Binding leverage as a molecular basis for allosteric regulation

Allosteric regulation involves conformational transitions or fluctuations between a few closely related states, caused by the binding of effector molecules. We introduce a quantity called binding leverage that measures the ability of a binding site to couple to the intrinsic motions of a protein. We use Monte Carlo simulations to generate potential binding sites and either normal modes or pairs of crystal structures to describe relevant motions. We analyze single catalytic domains and multimeric allosteric enzymes with complex regulation. For the majority of the analyzed proteins, we find that both catalytic and allosteric sites have high binding leverage. Furthermore, our analysis of the catabolite activator protein, which is allosteric without conformational change, shows that its regulation involves other types of motion than those modulated at sites with high binding leverage. Our results point to the importance of incorporating dynamic information when predicting functional sites. Because it is possible to calculate binding leverage from a single crystal structure it can be used for characterizing proteins of unknown function and predicting latent allosteric sites in any protein, with implications for drug design.     

Coupling between global dynamics and signal transduction pathways: a mechanism of allostery for chaperonin GroEL

Despite significant efforts toward understanding the molecular basis of allosteric communication, the mechanisms by which local energetic and conformational changes cooperatively diffuse from ligand-binding sites to distal regions across the 3-dimensional structure of allosteric proteins remain to be established. Recent experimental and theoretical evidence supports the view that allosteric communication is facilitated by the intrinsic ability of the biomolecules to undergo collective changes in structure, triggered by ligand binding. Two groups of studies recently proved to provide insights into such intrinsic, structure-induced effects: elastic network models that permit us to visualize the cooperative changes in conformation that are most readily accessible near native state conditions, and information-theoretic approaches that elucidate the most efficient pathways of signal transmission favored by the overall architecture. Using a combination of these two approaches, we highlight, by way of application to the bacterial chaperonin complex GroEL-GroES, how the most cooperative modes of motion play a role in mediating the propagation of allosteric signals. A functional coupling between the global dynamics sampled under equilibrium conditions and the signal transduction pathways inherently favored by network topology appears to control allosteric effects.     

Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication

Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.     

Quantifying allosteric effects in proteins

In allosteric regulation, protein activity is altered when ligand binding causes changes in the protein conformational distribution. Little is known about which aspects of protein design lead to effective allosteric regulation, however. To increase understanding of the relation between protein structure and allosteric effects, we have developed theoretical tools to quantify the influence of protein-ligand interactions on probability distributions of reaction rates and protein conformations. We define the rate divergence, Dk, and the allosteric potential, Dx, as the Kullback-Leibler divergence between either the reaction-rate distributions or protein conformational distributions with and without the ligand bound. We then define Dx as the change in the conformational distribution of the combined protein/ligand system, derive Dx in the harmonic approximation, and identify contributions from 3 separate terms: the first term, D[stackxomega], results from changes in the eigenvalue spectrum; the second term, D[stackxDeltax], results from changes in the mean conformation; and the third term, Dxv, corresponds to changes in the eigenvectors. Using normal modes analysis, we have calculated these terms for a natural interaction between lysozyme and the ligand tri-N-acetyl-D-glucosamine, and compared them with calculations for a large number of simulated random interactions. The comparison shows that interactions in the known binding-site are associated with large values of Dxv. The results motivate using allosteric potential calculations to predict functional binding sites on proteins, and suggest the possibility that, in Nature, effective ligand interactions occur at intrinsic control points at which binding induces a relatively large change in the protein conformational distribution.     

Allosteric sites can be identified based on the residue–residue interaction energy difference

Allosteric drugs act at a distance to regulate protein functions. They have several advantages over conventional orthosteric drugs, including diverse regulation types and fewer side effects. However, the rational design of allosteric ligands remains a challenge, especially when it comes to the identification allosteric binding sites. As the binding of allosteric ligands may induce changes in the pattern of residue–residue interactions, we calculated the residue–residue interaction energies within the allosteric site based on the molecular mechanics generalized Born surface area energy decomposition scheme. Using a dataset of 17 allosteric proteins with structural data for both the apo and the ligand‐bound state available, we used conformational ensembles generated by molecular dynamics simulations to compute the differences in the residue–residue interaction energies in known allosteric sites from both states. For all the known sites, distinct interaction energy differences (>25%) were observed. We then used CAVITY, a binding site detection program to identify novel putative allosteric sites in the same proteins. This yielded a total of 31 “druggable binding sites,” of which 21 exhibited >25% difference in residue interaction energies, and were hence predicted as novel allosteric sites. Three of the predicted allosteric sites were supported by recent experimental studies. All the predicted sites may serve as novel allosteric sites for allosteric ligand design. Our study provides a computational method for identifying novel allosteric sites for allosteric drug design. Proteins 2015; 83:1375–1384. © 2014 Wiley Periodicals, Inc.     

