Protozoal infections are still a global health problem, threatening the lives of millions of people around the world, mainly in impoverished tropical and sub‐tropical regions. Thus, in view of the lack of efficient therapies and increasing resistances against existing drugs, this study describes the antiprotozoal potential of synthetic cinnamate ester analogues and their structure‐activity relationships. In general, Leishmania donovani and Trypanosoma brucei were quite susceptible to the compounds in a structure‐dependent manner. Detailed analysis revealed a key role of the substitution pattern on the aromatic ring and a marked effect of the side chain on the activity against these two parasites. The high antileishmanial potency and remarkable selectivity of the nitro‐aromatic derivatives suggested them as promising candidates for further studies. On the other hand, the high in vitro potency of catechol‐type compounds against T. brucei could not be extrapolated to an in vivo mouse model.

A great number of sesquiterpenes are reported in the available literature as good antileishmanial leads. However, their mode of action at the molecular level has not been elucidated. The lack of molecular studies could be considered an impediment for studies seeking to improve sesquiterpene-based drug design. The present in silico study allows us to make important observations about the molecular details of the binding modes of a set of antileishmanial sesquiterpenes against four drug-enzyme targets [pteridine reductase-1 (PTR1), N-myristoyl transferase (NMT), cysteine synthase (CS), trypanothione synthetase (TryS)]. Through molecular docking it was found that two sesquiterpene coumarins are promising leads for the PTR1 and TryS inhibition purposes, and some xanthanolides also exhibited better affinity towards PTR1 and CS binding. In addition, the affinity values were clustered by Principal Component Analysis and drug-like properties were analyzed for the strongest-docking sesquiterpenes. The results are an excellent starting point for future studies of structural optimization of this kind of compounds.

Ifenprodil (1) is a potent GluN2B-selective N-methyl-D-aspartate (NMDA) receptor antagonist that is used as a cerebral vasodilator and has been examined in clinical trials for the treatment of drug addiction, idiopathic pulmonary fibrosis, and COVID-19. To correlate biological data with configuration, all four ifenprodil stereoisomers were prepared by diastereoselective reduction and subsequent separation of enantiomers by chiral HPLC. The absolute configuration of ifenprodil stereoisomers was determined by X-ray crystal structure analysis of (1R,2S)-1a and (1S,2S)-1d. GluN2B affinity, ion channel inhibitory activity, and selectivity over α, σ, and 5-HT receptors were evaluated. (1R,2R)-Ifenprodil ((1R,2R)-1c) showed the highest affinity toward GluN2B-NMDA receptors (K i = 5.8 nM) and high inhibition of ion flux in two-electrode voltage clamp experiments (IC 50 = 223 nM). Whereas the configuration did not influence considerably the GluN2B-NMDA receptor binding, (1R)-configuration is crucial for elevated inhibitory activity. (1R,2R)-Configured ifenprodil (1R,2R)-1c exhibited high selectivity for GluN2B-NMDA receptors over adrenergic, serotonergic, and σ 1 receptors.

Parasitic infections like leishmaniasis and trypanosomiasis remain as a worldwide concern to public health. Improvement of the currently available drug discovery pipelines for those diseases is therefore mandatory. We have recently reported on the antileishmanial and antitrypanosomal activity of a set of cinnamate esters where we identified several compounds with interesting activity against L. donovani and T. brucei rhodesiense. For a better understanding of such compounds’ anti-infective activity, analyses of the underlying structure-activity relationships, especially from a quantitative point of view, would be a prerequisite for rational further development of such compounds. Thus, quantitative structure-activity relationships (QSAR) modeling for the mentioned set of compounds and their antileishmanial and antitrypanosomal activity was performed using a genetic algorithm as main variable selection tool and multiple linear regression as statistical analysis. Changes in the composition of the training/test sets were evaluated (two randomly selected and one by Kennard-Stone algorithm). The effect of the size of the models (number of descriptors) was also investigated. The quality of all resulting models was assessed by a variety of validation parameters. The models were ranked by newly introduced scoring functions accounting for the fulfillment of each of the validation criteria evaluated. The test sets were effectively within the applicability domain of the best models, which demonstrated high robustness. Detailed analysis of the molecular descriptors involved in those models revealed strong dependence of activity on the number and type of polar atoms, which affect the hydrophobic/hydrophilic properties causing a prominent influence on the investigated biological activities.

Fungal infections currently remain as a common problem in public health. Actually, drug discovery programs are oriented to the searching for lead structures. Virtual screening and molecular docking constitute great alternatives in order to find hit compounds. Novel infection targets can also be defined and employed together with molecular docking tools in drug discovery programs. Thus, thirty-two natural compounds were docked within the active site of N-myristoyl transferase (NMT) as antifungal enzyme target. From tested compounds, alkaloids, flavonoids, xanthones, and quinones exhibited strongest mean interaction with NMT than terpenoids, coumarins and phenolics. Particularly, affinities for one aporphine alkaloid, a prenylated flavonoid and two xanthones resulted to be comparable with that of previously reported synthetic inhibitor. Several hydrophobic and polar contacts were demonstrated by comparing different computational tools. The present results let to establish three possible lead structures to develop antifungal drugs although subsequent SAR analyses are still required.

Nitrobenzothiazinones (BTZs) are a very potent class of antibiotics against Mycobacterium tuberculosis. However, relationships between their structural properties and whole cell activity remain poorly predictable. Herein, we present the synthesis and antimycobacterial evaluation of a diverse set of BTZs. High potency was predominantly achieved by piperidine and piperazine substitutions, whereupon three compounds were identified as promising candidates, showing preferable metabolic stability. Lack of correlation between potency and calculated binding energies suggested that target inhibition is not the only requirement to obtain suitable antimycobacterial agents. In contrast, prediction of whole cell activity class was successfully accomplished by extensively validated machine learning models. The performance of the superior model was further verified by >70% correct class predictions for a large set of reported BTZs. Our generated model is thus a key prerequisite to streamline lead optimization endeavors, particularly regarding the improvement of overall hit rates in whole cell antimycobacterial assays.

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The essential oil was obtained by steam distillation from fruits of Iryanthera ulei Warb. growing in Colombia. The oil was analyzed by GC/FID and GC/ MS. The main components were α-muurolol (13.2%), spathulenol (12.1%), α-cadinol (7.8%), guaiol (4.0%), oplopanone (3.7%), 1,10-diepi-cubenol (3.4%) and limonene (3.3%) constituting a sesquiterpene-type enriched mixture. In addition, oil was tested for its antimicrobial activity against some Gram-positive and Gramnegative bacteria by means of a modified agar-well diffusion method. S. aureus strain was found to be the most sensitive microorganism.