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A 3D-QSAR model based screen for dihydropyridine-like compound library to identify inhibitors of amyloid beta (Aβ) production



Venkatarajan S Mathura*, Nikunj Patel, Corbin Bachmeier, Michael Mullan, Daniel Paris



Roskamp Institute, 2040 Whitfield Avenue, Sarasota, FL 34243, USA.

E-mail*; *Corresponding author

Article Type






Received July 11, 2010; Accepted August 11, 2010; Published September 20, 2010




Abnormal accumulation of amyloid beta peptide (Aβ) is one of the hallmarks of Alzheimer's disease progression. Practical limitations such as cost , poor hit rates and a lack of well characterized targets are a major bottle neck in the in vitro screening of a large number of chemical libraries and profiling them to
identify Aβ inhibitors. We used a limited set of 1,4 dihydropyridine (DHP)-like compounds from our model set (MS) of 24 compounds which inhibit Aβ as a training set and built 3D-QSAR (Three-dimensional Quantitative Structure-Activity Relationship) models using the Phase program (SchrÖdinger, USA). We developed a 3D-QSAR model that showed the best prediction for Aβ inhibition in the test set of compounds and used this model to screen a 1,043 DHP-like small library set of (LS) compounds. We found that our model can effectively predict potent hits at a very high rate and result in significant cost savings when screening larger libraries. We describe here our in silico model building strategy, model selection parameters and the chemical features that are useful for successful screening of DHP and DHP-like chemical libraries for Aß inhibitors.



3D-QSAR, β-amyloid, in silico screening, dihydropyridine, Alzheimer's Disease



Mathura et al. Bioinformation 5(3): 122-127 (2010)

Edited by


P. Kangueane








Biomedical Informatics




This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.