Using robotics to fold proteins and dock ligands

The problems of protein folding and ligand docking have been explored largely using molecular dynamics or Monte Carlo methods. These methods are very compute intensive because they often explore a much wider range of energies, conformations and time than necessary. In addition, Monte Carlo methods often get trapped in local minima. We initially showed that robotic motion planning permitted one to determine the energy of binding and dissociation of ligands from protein binding sites (Singh et al., 1999). The robotic motion planning method maps complicated three-dimensional conformational states into a much simpler, but higher dimensional space in which conformational rearrangements can be represented as linear paths. The dimensionality of the conformation space is of the same order as the number of degrees of conformational freedom in three-dimensional space. We were able to determine the relative energy of association and dissociation of a ligand to a protein by calculating the energetics of interaction for a few thousand conformational states in the vicinity of the protein and choosing the best path from the roadmap. More recently, we have applied roadmap planning to the problem of protein folding (Apaydin et al., 2002a). We represented multiple conformations of a protein as nodes in a compact graph with the edges representing the probability of moving between neighboring states. Instead of using Monte Carlo simulation to simulate thousands of possible paths through various conformational states, we were able to use Markov methods to calculate the steady state occupancy of each conformation, needing to calculate the energy of each conformation only once. We referred to this Markov method of representing multiple conformations and transitions as stochastic roadmap simulation or SRS. We demonstrated that the distribution of conformational states calculated with exhaustive Monte Carlo simulations asymptotically approached the Markov steady state if the same Boltzman energy distribution was used in both methods. SRS permits one to calculate contributions from all possible paths simultaneously with far fewer energy calculations than Monte Carlo or molecular dynamics methods. The SRS method also permits one to represent multiple unfolded starting states and multiple, near-native, folded states and all possible paths between them simultaneously. The SRS method is also independent of the function used to calculate the energy of the various conformational states. In a paper to be presented at this conference (Apaydin et al., 2002b) we have also applied SRS to ligand docking in which we calculate the dynamics of ligand-protein association and dissociation in the region of various binding sites on a number of proteins. SRS permits us to determine the relative times of association to and dissociation from various catalytic and non-catalytic binding sites on protein surfaces. Instead of just following the best path in a roadmap, we can calculate the contribution of all the possible binding or dissociation paths and their relative probabilities and energies simultaneously.     

Is allostery an intrinsic property of all dynamic proteins?

Allostery involves coupling of conformational changes between two widely separated binding sites. The common view holds that allosteric proteins are symmetric oligomers, with each subunit existing in "at least" two conformational states with a different affinity for ligands. Recent observations such as the allosteric behavior of myoglobin, a classical example of a nonallosteric protein, call into question the existing allosteric dogma. Here we argue that all (nonfibrous) proteins are potentially allosteric. Allostery is a consequence of re-distributions of protein conformational ensembles. In a nonallosteric protein, the binding site shape may not show a concerted second-site change and enzyme kinetics may not reflect an allosteric transition. Nevertheless, appropriate ligands, point mutations, or external conditions may facilitate a population shift, leading a presumably nonallosteric protein to behave allosterically. In principle, practically any potential drug binding to the protein surface can alter the conformational redistribution. The question is its effectiveness in the redistribution of the ensemble, affecting the protein binding sites and its function. Here, we review experimental observations validating this view of protein allostery.     

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein–ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art “fixed backbone” design methods perform poorly on these tests, we develop a new “coupled moves” design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein – ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.     

Construction and optimization of a family of genetically encoded metabolite sensors by semirational protein engineering

A family of genetically-encoded metabolite sensors has been constructed using bacterial periplasmic binding proteins (PBPs) linearly fused to protein fluorophores. The ligand-induced conformational change in a PBP allosterically regulates the relative distance and orientation of a fluorescence resonance energy transfer (FRET)-compatible protein pair. Ligand binding is transduced into a macroscopic FRET observable, providing a reagent for in vitro and in vivo ligand-measurement and visualization. Sensors with a higher FRET signal change are required to expand the dynamic range and allow visualization of subtle analyte changes under high noise conditions. Various observations suggest that factors other than inter-fluorophore separation contribute to FRET transfer efficiency and the resulting ligand-dependent spectral changes. Empirical and rational protein engineering leads to enhanced allosteric linkage between ligand binding and chromophore rearrangement; modifications predicted to decrease chromophore rotational averaging enhance the signal change, emphasizing the importance of the rotational freedom parameter kappa2 to FRET efficiency. Tighter allosteric linkage of the PBP and the fluorophores by linker truncation or by insertion of chromophores into the binding protein at rationally designed sites gave rise to sensors with improved signal change. High-response sensors were obtained with fluorescent proteins attached to the same binding PBP lobe, suggesting that indirect allosteric regulation during the hinge-bending motion is sufficient to give rise to a FRET response. The optimization of sensors for glucose and glutamate, ligands of great clinical interest, provides a general framework for the manipulation of ligand-dependent allosteric signal transduction mechanisms.     

