Limits...
PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs.

Ito J, Ikeda K, Yamada K, Mizuguchi K, Tomii K - Nucleic Acids Res. (2014)

Bottom Line: This enlargement of the database is expected to enhance opportunities for biological and pharmaceutical applications, such as predictions of new functions and drug discovery.Furthermore, PoSSuMds enables users to explore the binding pocket universe within PoSSuM.Additionally, we have improved the web interface with new functions, including sortable tables and a viewer for visualizing and downloading superimposed pockets.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Bioinformatics, National Institute of Biomedical Innovation (NIBIO), 7-6-8 Saito-Asagi, Ibaraki, Osaka 567-0085, Japan Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan k-tomii@aist.go.jp.

Show MeSH

Related in: MedlinePlus

Captured images related to ligand diversity when the query compound was set to imatinib (HET: STI). The top 50 ligands, which are ranked by the number of binding pockets, are shown in the bar plot (A). Chemical similarities between the ligands are shown in Heatmaps (B) and in a Network view (C).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4383952&req=5

Figure 3: Captured images related to ligand diversity when the query compound was set to imatinib (HET: STI). The top 50 ligands, which are ranked by the number of binding pockets, are shown in the bar plot (A). Chemical similarities between the ligands are shown in Heatmaps (B) and in a Network view (C).

Mentions: The variety of the retrieved ligands is shown in the second section. At the top of this section, the distribution of the retrieved ligands is displayed in a bar plot (Figure 3A). Chemical similarities among the ligands can be viewed as heatmaps (Figure 3B), where darker colors represent higher JI values. The relationships can also be visualized as a network (Figure 3C), where a ligand is denoted by a node and the chemical similarity is represented by an edge. This type of visualization is expected to be useful for understanding the distribution of ligand analogs that bind to structurally similar pockets. In the case of imatinib (HET: STI), an example of a typical kinase inhibitor, the chemical similarities to natural ligands, metabolites (e.g. ATP, ADP and AMP) and to other inhibitors such as dasatinib (HET: 1N1) and sunitinib (HET: B49), are apparent in the network view. Furthermore, up to 50 of the top ligands, in descending order of the number of binding pockets, are shown in the table at the end of this section. All the other ligands can also be downloaded at the end of this table.


PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs.

Ito J, Ikeda K, Yamada K, Mizuguchi K, Tomii K - Nucleic Acids Res. (2014)

Captured images related to ligand diversity when the query compound was set to imatinib (HET: STI). The top 50 ligands, which are ranked by the number of binding pockets, are shown in the bar plot (A). Chemical similarities between the ligands are shown in Heatmaps (B) and in a Network view (C).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383952&req=5

Figure 3: Captured images related to ligand diversity when the query compound was set to imatinib (HET: STI). The top 50 ligands, which are ranked by the number of binding pockets, are shown in the bar plot (A). Chemical similarities between the ligands are shown in Heatmaps (B) and in a Network view (C).
Mentions: The variety of the retrieved ligands is shown in the second section. At the top of this section, the distribution of the retrieved ligands is displayed in a bar plot (Figure 3A). Chemical similarities among the ligands can be viewed as heatmaps (Figure 3B), where darker colors represent higher JI values. The relationships can also be visualized as a network (Figure 3C), where a ligand is denoted by a node and the chemical similarity is represented by an edge. This type of visualization is expected to be useful for understanding the distribution of ligand analogs that bind to structurally similar pockets. In the case of imatinib (HET: STI), an example of a typical kinase inhibitor, the chemical similarities to natural ligands, metabolites (e.g. ATP, ADP and AMP) and to other inhibitors such as dasatinib (HET: 1N1) and sunitinib (HET: B49), are apparent in the network view. Furthermore, up to 50 of the top ligands, in descending order of the number of binding pockets, are shown in the table at the end of this section. All the other ligands can also be downloaded at the end of this table.

Bottom Line: This enlargement of the database is expected to enhance opportunities for biological and pharmaceutical applications, such as predictions of new functions and drug discovery.Furthermore, PoSSuMds enables users to explore the binding pocket universe within PoSSuM.Additionally, we have improved the web interface with new functions, including sortable tables and a viewer for visualizing and downloading superimposed pockets.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Bioinformatics, National Institute of Biomedical Innovation (NIBIO), 7-6-8 Saito-Asagi, Ibaraki, Osaka 567-0085, Japan Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan k-tomii@aist.go.jp.

Show MeSH
Related in: MedlinePlus