NeuroPIpred is an in silico method, which is developed to predict and design insect neuropeptides with better efficacy for controlling pest from infesting various crops. We created two datasets (i) Natural dataset: This dataset comprises only natural peptides and there are 875 positive and 875 negative peptides. (ii) Modified dataset: This dataset consists of peptides which are modified at C-terminus and there are 2024 positive peptides and 1582 negative peptides.
NeuroPIPred Major features
- Predict: This module can be used to forecast whether a peptide is a neuropeptide or a non-neuropeptide along with the prediction score and it also calculates the various physiochemical properties.
- Designing Peptide: This module can be utilized to generate mutant analogs of given input neuropeptide, which can target neuropeptide-receptor complex and paralyze signal transduction pathway. The tool has a potential application in creating neuropeptide-based insecticides for integrated pest management.
- Protein Scanning : This module generates all possible overlapping peptides and their single mutant analogs of protein submitted by the user. It also predicts whether overlapping peptide/analog is neuropeptide or not.
- BLAST : BLAST seacrh will help user in indentifying experimental insect neuropeptides similar to the given query peptide.
- Download: This module provides the datasets used in this study.
One of the major features of server is that it also calculates various physicochemical properties. Peptide analogs can be displayed in sorting order based upon desired properties.