In silico Prediction and Physicochemical Analysis of Mutant Anticancer Short-length Pardaxin 6 Peptide Fragments Derived from Pardachirus Marmoratus 

Sau Har Lee^1,2,*, Yong Hui Wong¹ 

Abstract

Introduction: Cancer is a worldwide health issue, and conventional therapies are facing obstacles due to drug resistance and a wide range of side effects. Interestingly, peptides have emerged as promising therapeutic alternatives in the pharmaceutical industry, especially in the fight against cancer. Recent research utilised marine-derived sources of lead compounds in the drug discovery field for the treatment of various diseases, including their anti-cancer potential. Herein, we aim to study the anticancer activities of Red Sea Moses sole, Pardachirus marmoratus-derived peptides, namely pardaxin 6, in the form of short-length peptides through in silico approach. Methods: Fragmented peptides ranging from 5 to 15 amino acids were derived from parental peptides. These peptides were further mutated (quote technique), and along with the original fragmented peptides, were predicted for their Support Vector Machine (SVM) scores and physicochemical properties. The top mutant peptides were further examined for their toxicity, hemolytic probability, peptide structures, docking models (state enzyme/ receptor/ pathway) and energy scores using various web servers. The trend of fragmented and mutant peptides SVM scores, hemolytic possibility, and docking energy scores across 5 to 15 amino acid fragments were analyzed. Results: Results showed that when the amino acid numbers increased, the original peptides’ SVM score increased, whereas the mutant peptides showed a decreasing trend. Similarly, for the mutant peptides analysis, both the hemolytic probability and docking energy scores towards the FAS receptor showed an increasing pattern as the peptide length built up. Conclusion: This in silico prediction found shorter length pardaxin 6 peptide fragments derived from Pardachirus Marmoratus that could have good potential to be developed as anti-cancer agents in the future. 

Keywords: In silico prediction, Pardaxin, Anticancer peptides, Pardachirus marmoratus-derived peptides, Cancer

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