Protein chemical shift perturbations (CSPs), upon ligand binding, can be used to refine the structure of a protein-ligand complex by comparing experimental CSPs with calculated CSPs for any given set of structural coordinates. Herein, we describe a fast and accurate methodology that opens up new opportunities for improving the quality of protein-ligand complexes using nuclear magnetic resonance (NMR)-based approaches by focusing on the effect of the ligand on the protein. The new computational approach, 1H empirical chemical shift perturbation (HECSP), has been developed to rapidly calculate ligand binding-induced 1H CSPs in a protein. Given the dearth of experimental information by which a model could be derived, we employed high-quality density functional theory (DFT) computations using the automated fragmentation quantum mechanics/molecular mechanics approach to derive a database of ligand-induced CSPs on a series of protein-ligand complexes. Overall, the empirical HECSP model yielded correlation coefficients between its predicted and DFT-computed values of 0.897 (1HA), 0.971 (1HN), and 0.945 (side chain 1H) with root-mean-square errors of 0.151 (1HA), 0.199 (1HN), and 0.257 ppm (side chain 1H), respectively. Using the HECSP model, we developed a scoring function (NMRScore_P). We describe two applications of NMRScore_P on two complex systems and demonstrate that the method can distinguish native ligand poses from decoys and refine protein-ligand complex structures. We provide further refined models for both complexes, which satisfy the observed 1H CSPs in experiments. In conclusion, HECSP coupled with NMRScore_P provides an accurate and rapid platform by which protein-ligand complexes can be refined using NMR-derived information.