Alloscore statistics

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Citations per year

Number of citations per year for the bioinformatics software tool Alloscore
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Tool usage distribution map

This map represents all the scientific publications referring to Alloscore per scientific context
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Associated diseases

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Popular tool citations

chevron_left Protein-ligand docking Allosteric site prediction chevron_right
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Alloscore specifications

Information


Unique identifier OMICS_11089
Name Alloscore
Interface Web user interface
Restrictions to use None
Input data For each job, the user can specify allosteric complexes of interest by uploading a protein in a PDB file and multiple ligands in a Mol2 file.
Input format PDB, MOL2
Output data Alloscore provides the predicted energy terms, binding affinity and interactive 3D representation of each allosteric ligand-protein complex.
Computer skills Basic
Version 1.02
Stability Stable
Maintained Yes

Documentation


Maintainer


  • person_outline Jian Zhang

Publication for Alloscore

Alloscore citation

library_books

Are there physicochemical differences between allosteric and competitive ligands?

2017
PLoS Comput Biol
PMCID: 5699844
PMID: 29125840
DOI: 10.1371/journal.pcbi.1005813

[…] on of allosteric protein-ligand interactions using models developed by Li et al.[] In that study the hydrophobicity, as determined by a hydrophobic matching algorithm, had the highest contribution to Alloscore, which is their metric to predict allosteric interactions. The Monod-Wyman- Changeux model also states that protein-protein or subunit interfaces are frequent allosteric binding sites [], an […]


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Alloscore institution(s)
Department of Pathophysiology, Shanghai Jiao-Tong University School of Medicine, Shanghai, China; Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
Alloscore funding source(s)
This work was funded by National Natural Science Foundation of China (81322046, 81302698).

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