Sequential Application of Ligand and Structure Based Modeling Approaches to Index Chemicals for Their hH4R Antagonism

The human histamine H₄ receptor (hH₄R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH₄R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH₄R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH₄R bioactivity. An application of the prediction model on external test set composed of more than 160 hH₄R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼4000 chemicals highly indexed as H₄R antagonists'' candidates. Next, a series of 3D models of hH₄R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH₄R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.     

DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules

Metabolomics - Food and dietary ingredients have significant effects on metabolism and health. To evaluate whether and how different diets affected the serum lipidomic profile of dogs. Sixteen...     

Digital transformation—life cycle assessment of digital services,multifunctional devices and cloud computing

The International Journal of Life Cycle Assessment -     

Comparing the binding properties of peptides mimicking the Envelope protein of SARS‐CoV and SARS‐CoV‐2 to the PDZ domain of the tight junction‐associated PALS1 protein

The Envelope protein (E) is one of the four structural proteins encoded by the genome of SARS‐CoV and SARS‐CoV‐2 Coronaviruses. It is an integral membrane protein, highly expressed in the host cell, which is known to have an important role in Coronaviruses maturation, assembly and virulence. The E protein presents a PDZ‐binding motif at its C‐terminus. One of the key interactors of the E protein in the intracellular environment is the PDZ containing protein PALS1. This interaction is known to play a key role in the SARS‐CoV pathology and suspected to affect the integrity of the lung epithelia. In this paper we measured and compared the affinity of peptides mimicking the E protein from SARS‐CoV and SARS‐CoV‐2 for the PDZ domain of PALS1, through equilibrium and kinetic binding experiments. Our results support the hypothesis that the increased virulence of SARS‐CoV‐2 compared to SARS‐CoV may rely on the increased affinity of its Envelope protein for PALS1.     

Purification of rabies virus glycoprotein produced in Drosophila melanogaster S2 cells: An efficient immunoaffinity method

Most rabies vaccines are based on inactivated virus, which production process demands a high level of biosafety structures. In the past decades, recombinant rabies virus glycoprotein (RVGP) produced in several expression systems has been extensively studied to be used as an alternative vaccine. The immunogenic characteristics of this protein depend on its correct conformation, which is present only after the correct post-translational modifications, typically performed by animal cells. The main challenge of using this protein as a vaccine candidate is to keep its trimeric conformation after the purification process. We describe here a new immunoaffinity chromatography method using a monoclonal antibody for RVGP Site II for purification of recombinant rabies virus glycoprotein expressed on the membrane of Drosophila melanogaster S2 cells. RVGP recovery achieved at least 93%, and characterization analysis showed that the main antigenic proprieties were preserved after purification.     

Pretreatment free of 2,4-dichlorophenoxyacetic acid improves the differentiation of sugarcane somatic embryos by affecting the hormonal balance and the accumulation of reserves

Plant Cell, Tissue and Organ Culture (PCTOC) - Several factors influence culture conditions and somatic embryogenesis responses, such as the role of plant growth regulators (PGRs) during the...     

Analysing the yeast complexome—the Complex Portal rising to the challenge

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.