Our methodology encompasses three key components: (i) high-level (HL) single-point calculations, (ii) parameter optimization to reproduce PES profiles, atomic charges and atomic gradients, and (iii) comprehensive validation using the Adaptive String Method (ASM) to determine the minimum free energy path (MFEP). To demonstrate the effectiveness of our approach, we apply this methodology to the GFN2-xTB semiempirical method, selected for its computational efficiency and demonstrated success across various chemical applications. We validate our approach using two enzymatic systems involving hydride transfer reactions: Crotonyl-CoA carboxylase/reductase (CCR) and DHFR. These systems were chosen not only for their biochemical relevance but also for their suitability in demonstrating our methodology's effectiveness in handling mechanistically similar reactions and the degree of transferability of the derived parameters. Figure illustrates the reaction mechanisms for the hydride transfer reaction in CCR, where NADPH transfers a hydride to crotonyl-CoA, forming an enolate intermediate that can either proceed to C2 adduct formation or participate in subsequent carboxylation/protonation steps. CCR is one of the most efficient carboxylases and, because of that, has been used to design artificial CO 2 fixation cycles that hold great potential for biotechnological applications. Hydride transfer is the first catalytic step and has been identified as the rate-limiting step in the reductive carboxylation mechanism. Figure depicts the hydride transfer in DHFR, where a hydride is transferred from the C4 position of NADPH to the C6 position of the substrate 7,8-dihydrofolate to form the product 5,6,7,8-tetrahydrofolate. It is worth mentioning that DHFR has been extensively studied both experimentally and theoretically, serving as a model for fundamental aspects of enzyme function. Thus, these hydride transfer reactions provide an excellent test case for validating our methodology. We begin by detailing our methodology's general workflow, encompassing systematic parametrization strategy, MOO formulation, and computational setup for the selected enzymatic systems. In the results section, we first examine the deficiencies of GFN2-xTB in describing hydride transfer reactions, followed by comprehensive analysis of our parametrization strategy's performance for both CCR and DHFR systems. We validate our approach through extensive QM/MM molecular dynamics (MD) simulations and principal component analysis (PCA), demonstrating both energetic and structural accuracy of the optimized pa-rameters. We conclude with an assessment of our work's implications for improving the accuracy of semiempirical methods in enzymatic simulations.