MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641112947 A) filed by Dr. B. Vasuki; Dr. Jyoti Ahirwar, Prof-Siptec; P. Devi, Asp-Jkkncp; and N. Mohanapriya, Ap-Jkkncp on September 21, 2026, for Predictive Binding Pharmacophores For Multi Target Cns Modulators.
Inventors include Dr. B. Vasuki; Dr. Jyoti Ahirwar, Prof-Siptec; P. Devi, Asp-Jkkncp; and N. Mohanapriya, Ap-Jkkncp.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The invention integrates artificial intelligence, machine learning-driven molecular modeling, adaptive pharmacophore generation, receptor topology analysis, molecular docking, and dynamic bioactivity prediction mechanisms within a unified therapeutic discovery architecture. The system acquires and processes heterogeneous biochemical, pharmacological, and genomic datasets to generate high-dimensional molecular representations capable of identifying critical ligand-binding motifs and receptor-compatible conformations across multiple CNS-associated targets including dopaminergic, serotonergic, glutamatergic, cholinergic, and GABAergic pathways. A cross-attention interaction learning framework evaluates synergistic receptor interactions and adaptive neural signaling dependencies to improve therapeutic efficacy while minimizing adverse pharmacological effects and off-target interactions. The invention further incorporates blood-brain barrier permeability prediction, toxicity estimation, pharmacokinetic optimization, and polypharmacological assessment for intelligent therapeutic prioritization and safer CNS drug development. An adaptive feedback learning subsystem continuously retrains predictive models using experimental and clinical datasets to improve molecular screening accuracy, scalability, and translational applicability.
Disclaimer: Curated by HT Syndication.
