yield despite an increase in amino acid availability. The modification of genes involved in quorum sensing pathways has been associated with the regulation of natural competence development and cell cycle progression. For example, srfA promoter replacement and comA overexpression resulted in a significant enhancement of srfA operon expression and surfactin production. The overexpression of efflux pumps ycxA and yerP resulted in enhanced surfactin secretion and increased self-resistance to surfactin. In contrast the deletion of sporulation genes resulted in an increase in surfactin yield per biomass; however, it caused inhibition of growth. Knockout of biofilm-related genes and competing lipopeptide pathways resulted in an increase in surfactin yield. A hypothesis of triple-mutant strain combining comA overexpression, ycxA and yerP enhanced efflux transport, and kinC deletion was proposed based on the constructed regulatory metabolic network that theoretically can improve surfactin yield and strain stability; however, further validation is required to assess potential unintended effects.

The production of high-quality biodiesel from vegetable oils requires an integrated approach that considers feedstock quality, transesterification, and final product purification. This study investigates a comprehensive technological sequence for soybean biodiesel production combining enzymatic degumming, treatment with biosurfactant-containing microbial culture fluid, cavitation-assisted transesterification, and adsorptive dry purification. Enzymatic pretreatment using the multienzyme preparation Purifine^® 3G in combination with culture fluid obtained from Pseudomonas fluorescens cultivation was associated with reductions in residual phosphorus and sulfur contents and acid value, potentially due to improved enzyme-substrate interactions, although increasing the culture-fluid dosage prolonged phase separation. Cavitation-assisted transesterification produced biodiesel with a higher fatty acid methyl ester (FAME) mass fraction than conventional stirred-reactor processing under the investigated operating conditions, while spectroscopic and chromatographic analyses confirmed the formation of products with similar FAME profiles. A comparative evaluation of three purification schemes demonstrated that direct adsorptive dry purification using natural clinoptilolite provided the highest FAME mass fraction without requiring an additional water-washing step. Industrial-scale testing confirmed the applicability of clinoptilolite-based adsorptive conditioning for reducing residual water content while maintaining a high ester content. Overall, the findings support the technical feasibility of integrating enzymatic feedstock pretreatment, transesterification, and adsorptive conditioning into soybean biodiesel production and identify key aspects for further process optimization and industrial validation.

The development of novel antiepileptic agents requires early identification of pharmacokinetic limitations to mitigate risks at later stages. This study aimed to perform in silico profiling of a library containing 448 novel 2H,5H-chromeno[4’,3’:4,5]thiopyrano[2,3-d]thiazol-2-one derivatives to select lead compounds with an optimal balance of safety and efficacy. The study was conducted using the ADMET-AI platform, based on a graph neural network, to predict physicochemical, pharmacokinetic, and toxicological properties. The methodology involved calculating drug-likeness descriptors for primary screening and a comparative statistical analysis of the top 20 selected structures against 16 approved antiepileptic drugs and four reference compounds. Based on drug-likeness descriptors and predicted ADMET (absorption, distribution, metabolism, excretion, toxicity) related parameters, 20 structures were prioritized for further analysis. Their predicted profiles suggested high intestinal absorption and blood–brain barrier (BBB) permeability, which may be relevant for central nervous system (CNS) directed agents. In comparison with the reference thiazolidinones, the prioritized compounds showed comparatively more favorable predicted mutagenicity and carcinogenicity profiles. Elevated predicted risks of hepatotoxicity and cardiotoxicity were observed for several structures, indicating the need for further structural optimization. The results suggest that the thiopyranothiazolidinone scaffold merits further anticonvulsant-oriented investigation at the stage of early compound prioritization. Experimental validation will be required to confirm the actual pharmacokinetic, toxicological, and anticonvulsant properties of the prioritized compounds.