The giardicidal activity of lobendazole, fabomotizole, tenatoprazole and ipriflavone: A ligand-based virtual screening and in vitro study

Similarity searching for anticandidal agents employing a repurposing approach

Fungal infections caused by Candida are still a public health concern. Particularly, the resistance to traditional chemotherapeutic agents is a major issue that requires efforts to develop new therapies. One of the most interesting approaches to finding new active compounds is drug repurposing aided by computational methods. In this work, two databases containing anticandidal agents and drugs were studied employing cheminformatics and compared by similarity methods. The results showed 36 drugs with high similarities to some candicidals. From these drugs, trimetozin, osalmid and metochalcone were evaluated against C. albicans (18804), C. glabrata (90030), and miconazole-resistant strain C. glabrata (32554). Osalmid and metochalcone were the best, with activity in the micromolar range. These findings represent an opportunity to continue with the research on the potential antifungal application of osalmid and metochalcone as well as the design of structurally related derivatives.

Discovery of novel TLR4/MD-2 inhibitors: Receptor structure-based virtual screening studies and anti-inflammatory evaluation

In this study, a receptor structure-based virtual screening strategy was constructed using a computer-aided drug design. First, the compounds were filtered based on the Lipinski pentad and adsorption, distribution, metabolism, excretion, and toxicity profiles. Then, receptor structure-based pharmacophore models were constructed and screened. Finally, the in vitro toxicity and anti-inflammatory activities of hit compounds were initially evaluated to investigate their in vitro anti-inflammatory effects and mechanisms of action. The results revealed that hit 94 had the best anti-inflammatory activity and low toxicity while inhibiting the activation of Toll-like receptor (TLR) 4/myeloid differentiation factor 2 (MD2)-associated signaling pathways of nuclear factor-κB and mitogen-activated protein kinase. In vivo adjuvant arthritis results also revealed that hit 94 ameliorated foot swelling to a greater extent in rats compared with the positive control drug indomethacin. These results suggest that hit 94 can be used as a potential TLR/MD2 inhibitor for inflammatory diseases.

Comparison of logP and logD correction models trained with public and proprietary data sets

In drug discovery, partition and distribution coefficients, logP and logD for octanol/water, are widely used as metrics of the lipophilicity of molecules, which in turn have a strong influence on the bioactivity and bioavailability of potential drugs. There are a variety of established methods, mostly fragment or atom-based, to calculate logP while logD prediction generally relies on calculated logP and pKa for the estimation of neutral and ionized populations at a given pH. Algorithms such as ClogP have limitations generally leading to systematic errors for chemically related molecules while pKa estimation is generally more difficult due to the interplay of electronic, inductive and conjugation effects for ionizable moieties. We propose an integrated machine learning QSAR modeling approach to predict logD by training the model with experimental data while using ClogP and pKa predicted by commercial software as model descriptors. By optimizing the loss function for the ClogD calculated by the software, we build a correction model that incorporates both descriptors from the software and available experimental logD data. Additionally, we calculate logP from the logD model using the software predicted pKa's. Here, we have trained models using publicly or commercial available logD data to show that this approach can improve on commercial software predictions of lipophilicity. When applied to other logD data sets, this approach extends the domain of applicability of logD and logP predictions over commercial software. Performance of these models favorably compare with models built with a larger set of proprietary logD data.

Computer-Assisted Discovery of Alkaloids with Schistosomicidal Activity

Schistosomiasis is a chronic parasitic disease caused by trematodes of the genus Schistosoma; it is commonly caused by Schistosoma mansoni, which is transmitted by Bioamphalaria snails. Studies show that more than 200 million people are infected and that more than 90% of them live in Africa. Treatment with praziquantel has the best cost–benefit result on the market. However, hypersensitivity, allergy, and drug resistance are frequently presented after administration. From this perspective, ligand-based and structure-based virtual screening (VS) techniques were combined to select potentially active alkaloids against S. mansoni from an internal dataset (SistematX). A set of molecules with known activity against S. mansoni was selected from the ChEMBL database to create two different models with accuracy greater than 84%, enabling ligand-based VS of the alkaloid bank. Subsequently, structure-based VS was performed through molecular docking using four targets of the parasite. Finally, five consensus hits (i.e., five alkaloids with schistosomicidal potential), were selected. In addition, in silico evaluations of the metabolism, toxicity, and drug-like profile of these five selected alkaloids were carried out. Two of them, namely, 11,12-methylethylenedioxypropoxy and methyl-3-oxo-12-methoxy-n(1)-decarbomethoxy-14,15-didehydrochanofruticosinate, had plausible toxicity, metabolomics, and toxicity profiles. These two alkaloids could serve as starting points for the development of new schistosomicidal compounds based on natural products.

Antimicrobial resistance of the enteric protozoon Giardia duodenalis - A narrative review

Introduction

As therapy-refractory giardiasis is an emerging health issue, this review aimed at summarizing mechanisms of reduced antimicrobial susceptibility in Giardia duodenalis and strategies to overcome this problem.

Methods

A narrative review on antimicrobial resistance in G. duodenalis was based upon a selective literature research.

Results

Failed therapeutic success has been observed for all standard therapies of giardiasis comprising nitroimidazoles like metronidazole or tinidazole as first line substances but also benznidazoles like albendazole and mebendazole, the nitrofuran furazolidone, the thiazolide nitazoxanide, and the aminoglycoside paromomycin. Multicausality of the resistance phenotypes has been described, with differentiated gene expression due to epigenetic and post-translational modifications playing a considerable bigger role than mutational base exchanges in the parasite DNA. Standardized resistance testing algorithms are not available and clinical evidence for salvage therapies is scarce in spite of research efforts targeting new giardicidal drugs.

Conclusion

In case of therapeutic failure of first line nitroimidazoles, salvage strategies including various options for combination therapy exist in spite of limited evidence and lacking routine diagnostic-compatible assays for antimicrobial susceptibility testing in G. duodenalis. Sufficiently powered clinical and diagnostic studies are needed to overcome both the lacking evidence regarding salvage therapy and the diagnostic neglect of antimicrobial resistance.