This study investigates the thermodynamic behavior of molecular self-assembly along biochemical pathways leading to the formation of higher-order complexes. We specifically examine how thermodynamic parameters evolve - such as the dissociation constant [Formula: see text], the entropic contribution [Formula: see text], and the stability parameter of the interaction matrix [Formula: see text] - as molecular complexity increases from monomers to dimers, trimers, and tetramers. A central hypothesis is that stepwise thermodynamic modeling allows prediction of assembly pathways, identification of dead ends points, and the co-directional changes of thermodynamic variables during complex formation which reflect a preference for main biocomplex formation direction. We also introduce a practical rule to classify dead-end intermediates: a pathway step is considered a dead-end if the minimum [Formula: see text] occurs at a non-final intermediate or if [Formula: see text] falls below zero, indicating an entropic barrier. This criterion provides a reproducible way to flag non-viable assembly routes. We apply this analysis to several biologically relevant molecular systems, including the complex of LGP2 bound to an 8-base pair double-stranded RNA molecule, the dimer of VP35 protein interacting with double-stranded RNA and hexamer formations.
Keywords: AI-platform; protein interaction; the order of biocomplex formation; thermodynamic parameters; viral proteins.