In a pursuit of combating acquired immunodeficiency syndrome, the targets human immunodeficiency virus (HIV) protease, reverse transcriptase and HIV specific proteins were exhaustively explored. Resistance through mutations in these targets has impeded the further developments in HIV research. HIV-1 integrase (HIV-1 IN) has emerged as a newer target and 3 0 -processing, and strand transfer inhibition has proved potential intervention in HIV replication. In present study, in line with our interests in coumarin derivatives as potential bioactive molecules, 4D-quantitative structure-activity relationship (4D-QSAR) is proposed. Fifty-seven structurally diverse coumarin derivatives were subjected to 4D-QSAR studies. Quantum mechanics-based geometry optimization and molecular dynamics simulation were carried out on individual compound. The conformational ensemble generated for each compound was aligned with most active compound, and Coulombic and Lennard-Jones interaction energy descriptors were computed. After selecting the best variables in MATLAB, partial least square regression (PLS) analysis was carried out on 44 training set and 13 test set compounds. The model with ten latent variables was found best with R 2 calculated = 0.903015, R 2 crossvalidated = 0.599553, R 2 predicted = 0.688525, rootmean-square error (RMSE) calculated = 0.21276, RMSE predicted = 0.371579 and prediction bias = -0.15362. Docking studies were carried out on AutoDock Vina, which were in good agreement with the PLS model, suggesting the importance of few descriptors of Coulombic interaction energy and VWD interactions with VAL79, VAL77, ARG199 and GLU157. These results may be useful in designing more potent HIV-1 IN inhibitors.