Corona phase molecular recognition (CoPhMoRe) has been recently introduced as a means of generating synthetic molecular recognition sites on nanoparticle surfaces. A synthetic heteropolymer is adsorbed and confined to the surface of a nanoparticle, forming a corona phase capable of highly selective molecular recognition due to the conformational imposition of the particle surface on the polymer. In this work, we develop a computationally predictive model for analytes adsorbing onto one type of polymer corona phase composed of hydrophobic anchors on hydrophilic loops around a single-walled carbon nanotube (SWCNT) surface using a 2D equation of state that takes into consideration the analyte-polymer, analyte-nanoparticle, and polymer-nanoparticle interactions using parameters determined independently from molecular simulation. The SWCNT curvature is found to contribute weakly to the overall interaction energy, exhibiting no correlation for three of the corona phases considered, and differences of less than 5% and 20% over a larger curvature range for two other corona phases, respectively. Overall, the resulting model for this anchor-loop CoPhMoRe is able to correctly predict 83% of an experimental 374 analyte-polymer library, generating experimental fluorescence responses within 20% error of the experimental values. The modeling framework presented here represents an important step forward in the design of suitable polymers to target specific analytes.