HIVP-SAE is based on Chaos Game Representation (CGR) to characterize HIV protease (HIVP) mutant sequences. It is integrated with a supervised autoencoder (SAE) to predict whether a strain of HIV with protease mutations is resistant or susceptible to FDA approved HIVP inhibitors. Herein, we include 5 drugs: indinavir (IDV), saquinavir (SQV), nelfinavir (NFV), amprenavir (APV), and lopinavir (LPV). This tool can thus be used to identify the most effective treatment strategies for patients based on their individual HIVP mutation profiles. The web server is implemented based on the Flask framework, and has also been optimized for friendly use on mobile devices. Concurrently, such CGR and SAE combined approach has been employed as well to model the hemolytic properties of peptides.

Input of HIVP Mutant Sequence(s) in FASTA

Output of Predicted HIVP Susceptibility to Drugs