Aims & Scope: Lipophilicity represents one of the most studied and most frequently used
fundamental physicochemical properties. In the present work, harmony search (HS) algorithm is
suggested to feature selection in quantitative structure-property relationship (QSPR) modeling to
predict lipophilicity of neutral, acidic, basic and amphotheric drugs that were determined by
UHPLC. Harmony search is a music-based metaheuristic optimization algorithm. It was affected by
the observation that the aim of music is to search for a perfect state of harmony.
Materials & Methods: Semi-empirical quantum-chemical calculations at AM1 level were used to
find the optimum 3D geometry of the studied molecules and variant descriptors (1497 descriptors)
were calculated by the Dragon software. The selected descriptors by harmony search algorithm (9
descriptors) were applied for model development using multiple linear regression (MLR). In
comparison with other feature selection methods such as genetic algorithm and simulated annealing,
harmony search algorithm has better results. The root mean square error (RMSE) with and without
leave-one out cross validation (LOOCV) were obtained 0.417 and 0.302, respectively.
Results & Conclusion: The results were compared with those obtained from the genetic algorithm
and simulated annealing methods and it showed that the HS is a helpful tool for feature selection
with fine performance.