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Profile-QSAR and Surrogate AutoShim Protein-Family Modeling of Proteases

Martin, Eric and Mukherjee, Prasenjit and Sirockin, Finton (2008) Profile-QSAR and Surrogate AutoShim Protein-Family Modeling of Proteases. J Chem Inf Model. 2008 Apr;48(4):873-81. doi: 10.1021/ci700455u..

Abstract

The 2D Profile-QSAR and 3D Surrogate AutoShim protein-family virtual screening methods were originally developed for kinases. They are the key components of an iterative medium-throughput screening alternative to expensive and time-consuming experimental high-throughput screening. Encouraged by the success with kinases, the S1-serine proteases were selected as a second protein family to tackle, based on the structural and SAR similarity among them, availability of structural and bioactivity data, and the current and future small-molecule drug discovery interest. Validation studies on 24 S1-serine protease assay datasets from 16 unique proteases gave positive results. Profile-QSAR gave a median R2ext = 0.60 for 24 assay datasets, and pairwise selectivity modeling on 60 protease pairs gave a median R2ext = 0.64, comparable to the performance for kinases. A 17-structure universal ensemble S1-serine protease surrogate receptor for Autoshim was developed from a collection of ~1500 X-ray structures. The predictive performance on 24 S1-serine protease assays was good, with a median R2ext = 0.41, but lower than was obtained for kinases. Analysis showed that the higher structural diversity of the protease structures, as well as lower dataset volume and fewer potent compounds, both contributed to the decreased predictive power. In a prospective virtual screening application, 32 compounds were selected from a 1.5 million archive and tested in a biochemical assay. 13 of the 32 compounds were active at IC50 ≤ 10 M, a 41% hit-rate. Three new scaffolds were identified which are being followed up with testing of additional analogues. A SAR similarity analysis for this target against 13 other proteases also indicated two potential protease targets which were positively and negatively correlated with the activity of the target protease.

Item Type: Article
Keywords: AutoShim, Profile-QSAR, Protease, virtual screening, in silico screen,
Date Deposited: 26 Apr 2016 23:46
Last Modified: 26 Apr 2016 23:46
URI: https://oak.novartis.com/id/eprint/7624

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