In Silico Design of New Inhibitors Against Hemagglutinin of Influenza

MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods

Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of ca. 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.

Antitarget, Anti-SARS-CoV-2 Leads, Drugs, and the Drug Discovery-Genetics Alliance Perspective

The most advanced antiviral molecules addressing major SARS-CoV-2 targets (Main protease, Spike protein, and RNA polymerase), compared with proteins of other human pathogenic coronaviruses, may have a short-lasting clinical efficacy. Accumulating knowledge on the mechanisms underlying the target structural basis, its mutational progression, and the related biological significance to virus replication allows envisaging the development of better-targeted therapies in the context of COVID-19 epidemic and future coronavirus outbreaks. The identification of evolutionary patterns based solely on sequence information analysis for those targets can provide meaningful insights into the molecular basis of host-pathogen interactions and adaptation, leading to drug resistance phenomena. Herein, we will explore how the study of observed and predicted mutations may offer valuable suggestions for the application of the so-called "synthetic lethal" strategy to SARS-CoV-2 Main protease and Spike protein. The synergy between genetics evidence and drug discovery may prioritize the development of novel long-lasting antiviral agents.

Antiviral Activity of a Cyclic Pro-Pro-β3-HoPhe-Phe Tetrapeptide against HSV-1 and HAdV-5

The core of Cyclolinopeptide A (CLA, cyclo(LIILVPPFF)), responsible for its high immunosuppressive activity, contains a Pro-Pro-Phe-Phe sequence. A newly synthesized cyclic tetrapeptide, cyclo(Pro-Pro-β3-HoPhe-Phe) (denoted as 4B8M) bearing the active sequence of CLA, was recently shown to exhibit a wide array of anti-inflammatory properties in mouse models. In this investigation, we demonstrate that the peptide significantly inhibits the replication of human adenovirus C serotype 5 (HAdV-5) and Herpes simplex virus type-1 (HSV-1) in epithelial lung cell line A-549, applying Cidofovir and Acyclovir as reference drugs. Based on a previously established mechanism of its action, we propose that the peptide may inhibit virus replication by the induction of PGE2 acting via EP2/EP4 receptors in epithelial cells. In summary, we reveal a new, antiviral property of this anti-inflammatory peptide.

Inhibition of Viral Membrane Fusion by Peptides and Approaches to Peptide Design

Fusion of lipid-enveloped viruses with the cellular plasma membrane or the endosome membrane is mediated by viral envelope proteins that undergo large conformational changes following binding to receptors. The HIV-1 fusion protein gp41 undergoes a transition into a "six-helix bundle" after binding of the surface protein gp120 to the CD4 receptor and a co-receptor. Synthetic peptides that mimic part of this structure interfere with the formation of the helix structure and inhibit membrane fusion. This approach also works with the S spike protein of SARS-CoV-2. Here we review the peptide inhibitors of membrane fusion involved in infection by influenza virus, HIV-1, MERS and SARS coronaviruses, hepatitis viruses, paramyxoviruses, flaviviruses, herpesviruses and filoviruses. We also describe recent computational methods used for the identification of peptide sequences that can interact strongly with protein interfaces, with special emphasis on SARS-CoV-2, using the PePI-Covid19 database.

Computational prediction of the supramolecular self-assembling properties of organic molecules: the role of conformational flexibility of amide moieties

Two families of organic molecules with different backbones have been considered. The first family is based on a macrolactam-like unit that is constrained in a particular conformation. The second family is composed by a substituted central phenyl that allows a larger mobility for its substituents. They have however a common feature, three amide moieties (within the cycle for the macrolactam-like molecule and as substituents for the phenyl) that permit hydrogen bonding when molecules are stacked. In this study we propose a computational protocol to unravel the ability of the different families to self-assemble into organic nanotubes. Starting from the monomer and going towards larger assemblies like dimers, trimers, and pentamers we applied the different protocols to rationalize the behavior of the different assemblies. Both structures and thermodynamics were investigated to give a complete picture of the process. Thanks to the combination of a quantum mechanics approach and molecular dynamics simulations along with the use of tailored tools (non covalent interaction visualization) and techniques (umbrella sampling), we have been able to differentiate the two families and highlight the best candidate for self-assembling purposes.

Grafting Methionine on 1F1 Ab Increases the Broad-Activity on HA Structural-Conserved Residues of H1, H2, and H3 Influenza a Viruses

A high level of mutation enables the influenza A virus to resist antibiotics previously effective against the influenza A virus. A portion of the structure of hemagglutinin HA is assumed to be well-conserved to maintain its role in cellular fusion, and the structure tends to be more conserved than sequence. We designed peptide inhibitors to target the conserved residues on the HA surface, which were identified based on structural alignment. Most of the conserved and strongly similar residues are located in the receptor-binding and esterase regions on the HA1 domain In a later step, fragments of anti-HA antibodies were gathered and screened for the binding ability to the found conserved residues. As a result, Methionine amino acid got the best docking score within the −2.8 Å radius of Van der Waals when it is interacting with Tyrosine, Arginine, and Glutamic acid. Then, the binding affinity and spectrum of the fragments were enhanced by grafting hotspot amino acid into the fragments to form peptide inhibitors. Our peptide inhibitor was able to form in silico contact with a structurally conserved region across H1, H2, and H3 HA, with the binding site at the boundary between HA1 and HA2 domains, spreading across different monomers, suggesting a new target for designing broad-spectrum antibody and vaccine. This research presents an affordable method to design broad-spectrum peptide inhibitors using fragments of an antibody as a scaffold.

The Symmetric Difference Distance: A New Way to Evaluate the Evolution of Interfaces along Molecular Dynamics Trajectories; Application to Influenza Hemagglutinin

We propose a new and easy approach to evaluate structural dissimilarities between frames issued from molecular dynamics, and we test this methodology on human hemagglutinin. This protein is responsible for the entry of the influenza virus into the host cell by endocytosis, and this virus causes seasonal epidemics of infectious disease, which can be estimated to result in hundreds of thousands of deaths each year around the world. We computed the three interfaces between the three protomers of the hemagglutinin H1 homotrimer (PDB code: 1RU7) for each of its conformations generated from molecular dynamics simulation. For each conformation, we considered the set of residues involved in the union of these three interfaces. The dissimilarity between each pair of conformations was measured with our new methodology, the symmetric difference distance between the associated set of residues. The main advantages of the full procedure are: (i) it is parameter free; (ii) no spatial alignment is needed and (iii) it is simple enough so that it can be implemented by a beginner in programming. It is shown to be a relevant tool to follow the evolution of the conformation along the molecular dynamics trajectories.