investigation of the features of the network architecture can shed light on the dynamics and
efficacy of allosteric control and open the way to a completely new avenue of therapeutic
intervention. The general paradigm of proteins as “self-organizing” machines is the “red
line,” unifying all the different chapters of the book.
In Chapter 1, the authors put into an historical perspective the problem of allostery and
demonstrate how this issue constitutes the basic issue to give a scientific foundation to
biology freeing the life science to invoke “Maxwell demons” to get rid of the otherwise
impossible to understand extreme specificity of cell metabolism.
Chapter 2 has a methodological/computational flavor focusing on the necessary link
between allostery and network formalism.
Guang Hu in Chapter 3 presents a rigorous way to “dynamize” structural network by
considering their links as springs, and this modeling choice allows to simulate the allosteric
behavior of the protein molecules.
Chapter 4 goes in depth into the energetic features of allostery. The authors are able to
establish a link between the presence of oscillating modes traversing the structure and the
underlying network wiring, thus giving a physically motivated picture of allosteric process.
Adnan Sljoka, in Chapter 5, proposes a mechanical perspective for the elucidation of the
“second secret of life” (a suggestive but very well-motivated definition of allostery) in terms
of rigidity perturbation.
Chapter 6 (apparently) deals with another theme that is the nature of protein–protein
interaction, and this issue asks for the consideration of cooperative effects that are at the very
basis of any kind of signal transduction across protein structures.
The convergence between protein–protein interaction and allostery is clarified in
Chapter 7. Both allostery and protein–protein interaction rely on the shared need of contact
network rewiring that is at the very basis of any motion of the “protein machines.”
Chapter 8 is a reprise of the methodological line of reasoning of Chapter 2, going in
depth into the presence of “sub-networks” (domains) of global contact network and
introducing the crucial issue of “assortativity” that generates that breaks the symmetry of
contacts distribution creating “specialized spatial patches” in protein territory.
The “symmetry breaking” introduced by Lesieur and Vuillon in Chapter 8 is further
analyzed in Chapter 9, describing a method that combines the information on the correlated
protein motions resulting from atomistic MD simulations with a network analysis based on
graph partitioning into mutually exclusive groups, named communities.
Chapter 10 introduces a software suite designed to analyze molecular dynamics and
structural ensembles in a network perspective allowing to conjugate the three main dimensions of protein science: dynamical, structural, and chemical, allowing the different classes of
intra- and intermolecular interactions to be represented, combined, or alone in the form of
interaction graphs starting from molecular dynamics trajectories.
Chapter 11 faces the most paradigmatic case of interaction specificity in biomedicine:
the antigen–antibody recognition in terms of allostery allowing the reader to grasp the
fundamental role of this phenomenon in life sciences.
The “action at distance” by the transduction of signal across an organized network
structure is both the theme of Chapter 12 and the fundamental “recipe” of living entities at
the molecular level.
The central position of allosteric-like signal transduction is the focus of Chapter 13,
dealing with the probably most famous (and studied) hub protein. P53 located at the crossroad of cell cycle regulation, genome integrity, and cancer development. Elena Papaleo in
vi
Preface
efficacy of allosteric control and open the way to a completely new avenue of therapeutic
intervention. The general paradigm of proteins as “self-organizing” machines is the “red
line,” unifying all the different chapters of the book.
In Chapter 1, the authors put into an historical perspective the problem of allostery and
demonstrate how this issue constitutes the basic issue to give a scientific foundation to
biology freeing the life science to invoke “Maxwell demons” to get rid of the otherwise
impossible to understand extreme specificity of cell metabolism.
Chapter 2 has a methodological/computational flavor focusing on the necessary link
between allostery and network formalism.
Guang Hu in Chapter 3 presents a rigorous way to “dynamize” structural network by
considering their links as springs, and this modeling choice allows to simulate the allosteric
behavior of the protein molecules.
Chapter 4 goes in depth into the energetic features of allostery. The authors are able to
establish a link between the presence of oscillating modes traversing the structure and the
underlying network wiring, thus giving a physically motivated picture of allosteric process.
Adnan Sljoka, in Chapter 5, proposes a mechanical perspective for the elucidation of the
“second secret of life” (a suggestive but very well-motivated definition of allostery) in terms
of rigidity perturbation.
Chapter 6 (apparently) deals with another theme that is the nature of protein–protein
interaction, and this issue asks for the consideration of cooperative effects that are at the very
basis of any kind of signal transduction across protein structures.
The convergence between protein–protein interaction and allostery is clarified in
Chapter 7. Both allostery and protein–protein interaction rely on the shared need of contact
network rewiring that is at the very basis of any motion of the “protein machines.”
Chapter 8 is a reprise of the methodological line of reasoning of Chapter 2, going in
depth into the presence of “sub-networks” (domains) of global contact network and
introducing the crucial issue of “assortativity” that generates that breaks the symmetry of
contacts distribution creating “specialized spatial patches” in protein territory.
The “symmetry breaking” introduced by Lesieur and Vuillon in Chapter 8 is further
analyzed in Chapter 9, describing a method that combines the information on the correlated
protein motions resulting from atomistic MD simulations with a network analysis based on
graph partitioning into mutually exclusive groups, named communities.
Chapter 10 introduces a software suite designed to analyze molecular dynamics and
structural ensembles in a network perspective allowing to conjugate the three main dimensions of protein science: dynamical, structural, and chemical, allowing the different classes of
intra- and intermolecular interactions to be represented, combined, or alone in the form of
interaction graphs starting from molecular dynamics trajectories.
Chapter 11 faces the most paradigmatic case of interaction specificity in biomedicine:
the antigen–antibody recognition in terms of allostery allowing the reader to grasp the
fundamental role of this phenomenon in life sciences.
The “action at distance” by the transduction of signal across an organized network
structure is both the theme of Chapter 12 and the fundamental “recipe” of living entities at
the molecular level.
The central position of allosteric-like signal transduction is the focus of Chapter 13,
dealing with the probably most famous (and studied) hub protein. P53 located at the crossroad of cell cycle regulation, genome integrity, and cancer development. Elena Papaleo in
vi
Preface