Literature DB >> 17381166

A common reference framework for analyzing/comparing proteins and ligands. Fingerprints for Ligands and Proteins (FLAP): theory and application.

Massimo Baroni1, Gabriele Cruciani, Simone Sciabola, Francesca Perruccio, Jonathan S Mason.   

Abstract

A fast new algorithm (Fingerprints for Ligands And Proteins or FLAP) able to describe small molecules and protein structures using a common reference framework of four-point pharmacophore fingerprints and a molecular-cavity shape is described in detail. The procedure starts by using the GRID force field to calculate molecular interaction fields, which are then used to identify particular target locations where an energetic interaction with small molecular features would be very favorable. The target points thus calculated are then used by FLAP to build all possible four-point pharmacophores present in the given target site. A related approach can be applied to small molecules, using directly the GRID atom types to identify pharmacophoric features, and this complementary description of the target and ligand then leads to several novel applications. FLAP can be used for selectivity studies or similarity analyses in order to compare macromolecules without superposing them. Protein families can be compared and clustered into target classes, without bias from previous knowledge and without requiring protein superposition, alignment, or knowledge-based comparison. FLAP can be used effectively for ligand-based virtual screening and structure-based virtual screening, with the pharmacophore molecular recognition. Finally, the new method can calculate descriptors for chemometric analysis and can initiate a docking procedure. This paper presents the background to the new procedure and includes case studies illustrating several relevant applications of the new approach.

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Year:  2007        PMID: 17381166     DOI: 10.1021/ci600253e

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


  82 in total

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8.  A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction.

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Journal:  BMC Bioinformatics       Date:  2010-04-17       Impact factor: 3.169

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Journal:  Curr Chem Genomics       Date:  2008-11-06

10.  Analysis of HSP90-related folds with MED-SuMo classification approach.

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Journal:  Drug Des Devel Ther       Date:  2009-09-21       Impact factor: 4.162

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