Allostery and cooperativity in multimeric proteins: bond-to-bond propensities in ATCase

Abstract

Aspartate carbamoyltransferase (ATCase) is a large dodecameric enzyme with six active sites that exhibits allostery: its catalytic rate is modulated by the binding of various substrates at distal points from the active sites. A recently developed method, bond-to-bond propensity analysis, has proven capable of predicting allosteric sites in a wide range of proteins using an energy-weighted atomistic graph obtained from the protein structure and given knowledge only of the location of the active site. Bond-to-bond propensity establishes if energy fluctuations at given bonds have significant effects on any other bond in the protein, by considering their propagation through the protein graph. In this work, we use bond-to-bond propensity analysis to study different aspects of ATCase activity using three different protein structures and sources of fluctuations. First, we predict key residues and bonds involved in the transition between inactive (T) and active (R) states of ATCase by analysing allosteric substrate binding as a source of energy perturbations in the protein graph. Our computational results also indicate that the effect of multiple allosteric binding is non linear: a switching effect is observed after a particular number and arrangement of substrates is bound suggesting a form of long range communication between the distantly arranged allosteric sites. Second, cooperativity is explored by considering a bisubstrate analogue as the source of energy fluctuations at the active site, also leading to the identification of highly significant residues to the T ↔ R transition that enhance cooperativity across active sites. Finally, the inactive (T) structure is shown to exhibit a strong, non linear communication between the allosteric sites and the interface between catalytic subunits, rather than the active site. Bond-to-bond propensity thus offers an alternative route to explain allosteric and cooperative effects in terms of detailed atomistic changes to individual bonds within the protein, rather than through phenomenological, global thermodynamic arguments.

Allosteric Hotspots in the Main Protease of SARS-CoV-2

“…Once the atomistic graph is constructed, we use Bond-to-bond propensities and Markov transients to complementary explore the connectivity within the proteins when sourced from relevant residues. To achieve this, Bond-to-bond propensity explores the instantaneous strength of communication of a perturbation to every bond in the protein which allows to identify allosteric sites [43] and investigate concepts like cooperativity in multimeric proteins [44]. Markov transients exploit the time evolution of a diffusion process on the atomistic graph to identify groups of atoms which are reached the fastest (i.e.…”

“…[43] and further discussed in Ref. [44], hence we only briefly summarise it here. This edge-space measure examines and exhibits the instantaneous communication of a perturbation at a source towards every bond in the protein.…”

“…It has been shown that Bond-to-bond propensities are capable of successfully predicting allosteric sites in a wide range of proteins without any a priori knowledge other than the active site [43]. Of particular relevance to the homodimeric protease studied here, it has been subsequently used to show how allostery and cooperativity are intertwined in multimeric enzymes such as the well studied aspartate carbamoyltransferase (ATCase) [44]. A complementary methodology, Markov transient analysis, further sheds light on the catalytic aspects of allostery and obtains the pathways implicated in allosteric regulation through the transients of the propagation of a random walker on the node space of the atomistic graph [41].…”

Edge-based formulation of elastic network models

“…More formally, the edge changes are the dual of the node motions [12]. An edge-centric approach has proved highly effective in previous studies of different networks [13][14][15], and indeed the formulation presented need not be restricted to proteins and is general for networks embedded in d-dimensional space. There has been extended discussion in the literature over the use of networks with scalar node variables to model two-and three-dimensional mechanical structures [16].…”

An edge-based formulation of elastic network models

“…More formally, the edge changes are the dual of the node motions [11]. An edge-centric approach has proved highly effective in previous studies of different networks [12][13][14], and indeed the formulation presented need not be restricted to proteins * m.hodges14@imperial.ac.uk † m.barahona@imperial.ac.uk and is general for networks embedded in d dimensional space. There has been extended discussion in the literature over the use of networks with scalar node variables to model 2-and 3-dimensional mechanical structures [15].…”