Філософія популізму як варіант сучасної філософії

We have previously reported on the functional interaction of Lipid II with human alpha-defensins, a class of antimicrobial peptides. Lipid II is an essential precursor for bacterial cell wall biosynthesis and an ideal and validated target for natural antibiotic compounds. Using a combination of structural, functional and in silico analyses, we present here the molecular basis for defensin-Lipid II binding. Based on the complex of Lipid II with Human Neutrophil peptide-1, we could identify and characterize chemically diverse low-molecular weight compounds that mimic the interactions between HNP-1 and Lipid II. Lead compound BAS00127538 was further characterized structurally and functionally; it specifically interacts with the N-acetyl muramic acid moiety and isoprenyl tail of Lipid II, targets cell wall synthesis and was protective in an in vivo model for sepsis. For the first time, we have identified and characterized low molecular weight synthetic compounds that target Lipid II with high specificity and affinity. Optimization of these compounds may allow for their development as novel, next generation therapeutic agents for the treatment of Gram-positive pathogenic infections

The RNA acetyltransferase driven by ATP hydrolysis synthesizes N4-acetylcytidine of tRNA anticodon

The wobble base of Escherichia coli elongator tRNAMet is modified to N4-acetylcytidine (ac4C), which is thought to ensure the precise recognition of the AUG codon by preventing misreading of near-cognate AUA codon. By employing genome-wide screen of uncharacterized genes in Escherichia coli (‘ribonucleome analysis'), we found the ypfI gene, which we named tmcA (tRNAMet cytidine acetyltransferase), to be responsible for ac4C formation. TmcA is an enzyme that contains a Walker-type ATPase domain in its N-terminal region and an N-acetyltransferase domain in its C-terminal region. Recombinant TmcA specifically acetylated the wobble base of E. coli elongator tRNAMet by utilizing acetyl-coenzyme A (CoA) and ATP (or GTP). ATP/GTP hydrolysis by TmcA is stimulated in the presence of acetyl-CoA and tRNAMet. A mutation study revealed that E. coli TmcA strictly discriminates elongator tRNAMet from the structurally similar tRNAIle by mainly recognizing the C27–G43 pair in the anticodon stem. Our findings reveal an elaborate mechanism embedded in tRNAMet and tRNAIle for the accurate decoding of AUA/AUG codons on the basis of the recognition of wobble bases by the respective RNA-modifying enzymes

A physicochemical descriptor-based scoring scheme for effective and rapid filtering of kinase-like chemical space

<p>Abstract</p> <p>Background</p> <p>The current chemical space of known small molecules is estimated to exceed 10⁶⁰structures. Though the largest physical compound repositories contain only a few tens of millions of unique compounds, virtual screening of databases of this size is still difficult. In recent years, the application of physicochemical descriptor-based profiling, such as Lipinski's rule-of-five for drug-likeness and Oprea's criteria of lead-likeness, as early stage filters in drug discovery has gained widespread acceptance. In the current study, we outline a kinase-likeness scoring function based on known kinase inhibitors.</p> <p>Results</p> <p>The method employs a collection of 22,615 known kinase inhibitors from the ChEMBL database. A kinase-likeness score is computed using statistical analysis of nine key physicochemical descriptors for these inhibitors. Based on this score, the kinase-likeness of four publicly and commercially available databases, i.e., National Cancer Institute database (NCI), the Natural Products database (NPD), the National Institute of Health's Molecular Libraries Small Molecule Repository (MLSMR), and the World Drug Index (WDI) database, is analyzed. Three of these databases, i.e., NCI, NPD, and MLSMR are frequently used in the virtual screening of kinase inhibitors, while the fourth WDI database is for comparison since it covers a wide range of known chemical space. Based on the kinase-likeness score, a kinase-focused library is also developed and tested against three different kinase targets selected from three different branches of the human kinome tree.</p> <p>Conclusions</p> <p>Our proposed methodology is one of the first that explores how the narrow chemical space of kinase inhibitors and its relevant physicochemical information can be utilized to build kinase-focused libraries and prioritize pre-existing compound databases for screening. We have shown that focused libraries generated by filtering compounds using the kinase-likeness score have, on average, better docking scores than an equivalent number of randomly selected compounds. Beyond library design, our findings also impact the broader efforts to identify kinase inhibitors by screening pre-existing compound libraries. Currently, the NCI library is the most commonly used database for screening kinase inhibitors. Our research suggests that other libraries, such as MLSMR, are more kinase-like and should be given priority in kinase screenings.</p

Molecular amino acid signatures in the MHC class II peptide-binding pocket predispose to autoimmune thyroiditis in humans and in mice

Hashimoto's thyroiditis (HT) is associated with HLA, but the associated allele is still controversial. We hypothesized that specific HLA-DR pocket-sequence variants are associated with HT and that similar variants in the murine I-E locus (homologous to HLA-DR) predispose to experimental autoimmune thyroiditis (EAT), a classical mouse model of HT. Therefore, we sequenced the polymorphic exon 2 of the HLA-DR gene in 94 HT patients and 149 controls. In addition, we sequenced exon 2 of the I-E gene in 22 strains of mice, 12 susceptible to EAT and 10 resistant. Using logistic regression analysis, we identified a pocket amino acid signature, Tyr-26, Tyr-30, Gln-70, Lys-71, strongly associated with HT (P = 6.18 × 10−5, OR = 3.73). Lys-71 showed the strongest association (P = 1.7 × 10−8, OR = 2.98). This association was seen across HLA-DR types. The 5-aa haplotype Tyr-26, Tyr-30, Gln-70, Lys-71, Arg-74 also was associated with HT (P = 3.66 × 10−4). In mice, the I-E pocket amino acids Val-28, Phe-86, and Asn-88 were strongly associated with EAT. Structural modeling studies demonstrated that pocket P4 was critical for the development of HT, and pockets P1 and P4 influenced susceptibility to EAT. Surprisingly, the structures of the HT- and EAT-susceptible pockets were different. We conclude that specific MHC II pocket amino acid signatures determine susceptibility to HT and EAT by causing structural changes in peptide-binding pockets that may influence peptide binding, selectivity, and presentation. Because the HT- and EAT-associated pockets are structurally different, it is likely that distinct antigenic peptides are associated with HT and EAT