Virtual Combinatorial Library Screening of Quinadoline B Derivatives against SARS-CoV-2 RNA-Dependent RNA Polymerase

The unprecedented global health threat of SARS-CoV-2 has sparked a continued interest in discovering novel anti-COVID-19 agents. To this end, we present here a computer-based protocol for identifying potential compounds targeting RNA-dependent RNA polymerase (RdRp). Starting from our previous study wherein, using a virtual screening campaign, we identified a fumiquinazolinone alkaloid quinadoline B (Q3), an antiviral fungal metabolite with significant activity against SARS-CoV-2 RdRp, we applied in silico combinatorial methodologies for generating and screening a library of anti-SARS-CoV-2 candidates with strong in silico affinity for RdRp. For this study, the quinadoline pharmacophore was subjected to structural iteration, obtaining a Q3-focused library of over 900,000 unique structures. This chemical library was explored to identify binders of RdRp with greater affinity with respect to the starting compound Q3. Coupling this approach with the evaluation of physchem profile, we found 26 compounds with significant affinities for the RdRp binding site. Moreover, top-ranked compounds were submitted to molecular dynamics to evaluate the stability of the systems during a selected time, and to deeply investigate the binding mode of the most promising derivatives. Among the generated structures, five compounds, obtained by inserting nucleotide-like scaffolds (1, 2, and 5), heterocyclic thiazolyl benzamide moiety (compound 3), and a peptide residue (compound 4), exhibited enhanced binding affinity for SARS-CoV-2 RdRp, deserving further investigation as possible antiviral agents. Remarkably, the presented in silico procedure provides a useful computational procedure for hit-to-lead optimization, having implications in anti-SARS-CoV-2 drug discovery and in general in the drug optimization process.

Combinatorial library screening of quinadoline B derivatives against SARS-CoV-2 RNA-dependent RNA polymerase

The unprecedented global health threat of SARS-CoV-2 has sparked a continued interest to discover novel anti-COVID-19 agents. To this end, we present here a computer-based protocol for identifying potential compounds targeting RNA-dependent RNA polymerase (RdRp). Starting from our previous study in which, by a virtual screening campaign, we identified a fumiquinazolinone alkaloid quinadoline B (Q3), an antiviral fungal metabolite with significant activity against SARS-CoV-2 RdRp, we applied an in silico combinatorial methodologies for generating and screening a library of anti-SARS-CoV-2 candidates with strong in silico affinity for RdRp. For this study, the quinadoline pharmacophore was subjected to structural iteration obtaining a Q3-focused library of over 900,000 unique structures. This chemical library was explored to identify binders of RdRp with greater affinity with respect to the starting compound Q3. Coupling this approach with the evaluation of physchem profile, we found 26 compounds with significant affinities for the RdRp binding site. Moreover, top-ranked compounds were submitted to molecular dynamics to evaluate the stability of the systems during a selected time, and for deeply investigating the binding mode of the most promising derivatives. Among the generated structures, five compounds, obtained by inserting nucleotide-like scaffolds (1, 2, and 5), heterocyclic thiazolyl benzamide moiety (compound 3), and a peptide residue (compound 4), exhibited enhanced binding affinity for SARS-CoV-2 RdRp, deserving further investigation as possible antiviral agents. Remarkably, the presented in silico procedure provides a useful computational procedure for hit-to-lead optimization, having implications in anti-SARS-CoV-2 drug discovery and in general in the drug optimization process.

The pockets guide to HLA class I molecules

Human leukocyte antigens (HLA) are cell-surface proteins that present peptides to T cells. These peptides are bound within the peptide binding cleft of HLA, and together as a complex, are recognised by T cells using their specialised T cell receptors. Within the cleft, the peptide residue side chains bind into distinct pockets. These pockets ultimately determine the specificity of peptide binding. As HLAs are the most polymorphic molecules in humans, amino acid variants in each binding pocket influences the peptide repertoire that can be presented on the cell surface. Here, we review each of the 6 HLA binding pockets of HLA class I (HLA-I) molecules. The binding specificity of pockets B and F are strong determinants of peptide binding and have been used to classify HLA into supertypes, a useful tool to predict peptide binding to a given HLA. Over the years, peptide binding prediction has also become more reliable by using binding affinity and mass spectrometry data. Crystal structures of peptide-bound HLA molecules provide a means to interrogate the interactions between binding pockets and peptide residue side chains. We find that most of the bound peptides from these structures conform to binding motifs determined from prediction software and examine outliers to learn how these HLAs are stabilised from a structural perspective.

Peptide Selectivity of the Proton-Coupled Oligopeptide Transporter from Neisseria meningitidis

Peptide transport in living organisms is facilitated by either primary transport, hydrolysis of ATP, or secondary transport, cotransport of protons. In this study, we focused on investigating the ligand specificity of the <i>Neisseria meningitidis</i> proton-coupled oligopeptide transporter (NmPOT). It has been shown that the gene encoding this transporter is upregulated during infection. NmPOT conformed to the typical chain length preference as observed in prototypical transporters of this family. In contrast to prototypical transporters, it was unable to accommodate a positively charged peptide residue at the C-terminus position of the substrate peptide. Sequence analysis of the active site of NmPOT displayed a distinctive aromatic patch, which has not been observed in any other transporters from this family. This aromatic patch may be involved in providing NmPOT with its atypical preferences. This study provides important novel information towards understanding how these transporters recognize their substrates.

A New Peptide with Membrane-permeable Function Derived from Human Circadian Proteins

Basic peptides such as human immunodeficiency virus type 1 (HIV-1) Tat-(48–60) and Drosophila Antennapedia-(43–58) have been reported to have a membrane permeability and a carrier function for intracellular protein delivery. Based on the fluorescence microscopic observations of the vascular endothelial cells (ECV-304) and the primary cultured neuroglial cells, we found that human Clock protein DNA-binding peptide [residue 35–47, hClock-(35–47)] had a translocation activity very similar to Tat-(48–60). The cellular uptake of hClock-(35–47) increases with the increase of incubation time and concentration. The internalization effect at 4 °C was same as that at 37 °C. Internalization of hClock-(35–47) was saturable and could be inhibited by the excess of the other MPPs. Moreover, The uptake of these peptides were significantly inhibited in the presence of heparan sulfate. These results strongly suggested that the hClock-(35–47) shared a common or very similar internalization pathway with other MPPs. Furthermore, we injected rat through the common carotid artery with hClock-(35–47)-FITC peptide, and cryostat sections of the brain were prepared and observed using a fluorescence microscope. Result showed that the peptide had the ability to translocate through the blood-brain barrier. It is promising to provide a new safe carrier for the intracellular and encephalic treatment.