Pathogens can have dramatic impact on human society. SARS-CoV-2 has caused a devastating COVID-19 pandemic by its rapid spreading and moderate mortality. Blocking SARS-CoV-2 from invading host cell is a straightforward and promising strategy to treat the virus. Using computational modeling methods, peptide inhibitors of SARS-CoV-2 were designed by mimicking ACE2 (cellular receptor of SARS-CoV-2) [1]. An algorithm was developed to further optimize the sequence of those inhibitors and address the mutation strains of SARS-CoV-2 [2]. To trigger the recognition and cleaning of SARS-CoV-2 by the preexisting antibody without vaccine, double-faced boosters were designed computationally. One booster face is made of ACE2-mimics that can bind to the receptor binding domain (RBD) of SARS-CoV-2. The other booster face is composed of a Hepatitis B core-antigen, targeting the Hepatitis B antibody fragment. Molecular dynamics (MD) simulations revealed that the designed boosters have a highly specific and stable binding both to RBD and the antibody fragment (AF) [3]. In addition, different nanomaterials presenting multivalent binding properties against other pathogens, such as HIV, HSV, and HPV, were also studied. Modified nanoparticles (NPs), cyclodextrins (CDns), functionalized Boron clusters were simulated to clarify their binding modes to their specific targets. Working mechanisms of antiviral NPs and CDns were proposed based on MD simulations [4-6].

Design and simulations of inhibitors against different viral pathogens

ACS Spring Meeting 2021

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.