QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

ElectroPredictor: An Application to Predict Mayr's Electrophilicity E through Implementation of an Ensemble Model Based on Machine Learning Algorithms

Electrophilicity (E) is one of the most important parameters to understand the reactivity of an organic molecule. Although the theoretical electrophilicity index (ω) has been associated with E in a small homologous series, the use of w to predict E in a structurally heterogeneous set of compounds is not a trivial task. In this study, a robust ensemble model is created using Mayr's database of reactivity parameters. A combination of topological and quantum mechanical descriptors and different machine learning algorithms are employed for the model's development. The predictability of the model is assessed using different statistical parameters, and its validation is examined, including a training/test partition, an applicability domain, and a y-scrambling test. The global ensemble model presents a Q5-fold2 of 0.909 and a Qext2 of 0.912, demonstrating an excellent predictability performance of E values and showing that w is not a good descriptor for the prediction of E, especially for the case of neutral compounds. ElectroPredictor, a noncommercial Python application (https://github.com/mmoreno1/ElectroPredictor), is developed to predict E. QM9, a well-known large dataset containing 133885 neutral molecules, is used to perform a virtual screening (94.0% coverage). Finally, the 10 most electrophilic molecules are analyzed as possible new Mayr's electrophiles, which have not yet been experimentally tested. This study confirms the necessity to build an ensemble model using nonlinear machine learning algorithms, topographic descriptors, and separating molecules into charged and neutral compounds to predict E with precision.

Small molecules containing chalcogen elements (S, Se, Te) as new warhead to fight neglected tropical diseases

Neglected tropical diseases (NTDs) encompass a group of infectious diseases with a protozoan etiology, high incidence, and prevalence in developing countries. As a result, economic factors constitute one of the main obstacles to their management. Endemic countries have high levels of poverty, deprivation and marginalization which affect patients and limit their access to proper medical care. As a matter of fact, statistics remain uncollected in some affected areas due to non-reporting cases. World Health Organization and other organizations proposed a plan for the eradication and control of the vector, although many of these plans were halted by the COVID-19 pandemic. Despite of the available drugs to treat these pathologies, it exists a lack of effectiveness against several parasite strains. Treatment protocols for diseases such as American trypanosomiasis (Chagas disease), leishmaniasis, and human African trypanosomiasis (HAT) have not achieved the desired results. Unfortunately, these drugs present limitations such as side effects, toxicity, teratogenicity, renal, and hepatic impairment, as well as high costs that have hindered the control and eradication of these diseases. This review focuses on the analysis of a collection of scientific shreds of evidence with the aim of identifying novel chalcogen-derived molecules with biological activity against Chagas disease, leishmaniasis and HAT. Compounds illustrated in each figure share the distinction of containing at least one chalcogen element. Sulfur (S), selenium (Se), and tellurium (Te) have been grouped and analyzed in accordance with their design strategy, chemical synthesis process and biological activity. After an exhaustive revision of the related literature on S, Se, and Te compounds, 183 compounds presenting excellent biological performance were gathered against the different causative agents of CD, leishmaniasis and HAT.

QSAR Studies, Molecular Docking, Molecular Dynamics, Synthesis, and Biological Evaluation of Novel Quinolinone-Based Thiosemicarbazones against Mycobacterium tuberculosis

In this study, a series of novel quinolinone-based thiosemicarbazones were designed in silico and their activities tested in vitro against Mycobacterium tuberculosis (M. tuberculosis). Quantitative structure-activity relationship (QSAR) studies were performed using quinolinone and thiosemicarbazide as pharmacophoric nuclei; the best model showed statistical parameters of R² = 0.83; F = 47.96; s = 0.31, and was validated by several different methods. The van der Waals volume, electron density, and electronegativity model results suggested a pivotal role in antituberculosis (anti-TB) activity. Subsequently, from this model a new series of quinolinone-thiosemicarbazone 11a-e was designed and docked against two tuberculosis protein targets: enoyl-acyl carrier protein reductase (InhA) and decaprenylphosphoryl-β-D-ribose-2'-oxidase (DprE1). Molecular dynamics simulation over 200 ns showed a binding energy of -71.3 to -12.7 Kcal/mol, suggesting likely inhibition. In vitro antimycobacterial activity of quinolinone-thiosemicarbazone for 11a-e was evaluated against M. bovis, M. tuberculosis H37Rv, and six different strains of drug-resistant M. tuberculosis. All compounds exhibited good to excellent activity against all the families of M. tuberculosis. Several of the here synthesized compounds were more effective than the standard drugs (isoniazid, oxafloxacin), 11d and 11e being the most active products. The results suggest that these compounds may contribute as lead compounds in the research of new potential antimycobacterial agents.

