Background: Human Immunodeficiency Virus (HIV) is the causative agent of Acquired Immunodeficiency Syndrome (AIDS) that imposes a global health burden. Therefore, HIV therapeutic agents have been discovery and development.
Objective: To construct Quantitative-structure Activity Relationship (QSAR) models of betulinic acid derivatives with anti-HIV activity using Simplified Molecular-Input Line-Entry System (SMILES)- based descriptors.
Methods: A data set of 107 betulinic acid derivatives and their anti-HIV activity was used to develop QSAR models. The SMILES format of the compounds was employed as descriptors for model construction using the CORAL software by means of the Monte Carlo method.
Results: Constructed QSAR models provided good correlation coefficients (R2) and root mean square error (RMSE) with values in the range of 0.5660-0.5890 and 0.963-1.020, respectively, for the training set, R2 value of 0.7206-0.7837 and RMSE as 0.609-1.250, respectively, for the calibration set, and R2 value of 0.6257-0.7748 and RMSE as 0.837-0.995, respectively, for the validation set. The best QSAR model displayed statistical parameters for training set: R2 = 0.5660 and RMSE = 0.963; calibration set: R2 = 0.7273 and RMSE = 0.609, and validation set: R2 = 0.7748 and RMSE = 0.972. In addition, features of the molecular structure that are promoters of the endpoint increase and decrease were defined and discussed. These are the basis for the mechanistic interpretation of the suggested models.
Conclusion: These findings provide useful knowledge for guiding the design of novel compounds with promising anti-HIV activity.