The paper discusses a comprehensive analysis of contemporary approaches to the structural modification of phenolic acids from the benzoic (C₆–C₁) and cinnamic (C₆–C₃) series, which have a wide range of biological activity. The main directions of chemical transformation of phenolic compounds that aim to improve their pharmaco-logical potential, stability, and bioavailability are discussed. The given study also makes an accent on the relationship between the structural features and biological effects of various phenolic acid derivatives, including antioxidant, anti-inflammatory, antimicrobial, and antitumor activity. The purpose of this investigation is to systematize current data on strategies for the structural modification of phenolic acids, to identify key areas of their chemical transformation, and to determine the most promising methods for creating biologically active compounds with improved pharmacological properties. The study was aimed at systematizing the accumulated knowledge and identifying promising areas for further research in the field of structural design of phenolic acid derivatives. Based on the analysis of experimental data and literature sources, key trends in the development of new medicinal compounds using the example of natural phenolic acids were characterized, and prospects for their use in medicine and pharmaceutical chemistry were shown.

This review examines the emerging role of machine learning (ML) in pharmaceutical chemistry, with emphasis on molecular design, synthetic feasibility, and structure–property–performance (SPP) relationships. By enabling pre-synthesis prediction of physicochemical properties, reaction pathways, and pharmaceutical performance, ML can reduce empirical trial-and-error experimentation and support more efficient exploration of chemical space. A structured narrative review design with PRISMA-aligned systematic search elements was used to evaluate 101 studies, enabling transparent literature identification, eligibility screening, and thematic synthesis across heterogeneous ML applications in pharmaceutical chemistry. This review examines structure–property relationships (SPRs) and property–performance relationships (PPRs), with emphasis on key pharmaceutical endpoints such as solubility, permeability, stability, dissolution, and bioavailability. An integrated SPP framework is proposed to connect molecular structure, intermediate properties, and final performance outcomes while incorporating retrosynthetic analysis and experimental feedback and closed-loop optimization. Recent frontier developments are also discussed, including molecular foundation models, multimodal language–graph models, diffusion-based molecular generation, E(3)-equivariant models, and MolMIM-like latent-space optimization. This review also covers co-folding and joint ligand–protein modeling, Boltz-2-like affinity prediction, AlphaFold 3-related biomolecular interaction modeling, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction. Key limitations include dataset leakage, benchmark inconsistency, assay variability, conformational and protonation-state effects, reproducibility challenges, regulatory constraints, and the gap between computational prediction and prospective experimental validation. Future progress is expected to depend on hybrid physics–ML models, uncertainty-aware prospective validation, autonomous experimentation, explainable artificial intelligence, and sustainability-aware molecular design. Overall, ML is evolving from a predictive tool into a chemically informed decision-support framework for rational, synthesis-aware, and experimentally validated pharmaceutical development.

This study systematically investigated lipophilic and polar metabolites of Atraphaxis virgata (Polygonaceae) and assessed its immunomodulatory activity in vivo. Supercritical CO₂ extraction of the aerial parts yielded a lipophilic fraction analyzed by means of gas chromatography–mass spectrometry (GC–MS), which identified 42 compounds, including fatty acid esters, sterols, hydrocarbons, and terpenoids. The residual plant meal was subjected to ultrasound-assisted extraction with 70% aqueous ethanol at 30–35 °C, using a solid-to-solvent ratio of 1:8 for 120 min. This polar extract was evaluated for amino acids, proteins, and carbohydrates, while solvent–solvent partitioning with chloroform, ethyl acetate, and water enabled isolation of phenolic- and flavonoid-enriched fractions. Six phenolic constituents, including four flavonol glycosides and two phenolic acids, were structurally confirmed. The extracts were rich in unsaturated fatty acids and water-soluble antioxidants, supporting their nutritional and pharmacological relevance. In vivo evaluation using a cyclophosphamide-induced myelosuppression model in Wistar rats demonstrated stimulation of erythropoiesis and leukopoiesis, confirming immunomodulatory potential. Collectively, this work provides the first comprehensive chemical and biological characterization of A. virgata and establishes a foundation for mechanistic studies and pharmacological validation.

Atraphaxis virgata and Atraphaxis pyrifolia are xerophytic species of the Polygonaceae family that remain insufficiently characterized from pharmacognostic, phytochemical, and toxicological perspectives. This study provides an integrated evaluation of both species through anatomical authentication, sequential extraction of CO₂-extracted residual biomass, GC–MS and LC–MS metabolite profiling, and acute oral toxicity assessment. Anatomical analysis revealed shared xeromorphic traits, including cuticular protection, dorsiventral mesophyll organization, structured vascular bundles, and calcium oxalate druses. It also identified species-specific differences in leaf thickness, mesophyll arrangement, vascular architecture, and druse morphology. GC–MS analysis showed distinct chemical profiles: A. virgata displayed a concentrated profile dominated by acetophenone- and benzofuran-related constituents, whereas A. pyrifolia showed a broader spectrum of carbohydrate-derived, phenolic-related, and oxygenated constituents. LC–MS analysis supported the tentative annotation of diverse polyphenolic classes, including flavonoids, phenolic acids, coumarins, and phenylpropanoid derivatives. Acute oral toxicity testing showed no mortality at doses up to 2000 mg/kg, supporting a low acute oral toxicity classification under the tested conditions. However, histological examination revealed mild to moderate dose-dependent alterations in liver and kidney tissues at higher doses. The novelty of this work lies in linking diagnostic anatomical traits, species-specific metabolite patterns, residual biomass valorization, and preliminary safety evidence within a single comparative framework. These findings provide a basis for pharmacognostic authentication, phytochemical standardization, and future bioactivity-guided evaluation of Atraphaxis species.