Literature DB >> 22657271

SAR matrices: automated extraction of information-rich SAR tables from large compound data sets.

Anne Mai Wassermann1, Peter Haebel, Nils Weskamp, Jürgen Bajorath.   

Abstract

We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

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Year:  2012        PMID: 22657271     DOI: 10.1021/ci300206e

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  14 in total

1.  Systematic mining of analog series with related core structures in multi-target activity space.

Authors:  Disha Gupta-Ostermann; Ye Hu; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2013-08-24       Impact factor: 3.686

2.  Computer-aided drug design at Boehringer Ingelheim.

Authors:  Ingo Muegge; Andreas Bergner; Jan M Kriegl
Journal:  J Comput Aided Mol Des       Date:  2016-09-20       Impact factor: 3.686

3.  Ligand-based approaches to activity prediction for the early stage of structure-activity-relationship progression.

Authors:  Itsuki Maeda; Akinori Sato; Shunsuke Tamura; Tomoyuki Miyao
Journal:  J Comput Aided Mol Des       Date:  2022-03-29       Impact factor: 3.686

4.  Rapid scanning structure-activity relationships in combinatorial data sets: identification of activity switches.

Authors:  José L Medina-Franco; Bruce S Edwards; Clemencia Pinilla; Jon R Appel; Marc A Giulianotti; Radleigh G Santos; Austin B Yongye; Larry A Sklar; Richard A Houghten
Journal:  J Chem Inf Model       Date:  2013-06-07       Impact factor: 4.956

5.  Adapting the DeepSARM approach for dual-target ligand design.

Authors:  Atsushi Yoshimori; Huabin Hu; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2021-03-13       Impact factor: 3.686

6.  Follow-up: Prospective compound design using the 'SAR Matrix' method and matrix-derived conditional probabilities of activity.

Authors:  Disha Gupta-Ostermann; Yoichiro Hirose; Takenao Odagami; Hiroyuki Kouji; Jürgen Bajorath
Journal:  F1000Res       Date:  2015-03-23

Review 7.  Exploring compound promiscuity patterns and multi-target activity spaces.

Authors:  Ye Hu; Disha Gupta-Ostermann; Jürgen Bajorath
Journal:  Comput Struct Biotechnol J       Date:  2014-01-29       Impact factor: 7.271

8.  The 'SAR Matrix' method and its extensions for applications in medicinal chemistry and chemogenomics.

Authors:  Disha Gupta-Ostermann; Jürgen Bajorath
Journal:  F1000Res       Date:  2014-05-16

9.  AnalogExplorer2 - Stereochemistry sensitive graphical analysis of large analog series.

Authors:  Ye Hu; Bijun Zhang; Martin Vogt; Jürgen Bajorath
Journal:  F1000Res       Date:  2015-10-09

10.  Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method.

Authors:  Emili Besalú
Journal:  Int J Mol Sci       Date:  2016-05-26       Impact factor: 5.923

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