3D-QSAR of PET Agents for Imaging β-Amyloid in Alzheimer's Disease

Abstract

Accumulation of excess senile plaques (β-amyloid, Aβplaques) in the brain is strongly associated with the pathogenesis of Alzheimer’s disease (AD). While there are no definitive treatments available to affect a cure of AD, much recent interest has been given to the development of antiamyloid therapies aimed at halting and reversing Aβ-deposition and, thus, monitoring of the therapeutic efficacy would greatly benefit from methods for the in vivo detection and quantification of Aβ-deposits in the brain. Several groups have reported a series of potential imaging agents for the in vivo imaging of Aβ-plaques with positron emission tomography (PET) or single-photon emission computed tomography (SPECT). However, to our knowledge, no three dimensional structure activity relationship (3D-QSAR) studies on PET ligands have been published so far with the exception of CoMFA/CoMSIA study on serotonin transporter (SERT) ligands, and the aim of the present study was to quantitatively investigate structure-activity relationships (SAR) of PET ligands with regard to the future development of potential new PET radiotracers by using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). In this study, we constructed a 3D-QSAR model with several PET ligands such as ThioT analogues and stilbene derivatives, which could be applied to predict binding affinity of the structurally related compounds against Aβplaques. From the literature, binding affinity data of 62 ThioT derivatives and 11 stilbene derivatives were obtained which were used for model building (Fig. 1). At first, the 73 compounds obtained from the literature were divided into two groups: 63 compounds as training set and the other 10 compounds as test set. The training set was used to build 3D-QSAR models with CoMFA and CoMSIA methods, while the test set was used to validate the 3D-