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Presentation date

2021

College, Institute, or Department

Pathology and Microbiology

Faculty Mentor

Dr. Guangshun Wang, Dr. St. Patrick Reid, Dr. Yangsheng Yu

Abstract

Natural antimicrobial peptides (AMPs) aid in many organisms innate immune defense against pathogens. Engineering new therapeutics from natural AMP templates may provide an effective treatment to emerging microbial infections such as SARS-CoV-2, Ebola viruses, and drug-resistant bacteria. One way to design antimicrobial peptides is the database filtering technology (DFT). The DFT is an ab initio design that selects the most probable parameters for an AMP by statistical analysis in the antimicrobial peptide database (https://aps.unmc.edu). To our knowledge, the DFT design has never been used to develop an antiviral peptide. We present here the improved DFT that enables a faster and more efficient design. Indeed, the peptide designed in this manner inhibits both SARS-CoV-2 and Ebola viruses. We also validated that deviations from the most probable length or amino acids led to a decrease in peptide activity. Further refinement of the peptide by introducing a disulfide bond improved peptide stability to proteases such as chymotrypsin and trypsin. Our database designed and improved peptide 1 (DDIP1) has the potential as a novel antiviral agent.

Keywords

Antimicrobial Peptides, Antiviral, APD3, Ebola, SARS-CoV-2

Inhibitory Effects of ab initio Antiviral Peptides Efficiently Designed Based on APD3 Database

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