Repurposing antiparasitic N,N'-aliphatic diamine derivatives as promising antimycobacterial agents.

In previous studies, we demonstrated the potent activity of a library of 25 N,N'-disubstituted diamines (NNDDA) toward Trypanosomatid and Apicomplexa parasites. Considering the structure similarity between this collection and SQ109, an antituberculosis compound, and its compelling antiparasitic properties, we aimed to repurpose this library for tuberculosis treatment. We assayed this collection against Mycobacterium tuberculosis H37Rv and M. avium, obtaining several compounds with MIC values below 10 µM. The most active analogs were also evaluated against M. smegmatis, a non-pathogenic species, and the non-tuberculosis mycobacteria M. abscessus, M. kansasii, and M. fortuitum. 3c stands out as the lead mycobacterial compound of the collection, with potent activity against M. tuberculosis (minimal inhibitory concentration [MIC] = 3.4 µM) and moderate activity against M. smegmatis, M. kansasii, and M. fortuitum (all with MIC values of 26.8 µM). To unravel the mechanism of action, we employed the web-based platform Polypharmacology Browser 2 (PPB2), obtaining carbonic anhydrases as potential drug targets. Nevertheless, none of the compounds displayed experimental inhibition. In summary, our study confirms the validity of the repurposing approach and underscores the antimycobacterial potential of NNDDA compounds, especially the analog 3c, setting a stepping stone for further studies.

1,2,3-Triazoles in Biomolecular Crystallography: A Geometrical Data-Mining Approach.

The 1,2,3-triazole scaffold has become very attractive to identify new chemical entities in drug discovery projects. Despite the widespread use of click chemistry to synthesize numerous 123Ts, there are few drugs on the market that incorporate this scaffold as a substructure. To investigate the true potential of 123Ts in protein-ligand interactions, we examined the noncovalent interactions between the 1,2,3-triazole ring and amino acids in protein-ligand cocrystals using a geometrical approach. For this purpose, we constructed a nonredundant database of 220 PDB IDs from available 123T-protein cocrystal structures. Subsequently, using the Protein Ligand Interaction Profiler web platform (PLIP), we determined whether 1,2,3-triazoles primarily act as linkers or if they can be considered interactive scaffolds. We then manually analyzed the geometrical descriptors from 333 interactions between 1,4-disubstituted 123T rings and amino acid residues in proteins. This study demonstrates that 1,2,3-triazoles exhibit diverse preferred interactions with amino acids, which contribute to protein-ligand binding.

Expanding the scope of novel 1,2,3-triazole derivatives as new antiparasitic drug candidates.

We have previously shown that prenyl and aliphatic triazoles are interesting motifs to prepare new chemical entities for antiparasitic and antituberculosis drug development. In this opportunity a new series of prenyl-1,2,3-triazoles were prepared from isoprenyl azides and different alkynes looking for new antimalarial drug candidates. The compounds were prepared by copper(i) catalyzed dipolar cycloaddition of the isoprenyl azide equilibrium mixture providing exclusively 1,4-disubstituted 1,2,3-triazoles in a regiospecific fashion. The complete collection of 64 compounds was tested on chloroquine-sensitive (CQ sensitive), Sierra Leone (D6), and the chloroquine-resistant, Indochina (W2), strains of Plasmodium falciparum and those compounds which were not previously reported were also tested against Leishmania donovani, the causative agent for visceral leishmaniasis. Thirteen analogs displayed antimalarial activity with IC50 below 10 µM, while the antileishmanial activity of the newly reported analogs could not improve upon those previously reported. Compounds 1o and 1r were identified as the most promising antimalarial drug leads with IC50 below 3.0 µM for both CQ-sensitive and resistant P. falciparum strains with high selectivity index. Finally, a chemoinformatic in silico analysis was performed to evaluate physicochemical parameters, cytotoxicity risk and drug score. The validation of a bifunctional farnesyl/geranylgeranyl diphosphate synthase PfFPPS/GGPPS as the potential target of the antimalarial activity of selected analogs should be further investigated.

Systematic study of 1,2,3-triazolyl sterols for the development of new drugs against parasitic Neglected Tropical Diseases.

A series of thirty 1,2,3-triazolylsterols, inspired by azasterols with proven antiparasitic activity, were prepared by a stereocontrolled synthesis. Ten of these compounds constitute chimeras/hybrids of 22,26-azasterol (AZA) and 1,2,3-triazolyl azasterols. The entire library was assayed against the kinetoplastid parasites Leishmania donovani, Trypanosoma cruzi, and Trypanosoma brucei, the causatives agents for visceral leishmaniasis, Chagas disease, and sleeping sickness, respectively. Most of the compounds were active at submicromolar/nanomolar concentrations with high selectivity index, when compared to their cytotoxicity against mammalian cells. Analysis of in silico physicochemical properties were conducted to rationalize the activities against the neglected tropical disease pathogens. The analogs with selective activity against L. donovani (E4, IC50 0.78 µM), T brucei (E1, IC50 0.12 µM) and T. cruzi (B1- IC50 0.33 µM), and the analogs with broad-spectrum antiparasitic activities against the three kinetoplastid parasites (B1 and B3), may be promising leads for further development as selective or broad-spectrum antiparasitic drugs.

Garbage in, garbage out: how reliable training data improved a virtual screening approach against SARS-CoV-2 MPro.

Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have the power to integrate, process and analyze multiple data in a short time. However, these initiatives may yield unrealistic results if the applied models are not inferred from reliable data and the resulting predictions are not confirmed by experimental evidence. Methods: We undertook a drug discovery campaign against the essential major protease (MPro) from SARS-CoV-2, which relied on an in silico search strategy -performed in a large and diverse chemolibrary- complemented by experimental validation. The computational method comprises a recently reported ligand-based approach developed upon refinement/learning cycles, and structure-based approximations. Search models were applied to both retrospective (in silico) and prospective (experimentally confirmed) screening. Results: The first generation of ligand-based models were fed by data, which to a great extent, had not been published in peer-reviewed articles. The first screening campaign performed with 188 compounds (46 in silico hits and 100 analogues, and 40 unrelated compounds: flavonols and pyrazoles) yielded three hits against MPro (IC50 ≤ 25 µM): two analogues of in silico hits (one glycoside and one benzo-thiazol) and one flavonol. A second generation of ligand-based models was developed based on this negative information and newly published peer-reviewed data for MPro inhibitors. This led to 43 new hit candidates belonging to different chemical families. From 45 compounds (28 in silico hits and 17 related analogues) tested in the second screening campaign, eight inhibited MPro with IC50 = 0.12-20 µM and five of them also impaired the proliferation of SARS-CoV-2 in Vero cells (EC50 7-45 µM). Discussion: Our study provides an example of a virtuous loop between computational and experimental approaches applied to target-focused drug discovery against a major and global pathogen, reaffirming the well-known "garbage in, garbage out" machine learning principle.