Hydrophobic diversification is the key to simultaneously increased antifungal activity and decreased cytotoxicity of two ab initio designed peptides.

The fact that some antimicrobial peptides have been utilized clinically and as food preservatives stimulated the efforts in search of new candidates. In our previous studies, we succeeded in designing potent peptides against methicillin-resistant Staphylococcus aureus (MRSA), severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), and Ebola viruses based on the database filtering technology. The designed peptides were proved highly potent. However, this ab initio method has not been utilized to design antifungal peptides. This study report two novel antifungal peptides with 21 and 15 amino acids designed by more effectively extracting the most probable parameters from ∼1200 antifungal peptides in the antimicrobial peptide database (APD). Subsequent hydrophobic diversification led to two peptide variants with enhanced activity against four fungal strains but reduced cytotoxicity to four mammalian cell lines. DFTAFP-1A (KWSGAAAKKLKSLLSGLGKLL) and DFTAFP-2A (KWSGLLLKLGAASKL) retained activity against Zygosaccharomyces bailii at pH 5.6 and 6.3 or after autoclave. The peptides could permeabilize fungal membranes and adopted helical conformations in membrane mimetic micelles. Collectively, this study demonstrated not only the successful design of two novel antifungal peptides based on the APD database but also optimization of desired peptide properties. This improved database approach may be utilized to design useful peptides to combat other drug-resistant pathogens as well.

Improved Database Filtering Technology Enables More Efficient Ab Initio Design of Potent Peptides against Ebola Viruses.

The rapid mutations of viruses such as SARS-CoV-2 require vaccine updates and the development of novel antiviral drugs. This article presents an improved database filtering technology for a more effective design of novel antiviral agents. Different from the previous approach, where the most probable parameters were obtained stepwise from the antimicrobial peptide database, we found it possible to accelerate the design process by deriving multiple parameters in a single step during the peptide amino acid analysis. The resulting peptide DFTavP1 displays the ability to inhibit Ebola virus. A deviation from the most probable peptide parameters reduces antiviral activity. The designed peptides appear to block viral entry. In addition, the amino acid signature provides a clue to peptide engineering to gain cell selectivity. Like human cathelicidin LL-37, our engineered peptide DDIP1 inhibits both Ebola and SARS-CoV-2 viruses. These peptides, with broad antiviral activity, may selectively disrupt viral envelopes and offer the lasting efficacy required to treat various RNA viruses, including their emerging mutants.