Bioreceptor Screening with MD and ANN for Substrate-Aware Binding

The patent uses computational models to create virtual copies of bioreceptors and their interactions with analytes. Molecular dynamics simulations generate digital representations that replicate experimental conditions, allowing researchers to screen and evaluate multiple bioreceptor candidates in silico before selecting the most promising candidates for experimental validation. This copying approach maintains reliability while dramatically reducing time and cost.

The patent replaces physical experimental systems with computational mechanical models. Instead of conducting numerous wet-lab experiments to test bioreceptor stability and analyte binding, the system uses molecular dynamics simulations and free energy calculations to predict these properties computationally. This substitution maintains scientific rigor while eliminating the time-consuming and expensive nature of traditional experimental screening.

The patent segments the complex simulation system into distinct functional modules: bioreceptor preparation, substrate modeling, analyte binding simulations, and data analysis. Each module handles specific aspects of the interaction independently, making the overall complex system more manageable. The bioreceptor is prepared separately, the substrate is modeled independently, and their interactions are simulated in controlled stages, reducing the complexity burden while maintaining atomic-level precision.

The patent introduces computational intermediaries such as force fields, potential energy functions, and simulation protocols that mediate between the complex physical reality of biomolecular interactions and the simplified computational models. These intermediaries translate complex atomic-level interactions into manageable computational parameters, allowing precise measurement of binding affinities and structural changes without being overwhelmed by the full complexity of the system.

The patent performs preliminary actions by pre-processing bioreceptor structures, pre-equilibrating solvent environments, and pre-characterizing substrate properties before conducting the main binding simulations. This preliminary preparation reduces the complexity of the subsequent multiparametric analysis by establishing stable baseline conditions. Free energy perturbation calculations are performed in staged sequences, with each stage building on previously established parameters, making the comprehensive analysis more manageable.

The patent systematically changes key parameters such as temperature, pressure, and solvent composition in controlled simulation steps to assess their effects on bioreceptor-analyte binding. By varying one parameter at a time while holding others constant, the method maintains comprehensiveness while reducing analytical complexity. The use of alchemical transformation parameters in free energy calculations allows systematic exploration of different binding states without requiring simultaneous optimization of all parameters.