Allosteric Communication Occurs via Networks of Tertiary and Quaternary Motions in Proteins

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that allosteric communication in proteins relies upon networks of quaternary (collective, rigid-body) and tertiary (residue–residue contact) motions. We argue that cyclic topology of these networks is necessary for allosteric communication. An automated algorithm identifies rigid bodies from the displacement between the inactive and the active structures and constructs “quaternary networks” from these rigid bodies and the substrate and effector ligands. We then integrate quaternary networks with a coarse-grained representation of contact rearrangements to form “global communication networks” (GCNs). The GCN reveals allosteric communication among all substrate and effector sites in 15 of 18 multidomain and multimeric proteins, while tertiary and quaternary networks exhibit such communication in only 4 and 3 of these proteins, respectively. Furthermore, in 7 of the 15 proteins connected by the GCN, 50% or more of the substrate-effector paths via the GCN are “interdependent” paths that do not exist via either the tertiary or the quaternary network. Substrate-effector “pathways” typically are not linear but rather consist of polycyclic networks of rigid bodies and clusters of rearranging residue contacts. These results argue for broad applicability of allosteric communication based on structural changes and demonstrate the utility of the GCN. Global communication networks may inform a variety of experiments on allosteric proteins as well as the design of allostery into non-allosteric proteins

Allo-network drugs: Extension of the allosteric drug concept to protein-protein interaction and signaling networks

Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most intra-protein conformational changes may be dynamically transmitted across protein-protein interaction and signaling networks of the cell. Allo-network drugs influence the pharmacological target protein indirectly using specific inter-protein network pathways. We show that allo-network drugs may have a higher efficiency to change the networks of human cells than those of other organisms, and can be designed to have specific effects on cells in a diseased state. Finally, we summarize possible methods to identify allo-network drug targets and sites, which may develop to a promising new area of systems-based drug design

Mapping energy transport networks in proteins

The response of proteins to chemical reactions or impulsive excitation that occurs within the molecule has fascinated chemists for decades. In recent years ultrafast X-ray studies have provided ever more detailed information about the evolution of protein structural change following ligand photolysis, and time-resolved IR and Raman techniques, e.g., have provided detailed pictures of the nature and rate of energy transport in peptides and proteins, including recent advances in identifying transport through individual amino acids of several heme proteins. Computational tools to locate energy transport pathways in proteins have also been advancing. Energy transport pathways in proteins have since some time been identified by molecular dynamics (MD) simulations, and more recent efforts have focused on the development of coarse graining approaches, some of which have exploited analogies to thermal transport in other molecular materials. With the identification of pathways in proteins and protein complexes, network analysis has been applied to locate residues that control protein dynamics and possibly allostery, where chemical reactions at one binding site mediate reactions at distance sites of the protein. In this chapter we review approaches for locating computationally energy transport networks in proteins. We present background into energy and thermal transport in condensed phase and macromolecules that underlies the approaches we discuss before turning to a description of the approaches themselves. We also illustrate the application of the computational methods for locating energy transport networks and simulating energy dynamics in proteins with several examples

Allostery in Its Many Disguises: From Theory to Applications.

Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts

All-scale structural analysis of biomolecules through dynamical graph partitioning

From femtosecond bond vibrations to millisecond domain motions, the dynamics of biomolecules spans a wide range of time and length scales. This hierarchy of overlapping scales links the molecular and biophysical details to key aspects of their functionality. However, the span of scales combined with their intricate coupling rapidly drives atomic simulation methods to their limits, thereby often resulting in the need for coarse-graining techniques which cannot take full account of the biochemical details. To overcome this tradeoff, a graph-theoretical framework inspired by multiscale community detection methods and stochastic processes is here introduced for the analysis of protein and DNA structures. Using biophysical force fields, we propose a general mapping of the 3D atomic coordinates onto an energy-weighted network that includes the physico-chemical details of interatomic bonds and interactions.Making use of a dynamics-based approach for community detection on networks, optimal partitionings of the structure are identified which are biochemically relevant over different scales. The structural organisation of the biomolecule is shown to be recovered bottom-up over the entire range of chemical, biochemical and biologically meaningful scales, directly from the atomic information of the structure, and without any reparameterisation. This methodology is applied and discussed in five proteins and an ensemble of DNA quadruplexes. In each case, multiple conformations associated with different states of the biomolecule or stages of the underlying catalytic reaction are analysed. Experimental observations are shown to be correctly captured, including the functional domains, regions of the protein with coherent dynamics such as rigid clusters, and the spontaneous closure of some enzymes in the absence of substrate. A computational mutational analysis tool is also derived which identifies both known and new residues with a significant impact on ligand binding. In large multimeric structures, the methodology highlights patterns of long range communication taking place between subunits. In the highly dynamic and polymorphic DNA quadruplexes, key structural features for their physical stability and signatures of their unfolding pathway are identified in the static structure.Open Acces

Computational Studies of Liver Receptor Homolog 1 in the Presence of Small Molecule Agonists: Allosteric Communication and Virtual Screening for New Potential Drug Candidates

Liver Receptor Homolog 1 (LRH-1) is a nuclear receptor whose dysfunction is affiliated with diseases such as diabetes and cancer. Recent investigations demonstrate that higher levels of activation and modulation of its activity can be achieved through its interaction with phospholipids (PLs) and synthetic small molecules. We employed molecular dynamics (MD) simulations to understand more about the structural basis of LRH-1’s activity when bound to small molecule agonist RJW100 as well as the RJW100 derivative 65endo. We find that RJW100 and derivative 65endo can trigger allosteric communication in LRH-1 despite the RJW100 scaffold inducing motions that differ from those induced by PLs. We also provide supporting evidence that a key threonine residue and a water network may be important in RJW100’s ability to activate LRH-1. Finally, in a campaign to identify new LRH-1 lead compounds, virtual screening was performed against RJW100, 65endo, and a second RJW100 derivative, 8AC

Protein Ligand Interactions Probed by NMR: A Dissertation

Molecular recognition, defined as the specific interactions between two or more molecules, is at the center of many biological processes including catalysis, signal transduction, gene regulation and allostery. Allosteric regulation is the modification of function caused by an intermolecular interaction. Allosteric proteins modify their activity in response to a biological signal that is often transmitted through the interaction with a small effector molecule. Therefore, determination of the origins of intermolecular interactions involved in molecular recognition and allostery are essential for understanding biological processes. Classically, molecular recognition and allosteric regulation have been associated to structural changes of the system. NMR spectroscopic methods have indicated that changes in protein dynamics may also contribute to molecular recognition and allostery. This thesis is an investigation of the contributions of both structure and dynamics in molecular binding phenomena. In chapter I, I describe molecular recognition, allostery and examples of allostery and cooperativity. Then I discuss the contribution of protein dynamics to function with a special focus on allosteric regulation. Lastly I introduce the hemoglobin homodimer, HbI of Scapharca inaequivalvis and the mRNA binding protein TIS11d. Chapter II is the primary focus of this thesis on the contribution of protein dynamics to allostery in the dimeric hemoglobin of scapharca inaequivalvis, HbI. Thereafter I concentrate on the mechanism of adenine recognition of the Tristetraprolin-like (TTP) protein TIS11d; this study is detailed in Chapter III. In Chapter IV I discuss broader impacts and future directions of my research. This thesis presents an example of the use of protein NMR spectroscopy to probe ligand binding. The studies presented in this thesis emphasize the importance of dynamics in understanding protein function. Measurements of protein motions will be an element of future studies to understand protein function in health and disease

Exploiting protein flexibility to predict the location of allosteric sites

Background: Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results: By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. Conclusions: We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors