Application of target repositioning and in silico screening to exploit fatty acid binding proteins (FABPs) from Echinococcus multilocularis as possible drug targets

Molecular characteristics of Echinococcus multilocularis FABP1 and its regulatory functions on murine macrophages

Fatty acid binding proteins (FABPs) have emerged as attractive vaccination candidates for several platyhelminth species. To explore the physiological functions of Echinococcus multilocularis (E. multilocularis) FABP, the molecular characteristics of EmFABP1 were analyzed by online software, and the regulatory roles of rEmFABP1 protein in murine macrophages were further investigated. The emfabp1 gene encodes 133 amino acids with the characteristic β-barrel shape of the cytoplasmic FABP family. Natural EmFABP1 protein is predominantly expressed in protoscoleces tegument and germinal layer cells and is also detected in cyst fluid and exosomes of E. multilocularis. rEmFABP1 protein demonstrated a notable suppression of phagocytic activity and nitric oxide production in murine macrophages. Additionally, the protein was observed to promote apoptosis and regulate cytokine expression in macrophages. These findings suggested that E. multilocularis FABP1 is critical in modifying macrophage physiological processes and that this protein may have immunomodulatory roles during infection.

Investigating the Taenia solium Fatty Acid Binding Protein Superfamily for Their Immunological Outlook and Prospect for Therapeutic Targets

Taenia solium, like other helminthic parasites, lacks key components of cellular machinery required for endogenous lipid biosynthesis. This deficiency compels the parasite to obtain all of its lipid requirements from its host. The passage of lipids across the cell membrane is tightly regulated. To facilitate effective lipid transport, the cestode parasite utilizes certain lipid binding proteins called FABPs. These FABPs bind with the lipid ligands and allow the transport of lipids across the membranes and into the cytosol. Here, by integrating a computational with homology protein prediction tools, we had identified five FABPs in the T. solium proteome. We confirmed their presence by RNA expression analysis of respective genes from the parasite's cysticerci transcript. During the molecular modeling and MD simulation studies, two of them, TsM_000544100 and TsM_001185100, were most stable. Furthermore, they had a robust interaction with the IgG1 molecule, as evidenced by MD simulation. In addition, by employing in silico screening, we had identified potential ligand interacting residues that are present on the probable druggable site. In combination with in vitro cysticidal assays, enalaprilat dihydrate showed efficacy against cysticerci, which suggests that FABPs play a significant role in the cysticercus life cycle. Together, we provided a detailed distribution of all FABPs expressed by T. solium cysticerci and the critical role of TsM_001185100 in cysticercus viability.

Molecular Characteristics of the Fatty-Acid-Binding Protein (FABP) Family in Spirometra mansoni-A Neglected Medical Tapeworm

The plerocercoid larva of the tapeworm Spirometra mansoni can parasitize humans and animals, causing serious parasitic zoonosis. The molecular characteristics and adaptive parasitism mechanism of Spirometra tapeworms are still unknown. In this study, 11 new members of the fatty-acid-binding protein (FABP) family were characterized in S. mansoni. A clustering analysis showed 11 SmFABPs arranged into two groups, and motif patterns within each group had similar organizations. RT-qPCR showed that SmFABPs were highly expressed in the adult stage, especially in gravid proglottid. A high genetic diversity of SmFABPs and relative conservation of FABPs in medical platyhelminthes were observed in the phylogenetic analysis. Immunolocalization revealed that natural SmFABP is mainly located in the tegument and parenchymal tissue of the plerocercoid and the uterus, genital pores, and cortex of adult worms. rSmFABP can build a more stable holo form when binding with palmitic acid to protect the hydrolytic sites of the protein. A fatty acid starvation induction test suggested that SmFABP might be involved in fatty acid absorption, transport, and metabolism in S. mansoni. The findings in this study will lay the foundation to better explore the underlying mechanisms of FABPs involved in Spirometra tapeworms as well as related taxa.

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.

Proteomic analysis of Taenia solium cysticercus and adult stages

Taenia solium (T. solium) cysticercosis is a neglected parasitic zoonosis that occurs in developing countries. Since T. solium has a complex life cycle that includes eggs, oncospheres, cysticerci, and adults, presumably many proteins are produced that enable them to survive and establish an infection within the host. The objectives of this study were to perform a comparative proteomic analysis of two ontogenetic stages of T. solium (cysticerci and adult) and to analyze their differential expression of proteins. Methods proteins were separated by High Performance Liquid Chromatography (HPLC) fractionation, and protein samples were also digested in liquid and identified by liquid chromatography tandem mass spectrometry (LC-MS/MS); the differentially expressed proteins were then processed by a bioinformatics analysis and verified by parallel reaction monitoring (PRM). Results we identified 2,481 proteins by label-free quantitative proteomics. Then differentially expressed proteins were screened under P values < 0.05 and 2 fold change, we found that 293 proteins up-regulated and 265 proteins down-regulated. Discussion through the bioinformatics analysis, we analyzed the differences types and functions of proteins in the Taenia solium and cysticercus, the data will provide reference value for studying the pathogenic mechanism of the two stages and the interaction with the host, and also support for further experimental verification.

Function of lipid binding proteins of parasitic helminths: still a long road

Infections with parasitic helminths cause severe debilitating and sometimes lethal diseases in humans and domestic animals on a global scale. Unable to synthesize de novo their own fatty acids and sterols, helminth parasites (nematodes, trematodes, cestodes) rely on their hosts for their supply. These organisms produce and secrete a wide range of lipid binding proteins that are, in most cases, structurally different from the ones found in their hosts, placing them as possible novel therapeutic targets. In this sense, a lot of effort has been made towards the structure determination of these proteins, but their precise function is still unknown. In this review, we aim to present the current knowledge on the functions of LBPs present in parasitic helminths as well as novel members of this highly heterogeneous group of proteins.

Homology Modeling and Molecular Dynamics Simulations of Trypanosoma cruzi Phosphodiesterase b1

Cyclic nucleotide phosphodiesterases have been implicated in the proliferation, differentiation and osmotic regulation of trypanosomatids; in some trypanosomatid species, they have been validated as molecular targets for the development of new therapeutic agents. Because the experimental structure of Trypanosoma cruzi PDEb1 (TcrPDEb1) has not been solved so far, an homology model of the target was created using the structure of Trypanosoma brucei PDEb1 (TbrPDEb1) as a template. The model was refined by extensive enhanced sampling molecular dynamics simulations, and representative snapshots were extracted from the trajectory by combined clustering analysis. This structural ensemble was used to develop a structure-based docking model of the target. The docking accuracy of the model was validated by redocking and cross-docking experiments using all available crystal structures of TbrPDEb1, whereas the scoring accuracy was validated through a retrospective screen, using a carefully curated dataset of compounds assayed against TbrPDEb1 and/or TcrPDEb1. Considering the results from in silico validations, the model may be applied in prospective virtual screening campaigns to identify novel hits, as well as to guide the rational design of potent and selective inhibitors targeting this enzyme.

Ensemble learning application to discover new trypanothione synthetase inhibitors

Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is considered one of the most attractive drug targets within the thiol-polyamine metabolism of typanosomatids, being unique, essential and druggable. Here, we have compiled a dataset of 401 T. brucei TryS inhibitors that includes compounds with inhibitory data reported in the literature, but also in-house acquired data. QSAR classifiers were derived and validated from such dataset, using publicly available and open-source software, thus assuring the portability of the obtained models. The performance and robustness of the resulting models were substantially improved through ensemble learning. The performance of the individual models and the model ensembles was further assessed through retrospective virtual screening campaigns. At last, as an application example, the chosen model-ensemble has been applied in a prospective virtual screening campaign on DrugBank 5.1.6 compound library. All the in-house scripts used in this study are available on request, whereas the dataset has been included as supplementary material.

Artificial intelligence, machine learning, and drug repurposing in cancer

Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means.Areas covered: The authors focus on supervised ML and AI methods that make use of publicly available databases and information resources. While most of the example applications are in the field of anticancer drug therapies, the methods and resources reviewed are widely applicable also to other indications including COVID-19 treatment. A particular emphasis is placed on the use of comprehensive target activity profiles that enable a systematic repurposing process by extending the target profile of drugs to include potent off-targets with therapeutic potential for a new indication.Expert opinion: The scarcity of clinical patient data and the current focus on genetic aberrations as primary drug targets may limit the performance of anticancer drug repurposing approaches that rely solely on genomics-based information. Functional testing of cancer patient cells exposed to a large number of targeted therapies and their combinations provides an additional source of repurposing information for tissue-aware AI approaches.