3D QSAR of Pyrrolo Pyrimidine and Thieno Pyrimidines as Human Thymidylate Synthase Inhibitors

K Meena Kumari,L Yamini,M Vijjulatha

doi:10.1155/2012/201937

Abstract

Thymidylate synthase (TS) is a crucial enzyme for DNA biosynthesis and many nonclassical lipophilic antifolates targeting this enzyme are quite efficient and encouraging as antitumor drugs. We report 3D-QSAR analyses on pyrrolo pyrimidine and thieno pyrimidine antifolates to contemplate the mechanism of action and structure-activity relationship of these molecules. By applying leave-one-out (LOO) cross-validation study, cross-validated q2value of 0.523 and 0.566 for CoMFA Ligand based (LB) and Receptor based (RB), 0.516 and 0.471 for CoMSIA LB and RB respectively. while the non-cross-validated r2values were found to be 0.974 and 0.969 for CoMFA LB and RB, 0.983 and 0.972 for CoMSIA LB and RB respectively. The models were graphically interpreted using CoMFA and CoMSIA contour plots. The results obtained from this study were used for rational design of potent inhibitors against thymidylate synthase.

Highlights

Folate metabolism has long been recognised as an attractive target for cancer chemotherapy because of its indispensable role in the biosynthesis of nucleic acid precursors[1,2]
The 3D QSAR – comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) analyses were carried out using pyrrolo pyrimidine and thienopyrimidine derivatives reported as potent Human Thymidylate Synthase inhibitors by Aleem Gangjee et al Molecules with precise IC50 values were selected, a set of 34 molecules were used for derivation of model, these were divided into training set of 27 molecules and test set of 7 molecules
The CoMSIA models showed better results than CoMFA models, this shows that the Hbond donor fields that are not included in the CoMFA model are important for explaining the potency of the molecules

Summary

Introduction

Folate metabolism has long been recognised as an attractive target for cancer chemotherapy because of its indispensable role in the biosynthesis of nucleic acid precursors[1,2]. CoMFA analysis involves the alignment of molecules in a structurally and pharmacologically reasonable manner on the basis of the assumption that each molecule acts via a common macromolecular target binding site In this method, it is possible to predict the biological activity of molecules and represent the relationships between molecular properties (steric and electrostatic) and biological activity in the form of contour maps. In addition to steric and electrostatic fields of CoMFA, CoMSIA defines explicit hydrophobic and hydrogen bond donor and acceptor fields Such 3D QSAR models would be of great help in a drug development program since the activity of new analogues could be quantitatively predicted before attempting their synthesis and testing. To validate the CoMFA and CoMSIA derived models, the predictive ability for the test set of molecules (expressed as r2 pred) was determined by using the following equation: r2pred = (SD – PRESS)/SD. For stronger evaluation of the model applicability on new chemicals, the activities of the new molecules were evaluated using these QSAR models

Results and Discussions

Design of New Inhibitors

Conclusions