Cooperative Protein Allosteric Transition Mediated by a Fluctuating Transmission Network

Allosteric communication between distant protein sites represents a key mechanism of biomolecular regulation and signal transduction. Compared to other processes such as protein folding, however, the dynamical evolution of allosteric transitions is still not well understood. As an example of allosteric coupling between distant protein regions, we consider the global open-closed motion of the two domains of T4 lysozyme, which is triggered by local motion in the hinge region. Combining extensive molecular dynamics simulations with a correlation analysis of interresidue contacts, we identify a network of interresidue distances that move in a concerted manner. The cooperative process originates from a cogwheel-like motion of the hydrophobic core in the hinge region, which constitutes an evolutionary conserved and flexible transmission network. Through rigid contacts and the protein backbone, the small local changes of the hydrophobic core are passed on to the distant terminal domains and lead to the emergence of a rare global conformational transition. As in an Ising-type model, the cooperativity of the allosteric transition can be explained via the interaction of local fluctuations.     

A principal component analysis of the dynamics of subdomains and binding sites in human serum albumin

The conformational dynamics of human serum albumin (HSA) was investigated by principal component analysis (PCA) applied to three molecular dynamics trajectories of 200 ns each. The overlap of the essential subspaces spanned by the first 10 principal components (PC) of different trajectories was about 0.3 showing that the PCA based on a trajectory length of 200 ns is not completely convergent for this protein. The contributions of the relative motion of subdomains and of the subdomains (internal) distortion to the first 10 PCs were found to be comparable. Based on the distribution of the first 3 PC, 10 protein conformers are identified showing relative root mean square deviations (RMSD) between 2.3 and 4.6 Å. The main PCs are found to be delocalized over the whole protein structure indicating that the motions of different protein subdomains are coupled. This coupling is considered as being related to the allosteric effects observed upon ligand binding to HSA. On the other hand, the first PC of one of the three trajectories describes a conformational transition of the protein domain I that is close to that experimentally observed upon myristate binding. This is a theoretical support for the older hypothesis stating that changes of the protein onformation favorable to binding can precede the ligand complexation. A detailed all atoms PCA performed on the primary Sites 1 and 2 confirms the multiconformational character of the HSA binding sites as well as the significant coupling of their motions. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 561–572, 2014.     

Allostery without conformational change

A general model is presented whereby lignand-induced changes in protein dynamics could produce allosteric communication between distinct binding sites, even in the absence of a macromolecular conformational change. Theoretical analysis, based on the statistical thermodynamics of ligand binding, shows that cooperative interaction free energies amounting to several kJ · mol^-1 may be generated by this means. The effect arises out of the possible changes in frequencies and amplitudes of macromolecular thermal fluctuations in response to ligand attachment, and can involve all forms of dynamic behaviour, ranging from highly correlated, low-frequency normal mode vibrations to random local anharmonic motions of individual atoms or groups. Dynamic allostery of this form is primarily an entropy effect, and we derive approximate expressions which might allow the magnitude of the interaction in real systems to be calculated directly from experimental observations such as changes in normal mode frequencies and mean-square atomic displacements. Long-range influence of kinetic processes at different sites might also be mediated by a similar mechanism. We suggest that proteins and other biological macromolecules may have evolved to take functional advantage not only of mean conformational states but also of the inevitable thermal fluctuations about the mean.     

The Structural Basis of ATP as an Allosteric Modulator

Adenosine-5’-triphosphate (ATP) is generally regarded as a substrate for energy currency and protein modification. Recent findings uncovered the allosteric function of ATP in cellular signal transduction but little is understood about this critical behavior of ATP. Through extensive analysis of ATP in solution and proteins, we found that the free ATP can exist in the compact and extended conformations in solution, and the two different conformational characteristics may be responsible for ATP to exert distinct biological functions: ATP molecules adopt both compact and extended conformations in the allosteric binding sites but conserve extended conformations in the substrate binding sites. Nudged elastic band simulations unveiled the distinct dynamic processes of ATP binding to the corresponding allosteric and substrate binding sites of uridine monophosphate kinase, and suggested that in solution ATP preferentially binds to the substrate binding sites of proteins. When the ATP molecules occupy the allosteric binding sites, the allosteric trigger from ATP to fuel allosteric communication between allosteric and functional sites is stemmed mainly from the triphosphate part of ATP, with a small number from the adenine part of ATP. Taken together, our results provide overall understanding of ATP allosteric functions responsible for regulation in biological systems.     

