MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641114732 A) filed by Koneru Lakshmaiah Education Foundation on September 24, 2026, for A Computational Feature-Group-Based Ensemble Framework For Protein Hotspot Prediction.
Inventors include Gidugu Slbv Prasanthi; Dr. Ravi Boda; and Chaganti Venu Madhav.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: Title: A Computational Feature-Group-Based Ensemble Framework for Protein Hotspot Prediction The present invention relates to a computer-implemented computational framework for protein hotspot prediction using performance-driven amino acid feature-group selection and ensemble machine learning. The framework receives protein sequence-derived data and extracts multiple amino acid feature groups. The feature groups are comparatively evaluated using multiple predictive models to determine their respective predictive performance. Based on the comparative evaluation, top-performing feature groups are selected for subsequent hotspot prediction. The selected feature groups are provided to multiple machine learning and deep learning models configured to generate individual predictions for protein residues. The prediction outputs generated by the plurality of models are integrated through a voting ensemble mechanism to obtain a final hotspot classification. The framework thereby combines informative feature-group selection with complementary prediction capabilities of multiple models to improve robustness and reliability of protein hotspot prediction. The disclosed computational framework is applicable to protein–protein interaction analysis, protein engineering, therapeutic target identification, and drug discovery.
Disclaimer: Curated by HT Syndication.
