Cellular functions are primarily facilitated by biomolecular interactions with
proteins, and ligand binding synchronizes the function of a protein to the requirements
of its surroundings. Consequences of ligand binding to a protein may range from subtle
perturbations in the side chain conformations in the vicinity of the binding region to
large-scale global conformational changes. Coupling of a change in conformation with
that in activity of a protein is traditionally referred to as allostery. In the recent years,
however, the conventional allostery concept has been challenged to include
perturbations in dynamics of a large number of proteins even in the absence of
detectable changes in their backbone structure. Although it can evidently be suggested
that binding produces a signal which can propagate to distant sites of a protein to
achieve the observed conformational and/or dynamical perturbations, revealing a
detailed mechanism of signal propagation is still an elusive task. In order to elucidate
this mechanism, the following two questions demand to be answered: i) How do
different regions of the protein respond? ii) How does the protein “sense” and transmit
the local perturbation? The former question, being relatively easier to handle, has been
tackled with Normal Mode Analysis (NMA), Elastic Network Models (ENMs), and
statistical analyses of Monte Carlo (MC) and Molecular Dynamics (MD) simulation
trajectories for the last ~30 years in the literature. The latter question, on the other
hand, is currently a hot research topic in research community. Allosteric signals are
generally suggested to propagate through “energy transport channels” (residue
networks, or signaling pathways) formed by bonded and nonbonded contacts of
residues, and experimental methods, such as double-mutant analysis and NMR
relaxation methods, are used to identify residues participating to these intraprotein
signaling pathways. For the last 10-15 years, there has been a tremendous interest in utilizing computational techniques to elucidate allostericity in proteins. While elastic
network models and molecular simulations have continued to be resourceful methods,
the most important novel contributions, presumably, have come from the graph theory,
perturbation methods, and the statistical coupling method. In this chapter of Frontiers in
Computational Chemistry, various computational techniques used to elucidate
allosteric mechanisms in proteins are to be discussed with various examples.
Keywords: Conformational change, Communication pathway, Crystal structure,
Database, Elastic network model, Frequency, Graph theory, Induced fit,
Information theory, Ligand binding, Molecular dynamics, Monte carlo simulation,
Perturbation, Population shift¸ principal component analysis¸ protein dynamics¸
residue network, Signal propagation, Statistical coupling analysis, Web-server.
