MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202621077800 A) filed by Marathwada Mitra Mandals College Of Engineering on June 24, 2026, for Hybrid Quantum-Classical Computational System For Optimizing Molecular Binding Interactions.
Inventors include Dr. Girija Gireesh Chiddarwar; Bhushan Amol Anokar; Tejas Kiran Manakeshwar; Anuj Arun Dengle; Anvita Anand Kashikar; Esha Mayuresh Ratnaparkh; Dr. Kalpana Sunil Thakre; and Dr. Smita Mahesh Chaudhari.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: ABSTRACT HYBRID QUANTUM-CLASSICAL COMPUTATIONAL SYSTEM FOR OPTIMIZING MOLECULAR BINDING INTERACTIONS The present invention relates to a novel hybrid quantum-classical computational system (100) that leverages quantum reinforcement learning (QRL) for optimizing protein-ligand binding interactions in drug development. The hybrid quantum-classical computational system (100) integrates variational quantum circuits with classical molecular dynamics simulations to enable efficient exploration of chemical space and binding conformations. The system (100) employs quantum state encoding of molecular features, quantum policy networks for action selection, and active learning mechanisms for adaptive sampling.
Disclaimer: Curated by HT Syndication.
