3D QSAR and pharmacophore study of curcuminoids and curcumin analogs: Interaction with thioredoxin reductase

Inhibition of the thioredoxin system for radiosensitization therapy of cancer

Radiotherapy (RT) stands as a cornerstone in the clinical armamentarium against various cancers due to its proven efficacy. However, the intrinsic radiation resistance exhibited by cancer cells, coupled with the adverse effects of RT on normal tissues, often compromises its therapeutic potential and leads to unwanted side effects. This comprehensive review aims to consolidate our understanding of how radiosensitizers inhibit the thioredoxin (Trx) system in cellular contexts. Notable radiosensitizers, including gold nanoparticles (GNPs), gold triethylphosphine cyanide ([Au(SCN) (PEt3)]), auranofin, ceria nanoparticles (CONPs), curcumin and its derivatives, piperlongamide, indolequinone derivatives, micheliolide, motexafin gadolinium, and ethane selenide selenidazole derivatives (SeDs), are meticulously elucidated in terms of their applications in radiotherapy. In this review, the sensitization mechanisms and the current research progress of these radiosensitizers are discussed in detail, with the overall aim of providing valuable insights for the judicious application of Trx system inhibitors in the field of cancer radiosensitization therapy.

Toxicity and Antigenotoxic Effect of Hispolon Derivatives: Role of Structure in Modulating Cellular Redox State and Thioredoxin Reductase

Hispolon (HS), a bioactive polyphenol, and its derivatives such as hispolon monomethyl ether (HME), hispolon pyrazole (HP), and hispolon monomethyl ether pyrazole (HMEP) were evaluated for comparative toxicity and antigenotoxic effects. The stability of HS derivatives in biological matrices followed the order HS < HP ≈ HME < HMEP. The cytotoxicity analysis of HS derivatives indicated that HP and HMEP were less toxic than HS and HME, respectively, in both normal and tumor cell types. The mechanisms of toxicity of HS and HME involved inhibition of thioredoxin reductase (TrxR) and/or induction of reductive stress. From the enzyme kinetic and docking studies, it was established that HS and HME interacted with the NADPH-binding domain of TrxR through electrostatic and hydrophobic bonds, resulting in inhibition of the catalytic activity. Subsequently, treatment with HS, HP, and HMEP at a nontoxic concentration of 10 μM in Chinese Hamster Ovary (CHO) cells showed significant protection against radiation (4 Gy)-induced DNA damage as assessed by micronuclei and γ-H2AX assays. In conclusion, the above results suggested the importance of phenolic and diketo groups in controlling the stability and toxicity of HS derivatives. The pyrazole derivatives, HP and HMEP, may gain significance in the development of functional foods.

Triazole-curcuminoids: A new class of derivatives for 'tuning' curcumin bioactivities?

Curcumin is a unique blend of pharmacophores responsible for the pleiotropy of this natural pigment. In the present study we have replaced the 1,3-dicarbonyl moiety with a 1,2,3-triazole ring to furnish a new class of triazole-curcuminoids as a possible strategy to generate new compounds with different potency and selectivity compared to curcumin. We obtained a proof-of-principle library of 28 compounds tested for their cytotoxicity (SY-SY5Y and HeLa cells) and for their ability to inhibit NF-κB. Furthermore, we also generated 1,3-dicarbonyl curcuminoids of selected click compounds. Triazole-curcuminoids lost their ability to be Michael's acceptors, yet maintained some of the features of the parent compounds and disclosed new ones. In particular, we found that some compounds were able to inhibit NF-κB without showing cytotoxicity, while others, unlike curcumin, activated NF-κB signalling. This validates the hypothesis that click libraries can be used to investigate the biological activities of curcumin as well as generate analogs with selected features.

Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC₅₀ units from measured inhibition affinities and a Pearson’s correlation coefficient R² of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors.

Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming

Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R²) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.