In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study

Free fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic β-cells. An advantage of therapies that target FFA1 is their reduced risk of hypoglycemia relative to common type 2 diabetes treatments. In this work, quantitative structure–activity relationship (QSAR) approach was used to construct models to identify possible FFA1 agonists by applying four different machine-learning algorithms. The best model (M2) meets the Tropsha’s test requirements and has the statistics parameters R² = 0.843, Q²_CV = 0.785, and Q²_ext = 0.855. Also, coverage of 100% of the test set based on the applicability domain analysis was obtained. Furthermore, a deep analysis based on the ADME predictions, molecular docking, and molecular dynamics simulations was performed. The lipophilicity and the residue interactions were used as relevant criteria for selecting a candidate from the screening of the DiaNat and DrugBank databases. Finally, the FDA-approved drugs bilastine, bromfenac, and fenofibric acid are suggested as potential and lead FFA1 agonists.

Synthesis and antimicrobial activity of functional derivatives of thiazolo[2,3-c][1,2,4]triazoles

Background:

Condensed triazoles are a well-known class of heterocyclic compounds due to a wide range of biological activity. The study is dedicated to the evaluation of the antimicrobial potential of new functional derivatives of thiazolo[2,3-c][1,2,4]triazoles.

Methods:

Effective, easy-to-implement and low-cost routes to the production of title compounds via electrophilic intramolecular heterocyclization are reported. Bactericidal and fungicidal activities against Gram-positive and Gram-negative bacteria, and fungus were studied. The influence of functional groups on the biological activity of tested thiazolo[2,3-c][1,2,4]triazoles is discussed.

Results:

Microbiological evaluation shows that 6-[(trichlorotellanyl)methyl]-[1,3]thiazolo[2,3-c][1,2,4]triazol-3-amine hydrogen chloride 2a and 3-(2-hydroxyphenyl)-6-[(trichloro-λ4-tellanyl)methyl]-5,6-dihydro-[1,3]thiazolo[2,3-c][1,2,4]triazole 2g have a high bactericidal activity and Cu (I) salts of 3-(2-hydroxyphenyl)-6-iodomethyl/6-methylidene-5,6-dihydro-[1,3]thiazolo-[2,3-c][1,2,4]triazoles 5a,c have a high fungicidal activity.

Conclusion:

it must be concluded that these products or their derivatives may be of practical benefit as bactericidal and fungicidal agents.

Selenium and protozoan parasitic infections: selenocompounds and selenoproteins potential

The current drug treatments against protozoan parasitic diseases including Chagas, malaria, leishmaniasis, and toxoplasmosis represent good examples of drug resistance mechanisms and have shown diverse side effects. Therefore, the identification of novel therapeutic strategies and drug compounds against such life-threatening diseases is urgent. According to the successful usage of selenium (Se) compounds-based therapy against some diseases, this therapeutic strategy has been recently further underlined against these parasitic diseases by targeting different parasite´s essential pathways. On the other hand, due to the important functions played by parasite selenoproteins in their biology (such as modulating the host immune response), they can be also considered as a novel therapeutic strategy by designing specific inhibitors against these important proteins. In addition, the immunomodulatory potentiality of these compounds to trigger T helper type 1 (Th1) cells and cytokine-mediated immune response for the substantial induction of proinflammatory cytokines, thus, Se, selenoproteins, and parasite selenoproteins could be further investigated to find possible vaccine antigens. Herein, we collect and present the results of some studies regarding Se-based therapy against protozoan parasitic diseases and highlight relevant information and some viewpoints that might be insightful to advance toward more effective studies in the future.

Theoretically exploring selective-binding mechanisms of BRD4 through integrative computational approaches

The origin of cancer is related to the dysregulation of multiple signal pathways and of physiological processes. Bromodomain-containing protein 4 (BRD4) has become an attractive target for the development of anticancer and anti-inflammatory agents since it can epigenetically regulate the transcription of growth-promoting genes. The synthesized BRD4 inhibitors with new chemical structures can reduce the drug resistance, but their binding modes and the inhibitory mechanism remain unclear. Here, we initially constructed robust QSAR models based on 68 reported tetrahydropteridin analogues using topomer CoMFA and HQSAR. On the basis of QSAR results, we designed 16 novel tetrahydropteridin analogues with modified structures and carried out docking studies. Instead of significant hydrogen bondings with amino acid residue Asn140 as reported in previous research, the molecular docking modelling suggested a novel docking pose that involves the amino acid residues (Trp81, Pro82, Val87, Leu92, Leu94, Cys136, Asp144, and Ile146) at the active site of BRD4. The MD simulations, free energy calculations, and residual energy contributions all indicate that hydrophobic interactions are decisive factors affecting bindings between inhibitors and BRD4. The current study provides new insights that can aid the discovery of BRD4 inhibitors with enhanced anti-cancer ability.