Toxicity Assessment of Structurally Relevant Natural Products from Mexican Plants with Antinociceptive Activity

Abstract

UNIIQUIM database contains molecules from Mexican plants, one of the richest sources of bioactive molecules in the world. Here, we describe the chemical and toxicological profile of molecules with analgesic activity from UNIIQUIM. Most of the compounds are likely to interact with opioid receptors. The predicted acute toxicity is low and none is predicted mutagenic. Given the structural diversity, and biological and toxicity profiles, these molecules represent a new avenue in the search of molecules with antinociceptive activity.

In vivo Antidiabetic Activities of Aqueous Extract of Anchomanes difformis (Blume) Eng, Rhizophora racemosa G. Mey and Ravenala madagascariensis Sonn

“…The observed data suggested that the oral LD50 values of A. difformis, R. racemosa and R. madagascariensis are greater than 2000 mg/kg in Swiss albino mice. Therefore, according to the OECD Globally Harmonized Classification System [24] extracts from A. difformis, R. racemosa and R. madagascariensis are categorized as category 5 (2000 mg/kg < LD50 < 5000 mg/kg) and considered non-toxic orally. The low toxicity of these plants has been confirmed by other authors in various studies [25,26].…”

Progress and Impact of Latin American Natural Product Databases

“…Moreover, the predicted acute toxicity is low, and none is predicted to be mutagenic. The study concludes that because of the structural diversity, the common nociception activity and the predicted safety profile as non-mutagenic agents highlights the importance of the molecules for further studies on the search of analgesic and nociception effects [149].…”

Predictive Global Models of Cruzain Inhibitors with Large Chemical Coverage

“…12 , 13 These mutually complementary approaches are often called “descriptive QSAR” and “predictive QSAR.” 13 The advances in QSAR modeling led to its acceptance as a prediction tool of toxicity endpoints for the risk assessment of new chemical entities 14 or as a preliminary step in drug development to identify compounds with potential toxic or mutagenic profiles. 15 The Organization for Economic Cooperation and Development (OECD) established guidelines for the use of QSAR in regulatory settings, and these principles became gold standards in the general QSAR practice. 14 The OECD principles for the validation of QSAR models for regulatory purposes are (1) a defined endpoint, (2) an unambiguous algorithm, (3) a defined domain of applicability, (4) appropriate measures of goodness of fit, robustness, and predictability, and (5) a mechanistic interpretation, if possible.…”

“…Quantitative structure–activity relationship (QSAR) models mathematically correlate structural properties of molecules with their biological activity. There are two distinctive goals in the practice of QSAR modeling: the use of mathematical tools to describe the trends in the data, providing interpretations that could be useful in the understanding of an inherent mechanism, and the use of these methods to achieve predictions with high accuracy, irrespective of the interpretability of the generated models. , These mutually complementary approaches are often called “descriptive QSAR” and “predictive QSAR.” The advances in QSAR modeling led to its acceptance as a prediction tool of toxicity endpoints for the risk assessment of new chemical entities or as a preliminary step in drug development to identify compounds with potential toxic or mutagenic profiles . The Organization for Economic Cooperation and Development (OECD) established guidelines for the use of QSAR in regulatory settings, and these principles became gold standards in the general QSAR practice .…”