FunFOLD statistics

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Citations per year

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

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

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Popular tool citations

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FunFOLD specifications

Information


Unique identifier OMICS_03793
Name FunFOLD
Interface Web user interface
Restrictions to use None
Input data A protein sequence in single letter amino acid code.
Output data A list of putative ligand-binding site residues plus a list of the ligands within the binding site cluster.
Computer skills Basic
Version 2.0
Stability Stable
Maintained Yes

Subtool


  • FunFOLDQA

Maintainers


  • person_outline Liam J. McGuffin
  • person_outline Daniel Roche

Additional information


https://www.reading.ac.uk/bioinf/FunFOLD/FunFOLD_help_2_0.html

Publications for FunFOLD

FunFOLD citations

 (11)
library_books

Normal Modes Expose Active Sites in Enzymes

2016
PLoS Comput Biol
PMCID: 5225006
PMID: 28002427
DOI: 10.1371/journal.pcbi.1005293

[…] developed [–]. Several webservers of ligand binding sites have also been constructed and may be used to infer unknown ligand binding sites based on homology and other attributes such as Pocketome [], FunFold [], scPDB [], IBIS [], Multibind [], fPop [], and FINDSITE []. To date however, no comprehensive study comparing geometry based techniques has been performed.Normal-mode analysis is one of the […]

library_books

Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods

2015
Int J Mol Sci
PMCID: 4691145
PMID: 26694353
DOI: 10.3390/ijms161226202

[…] tional annotation. Furthermore, a number of structure-based methods for the prediction of protein–ligand binding sites have incorporated methods for predicting GO and EC terms, including COACH [] and FunFOLD3 [,,] (See ). However, as these methods build 3D models as part of their prediction pipeline, they are somewhat more computationally intensive than the sequence-only methods. The prediction of […]

library_books

In silico characterization and Molecular modeling of double strand break repair protein MRE11 from Phoenix dactylifera v deglet nour

2015
PMCID: 4635681
PMID: 26541955
DOI: 10.1186/s12976-015-0013-2

[…] sphatases []. One conserved residue in eukaryotic MRE11 proteins, Glu286 (Fig. ), forms H-bonds with HIS253 and stabilizes this histidine. The same active site binding substrates were found using the FunFOLD server [] and the 3DLigandSite server [].Fig. 4Comparing structures of HmsMRE11 (Homo sapiens, PDB : 3T1I) [], PfMRE11 (Pyrococcus furiosus, archaea PDB ID: 1II7, []), Sp MRE11 (Schizosaccharo […]

library_books

Hairpins under tension: RNA versus DNA

2015
Nucleic Acids Res
PMCID: 4787782
PMID: 26323319
DOI: 10.1093/nar/gkv860

[…] olution of these probabilities. To obtain the experimental hysteresis distributions, for each molecule the unfolding and folding forces measured are paired to generate all possible hysteresis values (Funfold − Ffold). The obtained values are weighted according to the number of force cycles actually performed on the molecule, and normalized. More details about the building of the histograms are pre […]

library_books

Molecular Dynamic Simulations Reveal the Structural Determinants of Fatty Acid Binding to Oxy Myoglobin

2015
PLoS One
PMCID: 4451517
PMID: 26030763
DOI: 10.1371/journal.pone.0128496

[…] in Mb is unknown, we sought to computationally predict the ligand-binding site. There are several methods that may be employed, including Q-site Finder [], SiteHound-web [], COACH [], BioLip [], and FunFOLD2 []. Despite their utility, these methods are challenging to apply to predictions in which the comparator proteins are structurally dissimilar and exhibit high sequence divergence. For instanc […]

library_books

Biophysical Properties of Intrinsically Disordered p130Cas Substrate Domain — Implication in Mechanosensing

2014
PLoS Comput Biol
PMCID: 3983058
PMID: 24722239
DOI: 10.1371/journal.pcbi.1003532

[…] ii–iv) other than I27's. Both F unfold (, top side panel) and ΔL (, right side panel) were broadly distributed, ranging from 30 to 120 pN and from 5 to 120 nm, respectively. The unfolding peak force Funfold and contour length change ΔL showed no correlations since no dominant region can be found in . The relationship between Funfold and ΔL as well as their distributions indicate that within those […]


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FunFOLD institution(s)
Laboratoire de genomique et biochimie du metabolisme, Genoscope, Institut de Genomique, Commissariat a l’Energie Atomique et aux Energies Alternatives, Evry, France; UMR 8030 - Genomique Metabolique, Centre National de la Recherche Scientifique, Evry, France; Department de Biologie, Universite d’Evry-Val-d’Essonne, Evry, France; PRES UniverSud Paris, Saint-Aubin, France; School of Biological Sciences, University of Reading, Reading, UK; BioComputing Section, Medical Research Council Harwell, Harwell Oxford, UK; Beamline B23, Diamond Light Source, Didcot, UK
FunFOLD funding source(s)
Supported by Studentship from the University of Reading, MRC Harwell and the Diamond Light Source; the European Union Seventh Framework Programme [FP7/2007-2013] under grant agreement No. [246556].

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