High-Throughput Virtual Screening of Protein-Catalyzed Capture Agents for Novel Hydrogel-Nanoparticle Fentanyl Sensors

Fast, portable, and reliable detection of chemical and
biological
compounds is an important challenge in many safety and healthcare
applications. Chemical sensors based on photonic crystals that use
protein-catalyzed capture (PCC) agents as molecular sensors are promising
tools for the portable detection of chemical and biological compounds.
We present the development and deployment of a high-throughput virtual
screening protocol to computationally identify PCC candidates that
maximize the binding sensitivity and selectivity for fentanyl. The
approach integrates enhanced sampling molecular dynamics free-energy
calculations, Gaussian process regression surrogate models, and Bayesian
optimization to efficiently navigate the design space of over 1 million
PCC candidates, resolve the sensitivity–selectivity Pareto
frontier, and identify the top-performing PCC candidates. We analyze
the molecular interactions between our top candidates and fentanyl
target to propose design rules for high-performance PCC agents to
be used for experimental testing and, ultimately, incorporation into
next-generation hydrogel–nanoparticle-based chemical sensing
devices.