Virtual screening (VS) has emerged in drug discovery as a powerful computational approach to screen large libraries of small molecules for new hits with desired properties that can then be tested experimentally. Similar to other computational approaches, VS intention is not to replace in vitro or in vivo assays, but to speed up the discovery process, to reduce the number of candidates to be tested experimentally, and to rationalize their choice. Moreover, VS has become very popular in pharmaceutical companies and academic organizations due to its time-, cost-, resources-, and labor-saving. Among the VS approaches, quantitative structure–activity relationship (QSAR) analysis is the most powerful method due to its high and fast throughput and good hit rate. As the first preliminary step of a QSAR model development, relevant chemogenomics data are collected from databases and the literature. Then, chemical descriptors are calculated on different levels of representation of molecular structure, ranging from 1D to nD, and then correlated with the biological property using machine learning techniques. Once developed and validated, QSAR models are applied to predict the biological property of novel compounds. Although the experimental testing of computational hits is not an inherent part of QSAR methodology, it is highly desired and should be performed as an ultimate validation of developed models. In this mini-review, we summarize and critically analyze the recent trends of QSAR-based VS in drug discovery and demonstrate successful applications in identifying perspective compounds with desired properties. Moreover, we provide some recommendations about the best practices for QSAR-based VS along with the future perspectives of this approach.

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Schistosomiasis control in endemic areas depends on several factors, including mass drug delivery programs and interrupting the transmission of disease by controlling the intermediate snail hosts in freshwater ecosystem using...

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With about 400,000 annual deaths worldwide, malaria remains a public health burden in tropical and subtropical areas, especially in low-income countries. Selection of drug-resistant Plasmodium strains has driven the need to explore novel antimalarial compounds with diverse modes of action. In this context, biodiversity has been widely exploited as a resourceful channel of biologically active compounds, as exemplified by antimalarial drugs such as quinine and artemisinin, derived from natural products. Thus, combining a natural product library and quantitative structure–activity relationship (QSAR)-based virtual screening, we have prioritized genuine and derivative natural compounds with potential antimalarial activity prior to in vitro testing. Experimental validation against cultured chloroquine-sensitive and multi-drug-resistant P. falciparum strains confirmed the potent and selective activity of two sesquiterpene lactones (LDT-597 and LDT-598) identified in silico. Quantitative structure–property relationship (QSPR) models predicted absorption, distribution, metabolism, and excretion (ADME) and physiologically based pharmacokinetic (PBPK) parameters for the most promising compound, showing that it presents good physiologically based pharmacokinetic properties both in rats and humans. Altogether, the in vitro parasite growth inhibition results obtained from in silico screened compounds encourage the use of virtual screening campaigns for identification of promising natural compound-based antimalarial molecules.

As part of a drug discovery program aimed at the identification of anti-Trypanosoma cruzi metabolites from Brazilian flora, four acetogenins (1−4) were isolated from the seeds of Porcelia macrocarpa and were identified by NMR spectroscopy and HRESIMS. The new compounds 1 and 2 displayed activity against the trypomastigote (IC 50 = 0.4 and 3.6 μM) and amastigote (IC 50 = 23.0 and 27.7 μM) forms. The structurally related known compound 3 showed less potency to the amastigotes, with an IC 50 value of 58 μM, while the known compound 4 was inactive. To evaluate the potential mechanisms for parasite death, parameters were evaluated by fluorometric assays: (i) plasma membrane permeability, (ii) plasma membrane electric potential (ΔΨ p ), (iii) reactive oxygen species production, and (iv) mitochondrial membrane potential (ΔΨ m ). The results obtained indicated that compounds 1 and 2 depolarize plasma membranes, affecting ΔΨ p and ΔΨ m and contributing to the observed cellular damage and disturbing the bioenergetic system. In silico studies of pharmacokinetics and toxicity (ADMET) properties predicted that all compounds were nonmutagenic, noncarcinogenic, nongenotoxic, and weak hERG blockers. Additionally, none of the isolated acetogenins 1−4 were predicted as pan-assay interference compounds.Porcelia macrocarpa (Warming) R. E. Fries (Annonaceae) is a species found in the Atlantic Forest and "Cerrado" regions of Brazil. 1 Previous studies by our group have shown the anti-Trypanosoma cruzi activity of acetylenic acids from the seeds and flowers from P. macrocarpa. 2,3 T. cruzi protozoan parasites are responsible for Chagas disease, a neglected disease with eight million cases each year in North and South America. 4 The available chemotherapy is unsatisfactory and is limited to two nitrogen-containing heterocyclic drugs, benznidazole and nifurtimox, 5 with severe adverse effects and reduced efficacy. 6−8 In this context, the search for new chemotherapeutic alternatives for Chagas disease is crucial, and natural products are a promising approach to identify new lead compounds. In the present work, the antitrypanosomal activities of four acetogenins (1−4) isolated from the seeds of P. macrocarpa were evaluated, including two new compounds (1 and 2). Furthermore, studies concerning the mechanism of cellular death were performed on compounds 1 and 2, in addition to in silico evaluations of their ADMET properties.

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

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