Literature DB >> 19364101

APIF: a new interaction fingerprint based on atom pairs and its application to virtual screening.

Violeta I Pérez-Nueno1, Obdulia Rabal, José I Borrell, Jordi Teixidó.   

Abstract

A new interaction fingerprint (IF) called APIF (atom-pairs-based interaction fingerprint) has been developed for postprocessing protein-ligand docking results. Unlike other existing fingerprints which employ absolute locations of individual interactions, APIF considers the relative positions of pairs of interacting atoms. Docking-based virtual screening was performed with GOLD using the crystal structures of trypsin, rhinovirus, HIV protease, carboxypeptidase, and estrogen receptor-alpha as targets. A score derived from the similarity of the bit strings for each docking solution to that of a known reference binding mode was obtained. Comparisons between APIF, GoldScore function, and standard interaction fingerprint (CHIF) scores were performed using enrichment plots. Superior recovery rates were observed in the IF score cases. Comparable results were achieved by using either of the two interaction fingerprints, substantially improving GoldScore function enrichment factors. Binding mode analyses were also carried out in order to study the best method for selecting conformations with a binding mode similar to that of the reference crystallized complex. These showed that the first conformations retrieved by interaction fingerprint scores had a more similar binding mode to the reference complex than those retrieved by the GoldScore function.

Entities:  

Year:  2009        PMID: 19364101     DOI: 10.1021/ci900043r

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


  28 in total

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Journal:  J Comput Chem       Date:  2011-05-03       Impact factor: 3.376

7.  The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

Authors:  Jie Xia; Jui-Hua Hsieh; Huabin Hu; Song Wu; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2017-06-01       Impact factor: 4.956

8.  Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.

Authors:  Jie Xia; Ermias Lemma Tilahun; Terry-Elinor Reid; Liangren Zhang; Xiang Simon Wang
Journal:  Methods       Date:  2014-12-03       Impact factor: 3.608

9.  Characterization of small molecule binding. I. Accurate identification of strong inhibitors in virtual screening.

Authors:  Bo Ding; Jian Wang; Nan Li; Wei Wang
Journal:  J Chem Inf Model       Date:  2013-01-09       Impact factor: 4.956

10.  Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

Authors:  Jui-Hua Hsieh; Shuangye Yin; Xiang S Wang; Shubin Liu; Nikolay V Dokholyan; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2011-12-14       Impact factor: 4.956

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