Ai-enhanced hybrid docking and MD simulation framework for molecular interactions
A high-throughput framework integrating AI-driven hybrid models with molecular dynamics to enhance predictive accuracy of molecular interactions with substrates like hair and skin. Ideal for cosmetic and detergent formulations, this scalable solution accelerates development.
Overview
The AI-enhanced hybrid docking and molecular dynamics (MD) simulation framework is designed to revolutionize the prediction of molecular interactions with complex substrates, such as hair, skin, and textiles, through the integration of AI-driven hybrid models and MD simulations. This innovative solution leverages graph neural networks (GNNs) to enhance predictive accuracy and scalability, providing high-throughput, precise predictions of compound behaviors, including film formation and viscosity changes. This framework is particularly beneficial for developing advanced cosmetic and detergent formulations, offering faster and more accurate results than traditional methods.
Technical specifications
Key features:
- Integration of AI and MD: Combines molecular dynamics with AI-driven hybrid models to improve predictive accuracy of molecular interactions.
- High-throughput capability: Enables rapid screening and prediction of behaviors such as film formation and polymer-surfactant interactions.
- Scalability: Adaptable to a wide range of molecular systems beyond cosmetics and detergents.
- Automated workflow: Utilizes tools like ProteoDockNet for docking and GROMACS for MD simulations, with shell scripting for automation.
- Validation metrics: Employs RMSE and MAE metrics for refining AI algorithms and ensuring robust correlation with experimental data.
Technology readiness level
The framework is currently at Technology Readiness Level 2, indicating that it is in the early stages of concept development. The project includes plans for further validation and optimization through a four-phase process, which will enhance its predictive capabilities and real-world applicability.
About R.V. College of Engineering
RV College of Engineering (RVCE) is an autonomous, self‑financing engineering institution in Bengaluru, affiliated to Visvesvaraya Technological University and accredited NAAC A+. It connects to industry through an active Industry Institute Interaction Cell, 150+ MoUs, and co‑located, industry‑sponsored labs and Centers of Excellence that enable joint training, prototyping, and upskilling on campus. Proximity to Bengaluru’s technology cluster supports internships, capstone co‑supervision, and consultancy engagements throughout the year. Research here is supported by competitive national programs and industry, including DRDO/NRB, AICTE, and ISRO collaborations. An IP Coordination Cell, together with incubation resources and a student‑run Entrepreneurship Development Cell, assists with patenting, licensing, and venture formation.
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