Assessment of Nonnucleoside Inhibitors Binding to HIV-1 Reverse Transcriptase Using HYDE Scoring

Evaluation of the antidermatophytic activity of potassium salts of N-acylhydrazinecarbodithioates and their aminotriazole-thione derivatives

Nowadays, dermatophyte infections are relatively easy to cure, especially since the introduction of orally administered antifungals such as terbinafine and itraconazole. However, these drugs may cause side effects due to liver damage or their interactions with other therapeutics. Hence, the search for new effective chemotherapeutics showing antidermatophyte activity seems to be the urge of the moment. Potassium salts of N-acylhydrazinecarbodithioates are used commonly as precursors for the synthesis of biologically active compounds. Keeping that in mind, the activity of a series of five potassium N-acylhydrazinecarbodithioates (1a-e) and their aminotriazole-thione derivatives (2a-e) was evaluated against a set of pathogenic, keratinolytic fungi, such as Trichophyton ssp., Microsporum ssp. and Chrysosporium keratinophilum, but also against some Gram-positive and Gram-negative bacteria. All tested compounds were found non-toxic for L-929 and HeLa cells, with the IC30 and IC50 values assessed in the MTT assay above 128 mg/L. The compound 5-amino-3-(naphtalene-1-yl)-4,5-dihydro-1H-1,2,4-triazole-5-thione (2d) was found active against all fungal strains tested. Scanning Electron Microscopy (SEM) revealed inhibition of mycelium development of Trichophyton rubrum cultivated on nail fragments and treated with 2d 24 h after infection with fungal spores. Transmission Electron Microscopy (TEM) observation of mycelium treated with 2d showed ultrastructural changes in the morphology of germinated spores. Finally, the RNA-seq analysis indicated that a broad spectrum of genes responded to stress induced by the 2d compound. In conclusion, the results confirm the potential of N-acylhydrazinecarbodithioate derivatives for future use as promising leads for new antidermatophyte agents development.

Effect of Linker Elongation on the VGSC Affinity and Anticonvulsant Activity among 4-Alkyl-5-aryl-1,2,4-triazole-3-thione Derivatives

The main aim of the current project was to investigate the effect of the linker size in 4-alkyl-5-aryl-1,2,4-triazole-3-thione derivatives, known as a group of antiepileptic drug candidates, on their affinity towards voltage-gated sodium channels (VGSCs). The rationale of the study was based both on the SAR observations and docking simulations of the interactions between the designed ligands and the binding site of human VGSC. HYDE docking scores, which describe hydrogen bonding, desolvation, and hydrophobic effects, obtained for 5-[(3-chlorophenyl)ethyl]-4-butyl/hexyl-1,2,4-triazole-3-thiones, justified their beneficial sodium channel blocking activity. The results of docking simulations were verified using a radioligand binding assay with [³H]batrachotoxin. Unexpectedly, although the investigated triazole-based compounds acted as VGSC ligands, their affinities were lower than those of the respective analogs containing shorter alkyl linkers. Since numerous sodium channel blockers are recognized as antiepileptic agents, the obtained 1,2,4-triazole derivatives were examined for antiepileptic potential using an experimental model of tonic-clonic seizures in mice. Median effective doses (ED₅₀) of the compounds examined in MES test reached 96.6 ± 14.8 mg/kg, while their median toxic doses (TD₅₀), obtained in the rotarod test, were even as high as 710.5 ± 47.4 mg/kg.

Machine Learning augmented docking studies of aminothioureas at the SARS-CoV-2-ACE2 interface

The current pandemic outbreak clearly indicated the urgent need for tools allowing fast predictions of bioactivity of a large number of compounds, either available or at least synthesizable. In the computational chemistry toolbox, several such tools are available, with the main ones being docking and structure-activity relationship modeling either by classical linear QSAR or Machine Learning techniques. In this contribution, we focus on the comparison of the results obtained using different docking protocols on the example of the search for bioactivity of compounds containing N-N-C(S)-N scaffold at the S-protein of SARS-CoV-2 virus with ACE2 human receptor interface. Based on over 1800 structures in the training set we have predicted binding properties of the complete set of nearly 600000 structures from the same class using the Machine Learning Random Forest Regressor approach.

Docking and QSAR of Aminothioureas at the SARS-CoV-2 S-Protein-Human ACE2 Receptor Interface

Docking of over 160 aminothiourea derivatives at the SARS-CoV-2 S-protein–human ACE2 receptor interface, whose structure became available recently, has been evaluated for its complex stabilizing potency and subsequently subjected to quantitative structure–activity relationship (QSAR) analysis. The structural variety of the studied compounds, that include 3 different forms of the N–N–C(S)–N skeleton and combinations of 13 different substituents alongside the extensive length of the interface, resulted in the failure of the QSAR analysis, since different molecules were binding to different parts of the interface. Subsequently, absorption, distribution, metabolism, and excretion (ADME) analysis on all studied compounds, followed by a toxicity analysis using statistical models for selected compounds, was carried out to evaluate their potential use as lead compounds for drug design. Combined, these studies highlighted two molecules among the studied compounds, i.e., 5-(pyrrol-2-yl)-2-(2-methoxyphenylamino)-1,3,4-thiadiazole and 1-(cyclopentanoyl)-4-(3-iodophenyl)-thiosemicarbazide, as the best candidates for the development of future drugs.