Abstract

Molecula rmodeling of novel anticancer agents for treatment of ovarian carcinoma by utilizing chlorambucil for optimizing properties

Author(s): Ronald Bartzatt

Epithelial ovarian cancer is a lethal and most common malignancy of the female enital area. Although advanced-stage ovarian cancer is responsive to multiple cytotoxic drugs, less that 25 % of these patients are alive and disease free after five years of diagnosis. This clinical reality justifies the origin and examination of new drug designs. This work presents nitrogen mustard alkylating agents developed froman optimized molecular modeling analysis of chlorambucil. Thirteen analogs of chlorambucil are selected to introduce potential anticancer agents that have pharmaceutical properties advantageous for clinical application. Importantmolecular properties such as Log P, polar surface area, formula weight,molecular volume, and violations of the Rule of 5 were determined. For all agents the polar surface area ranged from23.547A2 to 86.788A2. No agent showed violations of the Rule of 5 or had greater than 11 rotatable bonds. There was a wide variance in Log P values which ranged from -0.908 to 4.958. Many agents showed a numerically low polar surface area suitable for bloodbrain barrierpenetration ( 90 A2), but not accompanied by a supporting value of Log P. The broad range in Log P valuesmay enhance the efficacy of these agents for application because of diverse lipid by-layer permeation. With the alkylating nitrogen mustard group these agents possesses an aromatic ring and either an amide or carboxyl substituent. Molecular properties were analyzed by multivariate methods such as cluster analysis, K-means cluster analysis, discriminant analysis, andANOSIM(analysis of similarity) which revealed underlying subtle and clinically important relationships among these analogs.Multiple regression analysis produced a mathematical expression relating various molecular properties and useful in predicting additional novel drug designs analogous to this series.