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

Abstract

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.

Exploratory data analysis of physicochemical parameters of natural antimicrobial and anticancer peptides: Unraveling the patterns and trends for the rational design of novel peptides

“…For instance, it has been observed that subset 21-30 contains most of AMPs and ACPs followed by 11-20 and 31-40 as compared to other AMPs and ACPs subsets. Moreover, due to the significance of subsets information in the computer aided design of peptides as shown by few recent studies 78 we also extracted descriptive statistics (Table S1 & S2, Supplementary file 3 ) and prepared a graphical profile (Figs. S1-S11, Supplementary file 4 & Figs.…”

“…For instance, it has been observed that subset 21-30 contains most of AMPs and ACPs followed by 11-20 and 31-40 as compared to other AMPs and ACPs subsets. Moreover, due to the significance of subsets information in the computer aided design of peptides as shown by few recent studies 78 we also extracted descriptive statistics (Table S1 & Furthermore, the methodology used in this work can be used for the exploratory data analysis of the other peptide datasets such as anti-allergic, anti-hypertensive, antidiabetic, anti-inflammatory and immunomodulatory peptides etc. Additionally, our future work involves designing novel AMPs or ACPs based on the derived parameters.…”

Expanding the Landscape of Amino Acid-Rich Antimicrobial Peptides: Definition, Deployment in Nature, Implications for Peptide Design and Therapeutic Potential

“…In the APD, there are 16 natural θ-defensins, which are smaller than either α-defensins or β-defensins [ 60 ]. Theta-defensins present a remarkably unique amino acid signature [ 74 ], where the polar group (Thr, Ser, Gln, and Asn, and Tyr, based on the APD) is represented only by threonine, the glycine/proline group (Gly and Pro) uses only glycine, and the charge group (Lys, Arg, His, Asp, and Glu) contains solely arginine. Only the hydrophobic group (Leu, Val, Ile, Ala, Met, Phe, Trp, and Cys) is diversified with five types of amino acids: leucine, isoleucine, valine, alanine, and cysteine in this family of circular peptides.…”