Studies of antibacterial activity (in vitro and in vivo) and mode of action for des-acyl tridecaptins (DATs).

Tridecaptins comprise a class of linear cationic lipopeptides with an N-terminal fatty acyl moiety. These 13-mer antimicrobial peptides consist of a combination of d- and l-amino acids, conferring increased proteolytic stability. Intriguingly, they are biosynthesized by non-ribosomal peptide synthetases in the same bacterial species that also produce the cyclic polymyxins displaying similar fatty acid tails. Previously, the des-acyl analog of TriA1 (termed H-TriA1) was found to possess very weak antibacterial activity, albeit it potentiated the effect of several antibiotics. In the present study, two series of des-acyl tridecaptins were explored with the aim of improving the direct antibacterial effect. At the same time, overall physico-chemical properties were modulated by amino acid substitution(s) to diminish the risk of undesired levels of hemolysis and to avoid an impairment of mammalian cell viability, since these properties are typically associated with highly hydrophobic cationic peptides. Microbiology and biophysics tools were used to determine bacterial uptake, while circular dichroism and isothermal calorimetry were used to probe the mode of action. Several analogs had improved antibacterial activity (as compared to that of H-TriA1) against Enterobacteriaceae. Optimization enabled identification of the lead compound 29 that showed a good ADMET profile as well as in vivo efficacy in a variety of mouse models of infection.

Full Profiling of GE81112A, an Underexplored Tetrapeptide Antibiotic with Activity against Gram-Negative Pathogens.

After the first total synthesis combined with structure revision, we performed thorough in vitro and in vivo profiling of the underexplored tetrapeptide GE81112A. From the determination of the biological activity spectrum and physicochemical and early absorption-distribution-metabolism-excretion-toxicity (eADMET) properties, as well as in vivo data regarding tolerability and pharmacokinetics (PK) in mice and efficacy in an Escherichia coli-induced septicemia model, we were able to identify the critical and limiting parameters of the original hit compound. Thus, the generated data will serve as the basis for further compound optimization programs and developability assessments to identify candidates for preclinical/clinical development derived from GE81112A as the lead structure. IMPORTANCE The spread of antimicrobial resistance (AMR) is becoming a more and more important global threat to human health. With regard to current medical needs, penetration into the site of infection represents the major challenge in the treatment of infections caused by Gram-positive bacteria. Considering infections associated with Gram-negative bacteria, resistance is a major issue. Obviously, novel scaffolds for the design of new antibacterials in this arena are urgently needed to overcome this crisis. Such a novel potential lead structure is represented by the GE81112 compounds, which inhibit protein synthesis by interacting with the small 30S ribosomal subunit using a binding site distinct from that of other known ribosome-targeting antibiotics. Therefore, the tetrapeptide antibiotic GE81112A was chosen for further exploration as a potential lead for the development of antibiotics with a new mode of action against Gram-negative bacteria.

A Strategy Combining Differential Low-Throughput Screening and Virtual Screening (DLS-VS) Accelerating the Discovery of new Modulators for the Orphan GPR34 Receptor.

The DLS-VS strategy was developed as an integrated method for identifying chemical modulators for orphan GPCRs. It combines differential low-throughput screening (DLS) and virtual screening (VS). The two cascaded techniques offer complementary advantages and allow the experimental testing of a minimal number of compounds. First, DLS identifies modulators specific for the considered receptor among a set of receptors, through the screening of a small library with diverse chemical compounds. Then, an active molecular model of the receptor is built by homology to a validated template, and it is progressively refined by rotamers modification for key side-chains, by VS of the already screened library, and by iterative selection of the model generating the best enrichment. The refined active model is finally used for the VS of a large chemical library and the selection of a small set of compounds for experimental testing. Applied to the orphan receptor GPR34, the DLS-VS strategy combined the experimental screening of 20 000 compounds and the virtual screening of 1 250 000 compounds. It identified one agonist and eight inverse agonists, showing a high chemical diversity. We describe the method. The strategy can be applied to other GPCRs.