complementarity, interface residue propensity, hydrophobicity of
interface residues, and conformational changes on binding [1].
Networks have been used successfully in understanding the
complex nature of interactions in various disciplines such as biology, engineering, earth sciences, economics, and social sciences. In
this chapter, the primary focus lies on networks of protein structures, and various aspects of network theory related to proteinligand, protein-protein interactions, and its relevance to allostery
are discussed.
To study allostery, the formulation of networks is used extensively. One approach is to build a network of PPIs as done by
Szklarczyk et al. [2]. In such a study, the interest is in finding out
the binding partner(s) of a protein or family of proteins. The role of
evolutionarily conserved residues in PPI and allostery was shown by
Su ¨el and co-workers [3]. Tsai et al. [4] explored how hub proteins
in a PPI network can bind to multiple partners. A broader approach
on the causes behind protein interaction and allostery in
co-localization was taken by Kuriyan and Eisenberg [5]. The
importance of conformational ensembles in understanding allostery is emphasized by Motlagh et al. [6].
Conformational changes or conservation of residues in allostery can be efficiently studied using Protein Structure Networks
(PSNs). Various versions of PSNs such as Protein Contact Networks [7] and Residue Interaction Networks (RINs) [8] are available in literature. Di Paola et al. [9] beautifully capture the utility of
these protein interaction networks. While most of these methods
focus on backbone topology of proteins, emphasis on side-chain
interactions are also given in Protein Side-chain Networks (PScNs)
or Protein Energy Networks (PENs) [10]. PSNs give a bottom-up
(atom-atom contacts to conformational changes and effects on the
binding partners) or top-down (effect of binding partners on atomatom contact redistribution) approach to hone in on the multi-scale
contributions in allostery. A key observation in allostery is that the
conformational changes could span the entire protein structure. It
was reviewed in [10] that such changes can be deconstructed into
allosteric communication pathways. Using known network parameters, such communication pathways can be studied by looking at
optimal paths, their sub-optimal or alternate paths and junction
nodes.
This chapter deals with network methods to study allostery and
PPIs. The basics of network approach and metrics relevant to the
studying of PSNs are provided in Subheadings 2 and 3. The details
and its capability in investigating allostery have been covered extensively in earlier reviews [10–12], and the salient features are summarized here. Recent advances made in these methods [13–15],
weighted networks and their spectral properties capture the influence of small perturbations on the entire system. The technique not
only allows us to quantitatively evaluate the differences but also
90
Vasundhara Gadiyaram et al.
interface residues, and conformational changes on binding [1].
Networks have been used successfully in understanding the
complex nature of interactions in various disciplines such as biology, engineering, earth sciences, economics, and social sciences. In
this chapter, the primary focus lies on networks of protein structures, and various aspects of network theory related to proteinligand, protein-protein interactions, and its relevance to allostery
are discussed.
To study allostery, the formulation of networks is used extensively. One approach is to build a network of PPIs as done by
Szklarczyk et al. [2]. In such a study, the interest is in finding out
the binding partner(s) of a protein or family of proteins. The role of
evolutionarily conserved residues in PPI and allostery was shown by
Su ¨el and co-workers [3]. Tsai et al. [4] explored how hub proteins
in a PPI network can bind to multiple partners. A broader approach
on the causes behind protein interaction and allostery in
co-localization was taken by Kuriyan and Eisenberg [5]. The
importance of conformational ensembles in understanding allostery is emphasized by Motlagh et al. [6].
Conformational changes or conservation of residues in allostery can be efficiently studied using Protein Structure Networks
(PSNs). Various versions of PSNs such as Protein Contact Networks [7] and Residue Interaction Networks (RINs) [8] are available in literature. Di Paola et al. [9] beautifully capture the utility of
these protein interaction networks. While most of these methods
focus on backbone topology of proteins, emphasis on side-chain
interactions are also given in Protein Side-chain Networks (PScNs)
or Protein Energy Networks (PENs) [10]. PSNs give a bottom-up
(atom-atom contacts to conformational changes and effects on the
binding partners) or top-down (effect of binding partners on atomatom contact redistribution) approach to hone in on the multi-scale
contributions in allostery. A key observation in allostery is that the
conformational changes could span the entire protein structure. It
was reviewed in [10] that such changes can be deconstructed into
allosteric communication pathways. Using known network parameters, such communication pathways can be studied by looking at
optimal paths, their sub-optimal or alternate paths and junction
nodes.
This chapter deals with network methods to study allostery and
PPIs. The basics of network approach and metrics relevant to the
studying of PSNs are provided in Subheadings 2 and 3. The details
and its capability in investigating allostery have been covered extensively in earlier reviews [10–12], and the salient features are summarized here. Recent advances made in these methods [13–15],
weighted networks and their spectral properties capture the influence of small perturbations on the entire system. The technique not
only allows us to quantitatively evaluate the differences but also
90
Vasundhara Gadiyaram et al.