Lipophilicity and Biological Activity Study of Several Caspofungin Antifungal Drugs Using QSAR and Monte Carlo Methods

QSAR investigations of Caspofungin derivatives were conducted using Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Monte Carlo Methods. The obtained results were compared and GA -ANN and ICA-MLR combinations showed the best performance according to their correlation coefficient (R2) and Root Mean Sum Square Errors (RMSE). The most important physicochemical and structural descriptors were presented and discussed. Monte Carlo method revealed that the presence of a double bond with branching, a six -member cycle, the absence of halogens, the presence of sp(2) carbon connected to branching, the presence of Nitrogen and Oxygen atoms, absence of Sulphur and Phosphorus are the most important molecular features. The best Caspofungin derivative was exposed to reaction with Cu, Zn, Fe using B3lyp/6-311g/lanl2dz to investigate the stability of the formed complexes, from which the Zn complex was perceived to be the most stable one. It was concluded that QSAR study and the Monte Carlo method can lead to a more comprehensive understanding of the relation between physicochemical, structural, or theoretical molecular descriptors of drugs to their biological activities and Lipophilicity.