Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity towards other antibiotics, offers novel treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here we address this issue in the Gram-positive pathogen S. pneumoniae by quantifying collateral and fitness effects of a series of clinically relevant first-step (gyrA or parC) mutations, and their combinations, that confer resistance to fluoroquinolones. We integrated these results in a mathematical model which allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC mutations; however, the spectrum of collateral effects was unique for each mutation or mutation pair. This indicated that mutation identity, even different mutations to the same amino acid, can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. In addition, we observed that epistatic effects between gyrA and parC mutations strongly alter the strength of collateral effects against different antibiotics. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic specific pharmacodynamics, revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that the gene, mutational identity, and interactions between resistance mutations can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies.