The use of derivatives of natural and synthetic origin has gained attention because of their therapeutic effects against human diseases. Coumarins are one of the most common organic molecules and are used in medicine for their pharmacological and biological effects, such as anti-inflammatory, anticoagulant, antihypertensive, anticonvulsant, antioxidant, antimicrobial, and neuroprotective, among others. In addition, coumarin derivates can modulate signaling pathways that impact several cell processes. The objective of this review is to provide a narrative overview of the use of coumarin-derived compounds as potential therapeutic agents, as it has been shown that substituents on the basic core of coumarin have therapeutic effects against several human diseases and types of cancer, including breast, lung, colorectal, liver, and kidney cancer. In published studies, molecular docking has represented a powerful tool to evaluate and explain how these compounds selectively bind to proteins involved in various cellular processes, leading to specific interactions with a beneficial impact on human health. We also included studies that evaluated molecular interactions to identify potential biological targets with beneficial effects against human diseases.

Diabetic foot ulcers (DFUs) are very important diabetes-related lesions that can lead to serious physical consequences like amputations of limbs and equally severe social, psychological, and economic outcomes. It is reported that up to 25% of patients with diabetes develop a DFU in their lifetime, and more than half of them become infected. Therefore, it is essential to manage infection and ulcer recovery to prevent negatives outcomes. The available information plays a significant role in keeping both physicians and patients aware of the emerging therapies against DFUs. The purpose of this review is to compile the currently available approaches in the managing and treatment of DFUs, including molecular and regenerative medicine, antimicrobial and energy-based therapies, and the use of plant extracts, antimicrobial peptides, growth factors, ozone, devices, and nano-medicine, to offer an overview of the assessment of this condition.

The antileukemia cancer activity of organic compounds analogous to ellipticine representes a critical endpoint in the understanding of this dramatic disease. A molecular modeling simulation on a dataset of 23 compounds, all of which comply with Lipinski’s rules and have a structure analogous to ellipticine, was performed using the quantitative structure activity relationship (QSAR) technique, followed by a detailed docking study on three different proteins significantly involved in this disease (PDB IDs: SYK, PI3K and BTK). As a result, a model with only four descriptors (HOMO, softness, AC1RABAMBID, and TS1KFABMID) was found to be robust enough for prediction of the antileukemia activity of the compounds studied in this work, with an R² of 0.899 and Q² of 0.730. A favorable interaction between the compounds and their target proteins was found in all cases; in particular, compounds 9 and 22 showed high activity and binding free energy values of around −10 kcal/mol. Theses compounds were evaluated in detail based on their molecular structure, and some modifications are suggested herein to enhance their biological activity. In particular, compounds 22_1, 22_2, 9_1, and 9_2 are indicated as possible new, potent ellipticine derivatives to be synthesized and biologically tested.

Leishmaniasis affects mainly rural areas and the poorest people in the world. A computational study of the antileishmanial activity of organic selenium and tellurium compounds was performed. The 3D structures of the compounds were optimized at the wb97xd/lanl2dz level and used in the quantitative structure-activity relationship (QSAR) analysis. The antileishmanial activity was measured by L. donovani β carbonic anhydrase inhibition (Ki) and the half-maximal inhibitory concentration (IC₅₀) against L. infantum amastigotes. The dataset was divided into training (75%) and test sets (25%) by using a k-means clustering algorithm. For pKi prediction, model M3 with seven 3D topographic descriptors was characterized by the following statistical parameters: r ² = 0.879, Q ² _LOO = 0.822, and Q ² _ext = 0.840. For pIC₅₀ prediction, model M12 with six attributes was characterized by the following statistical parameters: r ² = 0.907, Q ² _LOO = 0.824, and Q ² _ext = 0.795. Both models met all the requirements of Tropsha´s test, which implies predictions of pIC₅₀ and pKi activities with high accuracy. Concomitantly, favourable interactions of the sulphonamide group with the Zn atom in the protein were revealed by the docking analysis.

This review is important to the field of preeclampsia (PE), because it provides a description of the principal in vitro, in vivo, and in silico models developed for the study of its principal aspects, and to test emerging therapies or biomarkers predicting the syndrome before their evaluation in clinical trials. Despite the current advance, the field still lacking of new methods and original modeling approaches that leads to new knowledge about pathophysiology. The part of in silico models described in this review has not been considered in the previous reports.