Literature DB >> 16777448

Finding ligands for G protein-coupled receptors based on the protein-compound affinity matrix.

Yoshifumi Fukunishi1, Satoru Kubota, Haruki Nakamura.   

Abstract

We developed a novel method of identifying new active ligands based on information related to known active compounds using protein-compound docking simulations, even when the tertiary structure of the actual target receptor protein is unknown. This method was used to find ligands of G protein-coupled receptors (GPCRs), i.e., agonists and antagonists of histamine, adrenaline, serotonin and dopamine receptors. The principal component analysis (PCA) method was applied to the protein-compound affinity matrix, which was given by thorough docking calculations between sets of many protein pockets and chemical compounds. The set of protein pockets did not necessary include the target protein. Each compound was depicted as a point in the PCA space. Compounds in a sphere, whose center was set to the known active compound in the multi-dimensional PCA space or to the average position of several known active compounds, were selected as candidate-hit compounds. Our method was found to be effective for finding the ligands of GPCRs based on known native ligands, even when only the soluble protein structures were used in the docking simulations.

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Year:  2006        PMID: 16777448     DOI: 10.1016/j.jmgm.2006.05.001

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  3 in total

1.  A method to enhance the hit ratio by a combination of structure-based drug screening and ligand-based screening.

Authors:  Katsumi Omagari; Daisuke Mitomo; Satoru Kubota; Haruki Nakamura; Yoshifumi Fukunishi
Journal:  Adv Appl Bioinform Chem       Date:  2008-08-12

2.  Quantitative Structure-activity Relationship (QSAR) Models for Docking Score Correction.

Authors:  Yoshifumi Fukunishi; Satoshi Yamasaki; Isao Yasumatsu; Koh Takeuchi; Takashi Kurosawa; Haruki Nakamura
Journal:  Mol Inform       Date:  2016-04-29       Impact factor: 3.353

3.  A similarity search using molecular topological graphs.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  J Biomed Biotechnol       Date:  2009-12-13
  3 in total

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