Bioreceptor Screening Using Molecular Dynamics and ANN for Biosensors

The patent creates computational copies (virtual models) of bioreceptors and analytes to simulate their interactions. Instead of physically testing numerous bioreceptor candidates through expensive and time-consuming wet lab experiments, the system uses molecular dynamics simulations to generate virtual representations that replicate real-world molecular behavior, allowing rapid screening and selection of promising candidates before experimental validation.

The patent replaces mechanical/manual experimental procedures with computational algorithms. The molecular dynamics simulation engine substitutes for physical experimentation, using mathematical models to predict molecular interactions, binding affinities, and structural stability. This computational approach eliminates the need for iterative wet lab experiments while maintaining scientific rigor through physics-based force fields and statistical mechanics.

The patent segments the complex simulation process into distinct computational stages: energy minimization to remove steric clashes, equilibrium dynamics to establish stable configurations, and production simulations to gather statistical data. This segmentation allows each stage to be optimized independently and enables parallel processing of multiple bioreceptor candidates, reducing overall computational burden while maintaining atomic-level precision in interaction analysis.

The patent performs preliminary energy minimization and equilibration simulations before conducting production MD simulations. This preliminary action prepares the systems by removing unrealistic atomic configurations and establishing thermodynamic equilibrium, ensuring that subsequent production simulations start from physically meaningful states. This prevents wasted computational resources on simulations of unstable or artifact-prone configurations.

The patent applies partial action by simulating only the essential components needed for accurate binding affinity calculation. Instead of modeling the entire cellular environment, the system focuses on the bioreceptor-analyte complex with a simplified explicit solvent model (water molecules and essential ions). This selective approach captures the critical solvation effects on binding while omitting computationally expensive details that contribute minimally to binding affinity predictions.

The patent employs periodic boundary conditions in the molecular dynamics simulations, where the simulation box repeats infinitely in all directions. This allows the system to simulate bulk solvent behavior with a finite number of water molecules, as molecules exiting one side of the box reappear on the opposite side. This periodic action maintains accurate solvation environments and binding affinity calculations while dramatically reducing the total number of solvent particles that would otherwise be required.