Multivalent linkers mediated ultra-sensitive bio-detection

Abstract

In biosensing and diagnostic applications, a key objective is to design detection systems capable of identifying targets at very low concentrations, i.e., achieving high sensitivity. Here, we propose a linker-mediated detection scheme in which the presence of multivalent target molecules (linkers) facilitates the adsorption of ligand-coated guest nanoparticles onto a receptor-coated host substrate. Through a combination of computer simulations and mean-field theory, we demonstrate that, at fixed overall binding strength, increasing the valency of linkers exponentially lowers the concentration threshold for detection. This counterintuitive behavior arises from the combinatorial entropy associated with multivalent binding configurations, which tremendously amplifies the adsorption sensitivity and enables the identification of targets at extremely low concentrations. Our findings highlight multivalency engineering of linkers as a powerful strategy to substantially enhance the sensitivity of biodetection systems.

Figures (3)

• Figure 1: Multivalent linker-mediated adsorption of guest particles. (a) Schematic illustration of the multivalent linker-mediated interaction between guest nanoparticles and the host substrate. Guest particles that form bridges to the substrate via linkers are considered in the adsorbed state, while those without such bridges are in the desorbed state. (b) Schematic of the GCMC simulation setup. Black dots represent immobile receptors randomly distributed on the substrate. Large gray circles indicate guest particles, each of which can interact only with receptors located within its own shaded region via linkers.
• Figure 2: $\rho$-dependent superselectivity and ultra-sensitivity. Here, $\kappa \beta f_l=\kappa \beta f_r=-5$, $n_l=\langle n_r \rangle=10$, $\beta f_{\rm cnf}=2$, and $z_g=10^{-5}$. The symbols are simulation results, and the solid curves are the theoretical prediction (Eq. \ref{['theory_pred']}). (a) The adsorption probability $\theta$ as a function of $\mathrm{log} \rho$ under different valencies of linkers. The dashed lines indicate the low-concentration and high-concentration limits of $\theta$sup_info. (b) The selectivity $\alpha_\rho$ to linker concentration as a function of $\mathrm{log} \rho$ under different valencies from theoretical prediction sup_info. (c) The maximal and minimal selectivity $(\alpha_\rho)_{\mathrm{max/min}}$ as a function of linker valency $\kappa$ from theoretical prediction. The dashed lines are guides of eyes where the curves converge to (d) Log of the adsorption and desorption $\mathrm{log} \rho_{\rm ad,dp}$ as a function of linker valency $\kappa$. The small triangle shows the converging slope of the desorption curve (Eq. \ref{['slope']}).
• Figure 3: Influence of non-specific binders. Here, $\kappa \beta f_l=\kappa \beta f_r=-5$, $\kappa=3$, $\beta f_m=1$, $\beta f_{\rm cnf}=2$, and $z_g=10^{-5}$. The symbols are simulation results, while the solid curves are the theoretical prediction (Eq. \ref{['theory_pred']}). (a) The adsorption probability $\theta$ as a function of $\log \rho$ for different non-specific binder chemical potential $\mu_m$, where $n_l=\langle n_r \rangle=10$. (b) The adsorption probability $\theta$ as a function of $\log \rho$ under different average receptor numbers $n_r$ with $n_l = 10$ and $\beta \mu_m=3$. (c) The adsorption probability $\theta$ as a function of $\log \rho$ under different nanoparticle valencies $n_l$ with $\langle n_r \rangle = 10$ and $\beta \mu_m=3$.