This study aims to comprehensively understand the functional characteristics and mutational effects of the SARS-CoV-2 spike protein through biological experiments and bioinformatics methods. Using deep mutational scanning (DMS) technology, high-throughput sequencing, and protein reconstruction techniques, we systematically analyzed the impact of S protein mutations on its binding affinity to the ACE2 receptor. The results showed that key mutation sites, such as D614G and N501Y, significantly enhanced the binding affinity of the S protein to ACE2, thereby increasing the virus’s transmissibility and immune evasion capabilities. By utilizing AlphaFold for three-dimensional structure prediction and protein docking simulations, we constructed an adaptive landscape model of the S protein, revealing the adaptive changes of different genotypes. Combining experimental data and computational simulations, this study not only validated the accuracy of model predictions but also provided scientific evidence for monitoring viral mutations and designing future vaccines.