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Pruned receptor surface models and pharmacophores for three-dimensional database searching
Jeffrey J Sutherland1, Lee A O'Brien, Donald F Weaver
1Departments of Chemistry and Pathology, Queen's University, Kingston, Ontario K7L 3N6, Canada.
Journal of Medicinal Chemistry
|July 9, 2004
Summary
Developing pruned receptor surface models (RSMs) using 3D quantitative structure-activity relationship (QSAR) models improves drug discovery. Pruned RSMs offer a balance between pharmacophore sensitivity and RSM selectivity for identifying potential drug leads.
Area of Science:
- Computational chemistry
- Drug discovery
- Medicinal chemistry
Background:
- Pharmacophores define shared 3D chemical features for molecules active at protein receptors, crucial for 3D database searching.
- Traditional pharmacophore searches lack shape constraints, leading to the identification of compounds ill-suited for active sites.
- Receptor surface models (RSMs) represent active sites but can be overconstraining in database searches.
Purpose of the Study:
- To develop a protocol for creating pruned RSMs using 3D quantitative structure-activity relationship (QSAR) models.
- To evaluate the performance of pharmacophore queries alone, with pruned RSMs, and with unpruned RSMs in database searches.
Main Methods:
- A protocol was developed to generate pruned RSMs informed by 3D QSAR models.
- Searches were conducted on six databases comparing pharmacophore queries with and without pruned/unpruned RSMs.
Main Results:
- Pruned RSMs demonstrated an average selectivity 1.8 times greater than pharmacophore queries, surpassing unpruned RSMs (1.6 times).
- Pruned RSMs successfully retrieved 73% of actives identified by pharmacophores, significantly higher than unpruned RSMs (40%).
Conclusions:
- Pruned RSMs offer a valuable compromise, balancing the high sensitivity of pharmacophores with the enhanced selectivity of unpruned RSMs.
- This approach improves the identification of potential drug lead compounds in virtual screening.