Alloscore statistics

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Citations per year

Number of citations per year for the bioinformatics software tool Alloscore

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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chevron_left Protein-ligand docking Allosteric site prediction chevron_right
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Alloscore specifications


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



  • person_outline Jian Zhang

Publication for Alloscore

Alloscore citation


Are there physicochemical differences between allosteric and competitive ligands?

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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