It is demonstrated that hotspot-guided design strategy, previously applied to proteins and d-peptides, can be effectively extended to l-peptide scaffolds, enabling the development of functional HA inhibitors informed by key residues at antigen–antibody interfaces.
Abstract
Here we report the applicability of a hotspot-centric approach for de novo computational design of l-peptides based on crystal structures of antigen–antibody complexes. Broadly neutralizing antibodies (bnAbs) FI6v3 and CR9114, which target influenza A virus hemagglutinin (HA), guided the peptide design. Disembodied hotspot residues from these bnAbs were selected and anchored onto known peptide scaffolds (≤35 amino acids) from the Protein Data Bank (PDB). The top-scoring designs were subsequently synthesized, folded, tested in vitro, and structurally characterized in complex with HA. The designed peptides demonstrate structural and functional mimicry by recapitulating the binding mode of the bnAbs on HA and act as inhibitors of low-pH-dependent conformational transitions in HA that facilitate membrane fusion. These findings demonstrate that hotspot-guided design strategy, previously applied to proteins and d-peptides, can be effectively extended to l-peptide scaffolds, enabling the development of functional HA inhibitors informed by key residues at antigen–antibody interfaces.
Peptide-based fusion inhibitors are promising pharmaceuticals in the fight against enveloped viruses relying on membrane fusion for host infection. However, peptide therapeutic applications have long been hindered by their poor stability in vivo. Here, we discovered that peptide inhibitors with the wildtype sequence of...
Kailu Yang, Chu-Chu Wang, Francesco Topi et al.· bioRxiv· 0 citations
Detailed molecular dynamics simulations combined with free energy perturbation calculations were used to systematically investigate the effects of point mutations on both the fusion peptide and the antibody, providing a quantitative and structural framework for understanding fusion peptide recognition.
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SARS-CoV-2 papain-like protease (PLpro) remains an attractive antiviral target because of its dual role in viral polyprotein processing and host immune modulation. In this study, we employed an exploratory structure-based computational workflow to identify antimicrobial peptide scaffolds with predicted PLpro-binding po...
Erenilson dos Santos Moreira, S. Siqueira, F. Barbosa et al.· Scientific Reports· 0 citations
INTRODUCTION
The emergence of Monkeypox Virus (MPXV) as a major global health concern underscores an urgent unmet need for innovative antiviral therapeutics. To address this need, a novel large-scale in silico screening strategy was adopted to identify highly potent antiviral cyclic peptides that inhibit the A42R profi...
Ahmad Firoz, Hani S. H. Mohammed Ali, I. Ullah· Current Drug Targets· 0 citations
The SARS-CoV-2 envelope protein (protein E) is a small but multifunctional structural protein that plays a critical role in viral assembly, budding, and pathogenesis, making it an attractive target for therapeutic intervention. This study investigated the interaction between the SARS-CoV-2 envelope protein (wild type a...
Afifah Husni Riani, Surya Rosa Putra, Devy Maulidya Cahyani et al.· EPJ Web of Conferences· 0 citations
The Zika virus NS2B/NS3 protease is an important antiviral target, and macrocyclic peptide inhibitors represent promising scaffolds because they combine multibasic recognition motifs with conformational restriction. Here, we investigated two structurally related cyclic peptide inhibitors, referred to as CP1 and CP2, wh...
Camilla Vitoria Silva Marinho, M. D. D. de Oliveira, Anderson H. Lima· Journal of Molecular Modelin...· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
