Mirabilis Antiviral Protein (MAP) is a specific protein found in the Mirabilis jalapa. The MAP has many promising benefits, one of them is that it can be used as biopesticides. However, the structure and visualization of protein from MAP have not been identified. This study investigated the modelling structures of MAP compounds which potentially become bioinsecticide for insect and the interaction between bonding ligand-receptor in the surface cell. This research used In silico models that refers to the BIOPEP database with the bioinformatics tools methods. The screening of MAP compounds was conducted through hydrolysis steps by 30 enzymes to become new peptides. The new Antimicrobial Peptides (AMPs) were analyzed by a multidimensional statistical analysis using four predicted algorithms, Support Vector Machines (SVM), Random Forest (RF), a Neural Network Artificial (ANN) and Discriminant Analysis (DA) that were available in the Anti-Microbial Peptides Collection (CAMP Database). The results were identified six new types of AMPs from 449 AMPs during the in-silico proteolysis process toward M. jalapa. This peptide predicted the function become antimicrobials by inactivating the ribosomes. There were obtained three of the best peptide structures from M. jalapa that have the potential as toxin compounds (biopesticides). Through the visualization of the three AMPs, models of biopesticide structures are WIFKTVEEIKLVMGLLKSS, IKLVMGLLKSS, and ITNIRTKVA with the residual category 6-22, and the characterization of molecular weight was 561,7 to 2971,4 g/mol. The AMPs fulfill the Boman Index which the measurement of protein-peptide affinity to build the biological interactions, ranging from -0,51 to 2,98. Further, these renewable peptides can be used to determine the pathways that occur in targeted insect pests as biopesticides.
Read full abstract