Toxicity of plant extracts containing pyrrolizidine alkaloids using alternative invertebrate models

Pyrrolizidine alkaloids (PAs) are a widespread class of hepatotoxic heterocyclic organic compounds found in approximately 3% of world flora. Some PAs have been shown to have genotoxic and carcinogenic effects. The present study focuses on the toxicity effects of four dry extracts obtained from medicinal plants (Senecio vernalis, Symphytum officinale, Petasites hybridus and Tussilago farfara), on two aquatic organisms, Artemia salina and Daphnia magna, and the correlation with their PAs content. A new GC‑MS method, using a retention time (TR)‑5MS type capillary column was developed. PAs Kovats retention indices, for this type of column were computed for the first time. The lethal dose 50% (LC50) values for the two invertebrate models were correlated (Pearson 's coefficient, >0.9) and the toxicity was PA concentration-dependent, for three of the four extracts. All tested extracts were found to be toxic in both aquatic organism models. The results can be used to develop a GC‑MS validated method for the assay of PAs in medicinal plants with a further potential application in the risk assessment study of PAs toxicity in humans

IBUPROFEN, A DRUG USED IN PAIN, INFLAMMATION AND FEVER

Ibuprofen is a non-steroidal antiinflammatory drug (NSAID) derived from propionic acid, used on a large scale both in adults and children for the treatment of pain, fever and inflammation of different etiologies. Many randomized clinical trials controlled against placebo or active substances support the efficacy of ibuprofen, administered alone or in combinations, single or repeated dose, in these pathological states. Literature safety data show that ibuprofen is one of the most utilized NSAIDs owing to its efficacy and reduced adverse events profile

In Silico Drug Repurposing Framework Predicts Repaglinide, Agomelatine and Protokylol as TRPV1 Modulators with Analgesic Activity

Pain is one of the most common symptoms experienced by patients. The use of current analgesics is limited by low efficacy and important side effects. Transient receptor potential vanilloid-1 (TRPV1) is a non-selective cation channel, activated by capsaicin, heat, low pH or pro-inflammatory agents. Since TRPV1 is a potential target for the development of novel analgesics due to its distribution and function, we aimed to develop an in silico drug repositioning framework to predict potential TRPV1 ligands among approved drugs as candidates for treating various types of pain. Structures of known TRPV1 agonists and antagonists were retrieved from ChEMBL databases and three datasets were established: agonists, antagonists and inactive molecules (pIC50 or pEC50 < 5 M). Structures of candidates for repurposing were retrieved from the DrugBank database. The curated active/inactive datasets were used to build and validate ligand-based predictive models using Bemis–Murcko structural scaffolds, plain ring systems, flexophore similarities and molecular descriptors. Further, molecular docking studies were performed on both active and inactive conformations of the TRPV1 channel to predict the binding affinities of repurposing candidates. Variables obtained from calculated scaffold-based activity scores, molecular descriptors criteria and molecular docking were used to build a multi-class neural network as an integrated machine learning algorithm to predict TRPV1 antagonists and agonists. The proposed predictive model had a higher accuracy for classifying TRPV1 agonists than antagonists, the ROC AUC values being 0.980 for predicting agonists, 0.972 for antagonists and 0.952 for inactive molecules. After screening the approved drugs with the validated algorithm, repaglinide (antidiabetic) and agomelatine (antidepressant) emerged as potential TRPV1 antagonists, and protokylol (bronchodilator) as an agonist. Further studies are required to confirm the predicted activity on TRPV1 and to assess the candidates’ efficacy in alleviating pain

Evaluation of Natural Extracts in Animal Models of Pain and Inflammation for a Potential Therapy of Hemorrhoidal Disease

The aim of this work was to assess the analgesic effect of three Vitis vinifera L. leaf extracts and the anti-inflammatory effect of three gels obtained from Aesculus hippocastanum L. seed extracts using animal models, as a preliminary study for the future development of topical preparations based on the combination of extracts with synergistic therapeutic effects on hemorrhoid disease. The analgesic effect was determined by means of the writhing test in mice. The anti-inflammatory effect was determined after administration of carrageenan or kaolin in the rat paw. Extraction using glycerol yielded the highest amounts of flavonoids for both V. vinifera leaves (37.27 ± 1.174 mg/L) and A. hippocastanum seeds (53.48 ± 0.212 mg/L). The highest total phenolic contents were registered for the V. vinifera 20% ethanolic extract (615.3 ± 34.44 mg/L) and for the A. hippocastanum glycerolic extract (247.8 ± 6.991 mg/L). The writhing test revealed that the V. vinifera ethanolic extract induced the most efficient analgesia (57.20%, p < 0.01), better than that induced by the positive control. In the carrageenan inflammation model, only the gel obtained from the A. hippocastanum glycerolic extract significantly reduced paw edema (17.27%, p < 0.05). An anti-inflammatory effect was also observed in the kaolin inflammation model but was not statistically significant (10.12%, p > 0.05). Our findings indicate that V. vinifera and A. hippocastanum extracts may have potential uses for the treatment of pain and inflammation associated with hemorrhoid disease