Allosteric communication in molecular machines via information exchange: what can be learned from dynamical modeling

Abstract

Allosteric regulation is crucial for the operation of protein machines and molecular motors. A major challenge is to characterize and quantify the information exchange underlying allosteric communication between remote functional sites in a protein, and to identify the involved relevant pathways. We review applications of two topical approaches of dynamical protein modeling, a kinetic-based single-molecule stochastic model, which employs information thermodynamics to quantify allosteric interactions, and structure-based coarse-grained modeling to characterize intra-molecular couplings in terms of conformational motions and propagating mechanical strain. Both descriptions resolve the directionality of allosteric responses within a protein, emphasizing the concept of causality as the principal hallmark of protein allostery. We discuss the application of techniques from information thermodynamics to dynamic protein elastic networks and evolutionary designed model structures, and the ramifications for protein allostery.

Keywords: Allosteric regulation; Elastic networks; Information theory; Markov networks; Molecular machines; Stochastic thermodynamics.

Fig. 1

Operations of the enzyme tryptophan synthase. a Schematic operation of tryptophan synthase. The catalytic cycle begins with the enzyme in the state where both sites are empty, and the catalytic subunits are accessible. The substrate IGP binds to the α-subunit and serine to the β-subunit, where it is quickly converted to the serine quinoline intermediate (Q₁). IGP activates the formation of the α-aminoacrylate (A-A) and the enzyme adopts the closed conformation. In the closed state (IGP,A-A), A-A activates the cleavage of IGP to produce G3P and indole. Indole is then channeled to the β-site where it reacts with A-A to give the tryptophan quinoline intermediate (Q₃), which is converted to tryptophan (Aex₂ is the external aldimine of tryptophan in the β-subunit). In the state (G3P,Aex₂), the enzyme opens and the products tryptophan and G3P are released. Thus, the enzyme returns to the initial conformation and is ready to start the next cycle. b Allosteric cross-regulation and channeling in tryptophan synthase. Magenta: transitions blocked in the states A-A, A-A + indole and Q₃ of the β-site. Green (light and dark): blocked in the state empty of the α-site. Light green: enhanced by a factor of 9.7 in the state IGP of the α-site. Blue (light and dark): blocked in the states empty, Q₁, Aex₂ of the β-site. Light blue: enhanced by a factor of 27.7 in the state A-A of the β-site. Red: channeling instantaneously changes the states of both sites. Numbers below the chemical notations will be used in the formulation of the kinetic model for the sake of clarity. c The kinetic Markov network of tryptophan synthase with numerical values of all transition rates, given as labels on the respective arrow, under physiological substrate and product concentrations in units of s^− 1. The states (a,b) are given by numerical values as introduced in b. The toned box corresponds to closed conformational states. All figures reprinted from Loutchko et al. (2017), with the permission of AIP Publishing

Fig. 2

Information flows generated through the mutual measurement of the α- and β-sites in tryptophan synthase in bits per seconds. The figure shows the numerical values of ${\sum }_b{J}_{a,a^{\prime }}^{b,b}ln\left(p\left(b\right|a)/p(b\left|a^{\prime }\right)\right)$ for the α-site and of ${\sum }_a{J}_{a,a}^{b,b^{\prime }}ln\left(p\left(a\right|b)/p(a\left|b^{\prime }\right)\right)$ for the β-site. The cross term I^cross is shown on the yellow fuzzy line. Reprinted from Loutchko et al. (2017), with the permission of AIP Publishing

Fig. 3

Allostery from structure-based modeling. a Evolutionary design of allosteric elastic networks. Starting from a random network (left) evolution gradually changed the network architecture by selecting favorable mutations, until a structure with optimized long-range communication between the ligand-binding pocket and the response site (blue beads) had emerged (right). b Allosteric communication in a designed network was characterized by the propagation of elastic strain. Upon ligand binding to the left pocket, contracting its size, neighboring links become strained first (left). Then, deformations propagate through the interface region and reach the right domain (middle), where eventually links around the response site are loaded with strain and the allosteric pocket opening is generated (right). Bond thickness indicates the strain magnitude and colors distinguish between stretched (blue) and compressed (red) links. c Communication pathways in two designed networks, constructed from the highly strained links. The structure on the left encoded symmetric allostery response (response site closed), while the other implemented asymmetric response (response site opened). d Allosteric communication during functional transition in the myosin V motor domain. By dynamically steering the ATP-binding site conformation from the free to the bound state, the allosterically regulated opening of the actin cleft was reproduced in elastic network simulations (left). The identified communication pathways involved during strain propagation (right) correspond to residue motifs important for chemo-mechanical coupling. All figures are adapted from the original publication (Flechsig 2017)