Fast modeling of binding affinities by means of superposing significant interaction rules (SSIR) method

2Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties.

Cite

CITATION STYLE

APA

Besalú, E. (2016). Fast modeling of binding affinities by means of superposing significant interaction rules (SSIR) method. International Journal of Molecular Sciences, 17(6). https://doi.org/10.3390/ijms17060827

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free