Tianjin Institute of Pharmaceutical Research Co., Ltd.

A series of novel potent HIV-1 protease inhibitors featuring diverse hydroxyaromatic acetanilide derivatives as P2 ligands and 4-substituted phenyl sulfonamides as P2' ligands were designed, synthesized, and biologically evaluated. The majority of the target compounds demonstrated potent enzyme inhibitory activity with IC₅₀ values below100 nM. Notably, compound 18h, incorporating a 2-(4-hydroxypyrimidin-5-yl) acetamide P2 ligand and a 4-methoxybenzenesulfonamide as the P2' ligand, exhibited exceptional potency with an enzyme IC₅₀ of 0.46 nM and antiviral EC₅₀ of 0.26 μM against HIV-1_NL4-3 strain. In addition, 18h displayed activity with EC₅₀ value of 0.25 μM against the subtype C HIV-1 Indie strain. The extensive hydrogen-bonding interactions with the protease active site revealed in the molecular docking analysis of 18h-bound HIV-1 protease provided valuable structural insights for the rational design of next-generation HIV-1 protease inhibitors.

The machine learning-based QSAR modeling procedure, molecular generations, and molecular dynamic simulations were applied to virtually screen the DNA polymerase theta inhibitors.

The DNA polymerase theta (Polθ or POLQ) is an attractive target for treatments of homologous recombination deficient (such as BRCA deficient) cancers. There are no approved drugs for targeting POLQ, and only one inhibitor is in Phase Ⅱclinical trials; thus, it is necessary to develop novel POLQ inhibitors.

To build machine learning models that predict the bioactivities of POLQ inhibitors. To build molecular generation models that generate diverse molecules. To virtually screen the generated molecules by the machine learning models. To analyze the binding modes of the screening results by molecular dynamic simulations.

In the present work, 325 inhibitors with POLQ polymerase domain bioactivities were Collected. Two machine learning methods, random forest and deep neural network, were used for building the ligand- and structure-based quantitative structure-activity relationship (QSAR) models. The substructure replacement-based method and transfer learning-based deep recurrent neural network method were used for molecular generations. Molecular docking and consensus QSAR models were carried out for virtual screening. The molecular dynamic simulations and MM/GBSA binding free energy calculation and decomposition were used to further analyze the screening results.

The MCC values of the best ligand- and structure-based consensus QSAR models reached 0.651 and 0.361 for the test set, respectively. The machine learning-based docking scores had better predicted ability to distinguish the highly and weakly active poses than the original docking scores. The 96490 molecules were generated by both molecular generation methods, and 10 molecules were retained by virtual screening. Four favorable interactions were concluded by molecular dynamic simulations.

The MCC values of the best ligand- and structure-based consensus QSAR models reached 0.651 and 0.361 for the test set, respectively. The machine learning-based docking scores had better-predicted ability to distinguish the highly and weakly active poses than the original docking scores. The 96490 molecules were generated by both molecular generation methods, and 10 molecules were retained by virtual screening. Four favorable interactions were concluded by molecular dynamic simulations.

We hope that the screening results and the binding modes are helpful for designing the highly active POLQ polymerase inhibitors and the models of the molecular design workflow can be used as reliable tools for drug design.

Cotinus coggygria Scop. (syn Rhus cotinus L.), a plant with a longstanding medicinal history, has been traditionally employed in Asian ethnomedicine for the management of hepatic disorders and gastrointestinal ailments.

This review systematically evaluates the ethnomedicinal applications, phytochemical profile, pharmacological properties, clinical relevance, and safety data of C. coggygria to establish a foundation for its rational development as a therapeutic agent in TCM.

A thorough literature search was carried out in several main databases (ScienceDirect, SciFinder, Wan Fang Database, Web of Science, PubMed, CNKI, Google Scholar and Baidu Scholar) and botanical nomenclature databases (The Plant List). The search used keywords such as "Cotinus coggygria," "Rhus coggygria," and all the taxonomic synonyms of this species.

Phytochemical investigations of C. coggygria have identified over 300 constituents, with 57 purified compounds characterized to date. Phenolic derivatives dominate the isolated compounds, while terpenoid-rich volatile oils constitute the majority of leaf components. Bioactivity assessments of C. coggygria reveal broad therapeutic potential, including hepatoprotective, antioxidant, cytotoxic, anti-inflammatory, antimicrobial, and anticoagulant effects. Flavonoid constituents emerge as the primary bioactive contributors, supported by mechanistic studies.

Despite centuries of ethnomedicinal use with minimal documented adverse effects, current clinical validation of C. coggygria remains limited to hepatic disorders. Critical research gaps persist in elucidating molecular mechanisms, dose-response relationships, and long-term safety profiles. Robust preclinical investigations and standardized clinical trials are imperative to substantiate the therapeutic promise of this species.