NTXpred: Prediction of Neurotoxins Based on Their Function and Source

NTXpred: Prediction of Neurotoxins Based on Their Function and Source Overview NTXpred is a computational platform developed for predicting neurotoxins and classifying them based on their biological source and functional activity. The system uses multiple machine learning and sequence-analysis approaches including: Support Vector Machine (SVM) Feed Forward Neural Network (FNN) Recurrent Neural Network (RNN) PSI-BLAST MEME/MAST The platform predicts: Neurotoxin proteins Source of neurotoxins Functional class of neurotoxins Ion channel blocker subclasses Web Server: http://www.imtech.res.in/raghava/ntxpred/ Research Paper Title: Prediction of neurotoxins based on their function and source Authors:Sudipto Saha and Gajendra P. S. Raghava Journal: In Silico Biology (2007) DOI: https://doi.org/10.3233/ISB-2007-7104 https://github.com/Piyushh1104/NTXpred.git Background Neurotoxins are toxic proteins that affect the nervous system by blocking nerve impulses and interfering with ion channels or neurotransmitter release. Major biological sources include: Eubacteria Cnidaria Mollusca Arthropoda Chordata Neurotoxins are important for: Drug discovery Pain research Epilepsy therapeutics Ion channel studies Functional proteomics Dataset Information The dataset was collected from Swiss-Prot/Tox-Prot databases. Initial Dataset 932 experimentally validated neurotoxin proteins Final Non-Redundant Dataset 582 neurotoxin sequences Redundancy reduction was performed using PROSET software with 90% sequence identity cutoff.