SMAP-WS statistics

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Citations per year

Number of citations per year for the bioinformatics software tool SMAP-WS

Tool usage distribution map

This map represents all the scientific publications referring to SMAP-WS per scientific context
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Associated diseases


Popular tool citations

chevron_left Protein-ligand docking Adverse drug reactions Drug repositioning chevron_right
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SMAP-WS specifications


Unique identifier OMICS_24609
Alternative name SMAP Web Service
Interface Web user interface, Application programming interface
Restrictions to use None
Input format PDB
Computer skills Advanced
Maintained No




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Publications for SMAP Web Service

SMAP-WS citations


Large scale computational drug repositioning to find treatments for rare diseases

NPJ Syst Biol Appl
PMCID: 5847522
PMID: 29560273
DOI: 10.1038/s41540-018-0050-7

[…] algorithms exploit the fact that proteins with similar pockets tend to have similar functions and recognize similar molecules. For instance, the sequence-order independent profile-profile alignment (SOIPPA) program employs Delaunay tessellation of Cα atoms and geometric potentials to compare binding pockets. Further, SiteAlign measures distances between druggable pockets with cavity fingerprints […]


Large scale detection of drug off targets: hypotheses for drug repurposing and understanding side effects

PMCID: 5408384
PMID: 28449705
DOI: 10.1186/s40360-017-0128-7

[…] . The method was also used to find targets related to observed side-effects for 656 drugs [].There are a number of target-based methods for the detection of binding-site similarities []. Among these, SOIPPA [], CavBase [], eMatchSite [], IsoCleft [, ] and IsoMIF [, ]. Such methods can be used to predict protein function from structure [–], understand promiscuity within a protein family [, ], asses […]


Molecular mechanisms involved in the side effects of fatty acid amide hydrolase inhibitors: a structural phenomics approach to proteome wide cellular off target deconvolution and disease association

NPJ Syst Biol Appl
PMCID: 5516858
PMID: 28725477
DOI: 10.1038/npjsba.2016.23
call_split See protocol

[…] ical properties using Geometric Potential that is robust to conformational variations of protein structure. Second, we align two surfaces using a sequence order independent profile–profile alignment (SOIPPA) algorithm. The sequence order independent profile–profile alignment can detect the most similar binding surface patch, without requiring predefinition of location/boundary of the binding sites […]


Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach

PMCID: 4677596
PMID: 26677339
DOI: 10.2147/AABC.S88522

[…] y and computationally solved 3D structures respectively. The selected protein was searched for any structural identity with the 3D ligand binding site of any human protein structure on the web server SMAP-WS at a cut off value of 30% sequence identity.Moreover, druggability is another important prioritization criterion for therapeutic targets; that is defined as the likelihood of being able to mod […]


Modeling enzyme ligand binding in drug discovery

J Cheminform
PMCID: 4594084
PMID: 26457119
DOI: 10.1186/s13321-015-0096-0

[…] he location and boundary of the query protein ligand binding site. The binding site is then compared against target 3D protein structures using a sequence-order independent profile–profile alignment (SOIPPA) algorithm [] that is able to detect similar binding sites between structurally unrelated proteins. The next step is the superimposition (and subsequent ligand transposition) of the query bindi […]


Combinatorial Clustering of Residue Position Subsets Predicts Inhibitor Affinity across the Human Kinome

PLoS Comput Biol
PMCID: 3675009
PMID: 23754939
DOI: 10.1371/journal.pcbi.1003087

[…] ration of purely structure-based alignments, such as those available in databases like homstrad or even local structure alignments such as those identified by motif/template search algorithms (e.g., soippa , and LabelHash, ). Other sources of annotation labels, including Gene Ontology (GO, ) terms, binding affinity for a given molecule and ligation state can be incorporated as-is with ccorps with […]

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SMAP-WS institution(s)
San Diego Supercomputer Center, University of California San Diego, La Jolla, CA, USA; National Biomedical Computation Resource University of California San Diego, La Jolla, CA, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
SMAP-WS funding source(s)
Supported by National Institutes of Health grant GM078596; and National Center for Research Resources, National Institutes of Health NIH P41RR08605 for the National Biomedical Computation Resource (NBCR).

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