2. The betweenness centrality computation requires purposed
algorithms; Brandes’ algorithm is the most applied [32] and
its version for Matlab, Java, and Python environments is available for free on web;
3. The clustering procedure is by far the most burdening part of
the whole algorithm and relies on the solution for the eigenvalues problem; it is also a crucial step to define proper data
structure to keep all useful information about clusters nodes.
Writing an efficient algorithm for this part will strongly affect
the whole program speed (shifting from many minutes to
seconds);
4. When computing ΔP, it is necessary to verify that the apo (not
bound) and holo (bound) forms are resolved with the same
number of residues; in any case, it is advisable to verify their
alignment through purposed software (see for instance, SuperPose http://wishart.biology.ualberta.ca/SuperPose/);
5. To create the ribbon maps, it is necessary to modify the PDB
files, by replacing the B-factors in the ATOM section with the
value of interest (i.e., node degree). To simplify the procedure,
it is advisable to implement the whole algorithm in the same
language of the molecular visualization system (Python for
PyMol and Java for Jmol, for instance).
References
1. Di Paola L, Giuliani A (2015) Protein contact
network topology: a natural language for allostery. Curr Opin Struct Biol 31:43–48.
https://doi.org/10.1016/j.sbi.2015.03.001
2. Tsai CJ, del Sol A, Nussinov R (2009) Protein
allostery, signal transmission and dynamics: a
classification scheme of allosteric mechanisms.
Mol BioSyst 5:207–216
3. De Ruvo M, Giuliani A, Paci P et al (2012)
Shedding light on protein-ligand binding by
graph theory: the topological nature of allostery. Biophys Chem 165–166:21–29.
https://doi.org/10.1016/j.bpc.2012.03.001
4. Giuliani A, Filippi S, Bertolaso M (2014) Why
network approach can promote a new way of
thinking in biology. Front Genet. https://doi.
org/10.3389/fgene.2014.00083
5. Watts DJ, Strogatz SH (1998) Collective
dynamics of “small-world” networks. Nature
393:440–442
6. Di Paola L, De Ruvo M, Paci P et al (2013)
Protein contact networks: an emerging paradigm
in
chemistry.
Chem
Rev
113:1598–1613. https://doi.org/10.1021/
cr3002356
7. Berman H, Westbrook J, Feng Z et al (2000)
The protein data bank. Nucleic Acids Res
28:235–242
8. Liu T, Lin Y, Wen X et al (2007) BindingDB: a
web-accessible database of experimentally
determined protein-ligand binding affinities.
Nucleic Acids Res 35:198–201
9. Wang R, Fang X, Lu Y, Wang S (2004) The
PDBbind database: collection of binding affinities for protein-ligand complexes with known
three-dimensional structures. J Med Chem
47:2977–2980
10. Yang J, Roy A, Zhang Y (2013) BioLiP: a semimanually curated database for biologically relevant ligand-protein interactions. Nucleic Acids
Res 41:1096–1103
11. De Ruvo M, Di Paola L, Giuliani A et al (2012)
Shedding light on protein–ligand binding by
graph theory: the topological nature of allostery. Biophys Chem 165–166:21–29.
https://doi.org/10.1016/j.bpc.2012.03.001
12. Deo N, Pang C (1984) Shortest-path algorithms: taxonomy and annotation. Networks
14:275–323. https://doi.org/10.1002/net.
3230140208
Disclosing Allostery Through Protein Contact Networks
19
algorithms; Brandes’ algorithm is the most applied [32] and
its version for Matlab, Java, and Python environments is available for free on web;
3. The clustering procedure is by far the most burdening part of
the whole algorithm and relies on the solution for the eigenvalues problem; it is also a crucial step to define proper data
structure to keep all useful information about clusters nodes.
Writing an efficient algorithm for this part will strongly affect
the whole program speed (shifting from many minutes to
seconds);
4. When computing ΔP, it is necessary to verify that the apo (not
bound) and holo (bound) forms are resolved with the same
number of residues; in any case, it is advisable to verify their
alignment through purposed software (see for instance, SuperPose http://wishart.biology.ualberta.ca/SuperPose/);
5. To create the ribbon maps, it is necessary to modify the PDB
files, by replacing the B-factors in the ATOM section with the
value of interest (i.e., node degree). To simplify the procedure,
it is advisable to implement the whole algorithm in the same
language of the molecular visualization system (Python for
PyMol and Java for Jmol, for instance).
References
1. Di Paola L, Giuliani A (2015) Protein contact
network topology: a natural language for allostery. Curr Opin Struct Biol 31:43–48.
https://doi.org/10.1016/j.sbi.2015.03.001
2. Tsai CJ, del Sol A, Nussinov R (2009) Protein
allostery, signal transmission and dynamics: a
classification scheme of allosteric mechanisms.
Mol BioSyst 5:207–216
3. De Ruvo M, Giuliani A, Paci P et al (2012)
Shedding light on protein-ligand binding by
graph theory: the topological nature of allostery. Biophys Chem 165–166:21–29.
https://doi.org/10.1016/j.bpc.2012.03.001
4. Giuliani A, Filippi S, Bertolaso M (2014) Why
network approach can promote a new way of
thinking in biology. Front Genet. https://doi.
org/10.3389/fgene.2014.00083
5. Watts DJ, Strogatz SH (1998) Collective
dynamics of “small-world” networks. Nature
393:440–442
6. Di Paola L, De Ruvo M, Paci P et al (2013)
Protein contact networks: an emerging paradigm
in
chemistry.
Chem
Rev
113:1598–1613. https://doi.org/10.1021/
cr3002356
7. Berman H, Westbrook J, Feng Z et al (2000)
The protein data bank. Nucleic Acids Res
28:235–242
8. Liu T, Lin Y, Wen X et al (2007) BindingDB: a
web-accessible database of experimentally
determined protein-ligand binding affinities.
Nucleic Acids Res 35:198–201
9. Wang R, Fang X, Lu Y, Wang S (2004) The
PDBbind database: collection of binding affinities for protein-ligand complexes with known
three-dimensional structures. J Med Chem
47:2977–2980
10. Yang J, Roy A, Zhang Y (2013) BioLiP: a semimanually curated database for biologically relevant ligand-protein interactions. Nucleic Acids
Res 41:1096–1103
11. De Ruvo M, Di Paola L, Giuliani A et al (2012)
Shedding light on protein–ligand binding by
graph theory: the topological nature of allostery. Biophys Chem 165–166:21–29.
https://doi.org/10.1016/j.bpc.2012.03.001
12. Deo N, Pang C (1984) Shortest-path algorithms: taxonomy and annotation. Networks
14:275–323. https://doi.org/10.1002/net.
3230140208
Disclosing Allostery Through Protein Contact Networks
19