Structure-based design and optimization of ligands for novel antiviral strategies

The coronavirus pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). There have been over 777 million reported COVID-19 cases and ~7 million deaths by January 2025. Since the virus was identified, scientists around the world have been continuously searching for improved SARS CoV-2 treatment strategies. Neutralizing antibodies that bind to viral fusion proteins block the fusion process thereby preventing infection. Such antibodies can also serve as templates for the generation of peptides, which retain the ability to bind to viral proteins thereby blocking viral fusion, and thus represent drug candidates. In the present project funded within the DFG GRK2504, we use computational methods, in particular molecular dynamics (MD) simulations, to identify peptide ligands targeting the spike-protein of CoV-2. 

In the first phase of the project, we have already established a computational pipeline for the high-throughput analysis of antibody-antigen complexes to identify high-affinity “complementarity determining regions” (CDRs) that can serve as basis for peptide design. This pipeline has been used to scan more than 1300 complexes of HIV-1 and CoV-2 fusion proteins (gp120, spike) with different antibodies, from which the energetically most favorable CDRs were selected for further characterization. For example, this approach allowed the identification of sulfated CDRs as high-affinity gp120-binders, and a CDR of antibody PG16 proved to be functional in subsequent experiments (Deubler et al., 2023). Despite this promising result for PG16-derived peptides, the overall success rate of the prediction strategy remained low. Further, a comparison of binding and non-binding peptides from our work also suggests that a high conformational stability of the free peptide is beneficial for binding. The current work takes this finding into account by selecting 20 CDRs that exhibit a high degree of intramolecular stabilization (e.g. by a β-hairpin) for further characterization. For those peptides, we perform long (5-µs) MD simulations of the free peptide to assess their conformational stability. To enhance statistical significance, three independent simulations are generally performed for each system investigated in our project. In the next step, we will investigate whether the conformational stability of the peptides can be enhanced by introduction of an additional disulfide bond, which proved to be a successful concept in our previous peptide studies. The 10 most promising candidates will then additionally be investigated in complex with their antigen by 1-µs MD simulations. 

In the second part of the project, we focus on bovine antibodies that contain exceptionally long (up to 70 residues) CDR segments (so-called "knob domains"). These knob domains have been shown to exhibit antiviral activity on their own, which can be enhanced by stabilizing the interaction between their N- and C-termini. We have investigated the dynamics of 19 bovine antibodies of known structure (1-µs MD simulations). These simulations helped us define the approximate length of the knob domains, which will be simulated as isolated units. Based on the results from these simulations the length of the knob domains will be further optimized by performing MD simulations with different lengths of the N- and C-termini as well as a covalent linkage of the termini by an additional disulfide bond (2-µs MD simulations). For all systems investigated above, the most promising candidates will be selected for experimental verification of their binding and neutralization properties, which is performed in collaboration with Prof. Jutta Eichler (Pharmaceutical Chemistry, FAU Erlangen) and Prof. Klaus Überla (Virology, FAU Erlangen).

References:

Deubler M, Weißenborn L, Leukel S, Horn AHC, Eichler J, Sticht H (2023). Computational Characterization of the Binding Properties of the HIV1-Neutralizing Antibody PG16 and Design of PG16-Derived CDRH3 Peptides. Biology (Basel) 12: 824.