Accounting for global protein deformability during protein-protein and protein-ligand docking

Computational docking methods are valuable tools aimed to simplify the costly process of drug development and improvement. Most current approaches assume a rigid receptor structure to allow virtual screening of large numbers of possible ligands and putative binding sites on a receptor molecule. However, inclusion of receptor flexibility can be of critical importance since binding of a ligand can lead to changes in the receptor protein conformation that are sterically necessary to accommodate a ligand. Recent approaches to efficiently account for receptor flexibility during docking simulations are reviewed. In particular, accounting efficiently for global conformational changes of the protein backbone during docking is a still challenging unsolved problem. An approximate method has recently been suggested that is based on relaxing the receptor conformation during docking in pre-calculated soft collective degrees of freedom (M. Zacharias, Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP, Proteins: Struct., Funct., Genet. 54 (2004) 759-767). Test applications on protein-protein docking and on docking the inhibitor staurosporine to the apo-form of cAMP-dependent protein kinase A catalytic domain indicate significant improvement of docking results compared to rigid docking at a very modest computational demand. Accounting for receptor conformational changes in pre-calculated global degrees of freedom might offer a promising route to improve systematic docking screening simulations.     

Ligand-linked structural changes in the Escherichia coli biotin repressor: the significance of surface loops for binding and allostery.

The Escherichia coli repressor of biotin biosynthesis (BirA) is an allosteric site-specific DNA-binding protein. BirA catalyzes synthesis of biotinyl-5'-AMP from substrates biotin and ATP and the adenylate serves as the positive allosteric effector in binding of the repressor to the biotin operator sequence. Although a three-dimensional structure of the apo-repressor has been determined by X-ray crystallographic techniques, no structures of any ligand-bound forms of the repressor are yet available. Results of previously published solution studies are consistent with the occurrence of conformational changes in the protein concomitant with ligand binding. In this work the hydroxyl radical footprinting technique has been used to probe changes in reactivity of the peptide backbone of BirA that accompany ligand binding. Results of these studies indicate that binding of biotin to the protein results in protection of regions of the central domain in the vicinity of the active site and the C-terminal domain from chemical cleavage. Biotin-linked changes in reactivity constitute a subset of those linked to adenylate binding. Binding of both bio-5'-AMP and biotin operator DNA suppresses cleavage at additional sites in the amino and carboxy-terminal domains of the protein. Varying degrees of protection of the five surface loops on BirA from hydroxyl radical-mediated cleavage are observed in all complexes. These results implicate the C-terminal domain of BirA, for which no function has previously been known, in small ligand and site-specific DNA binding and highlight the significance of surface loops, some of which are disordered in the apoBirA structure, for ligand binding and transmission of allosteric information in the protein.     

The role of slow and fast protein motions in allosteric interactions

Allostery is fundamentally thermodynamic in nature. Long-range communication in proteins may be mediated not only by changes in the mean conformation with enthalpic contribution but also by changes in dynamic fluctuations with entropic contribution. The important role of protein motions in mediating allosteric interactions has been established by NMR spectroscopy. By using CAP as a model system, we have shown how changes in protein structure and internal dynamics can allosterically regulate protein function and activity. The results indicate that changes in conformational entropy can give rise to binding enhancement, binding inhibition, or have no effect in the expected affinity, depending on the magnitude and sign of enthalpy–entropy compensation. Moreover, allosteric interactions can be regulated by the modulation a low-populated conformation states that serve as on-pathway intermediates for ligand binding. Taken together, the interplay between fast internal motions, which are intimately related to conformational entropy, and slow internal motions, which are related to poorly populated conformational states, can regulate protein activity in a way that cannot be predicted on the basis of the protein’s ground-state structure.     

Allosteric communication in cysteinyl tRNA synthetase: a network of direct and indirect readout

Protein structure networks are constructed for the identification of long-range signaling pathways in cysteinyl tRNA synthetase (CysRS). Molecular dynamics simulation trajectory of CysRS-ligand complexes were used to determine conformational ensembles in order to gain insight into the allosteric signaling paths. Communication paths between the anticodon binding region and the aminoacylation region have been identified. Extensive interaction between the helix bundle domain and the anticodon binding domain, resulting in structural rigidity in the presence of tRNA, has been detected. Based on the predicted model, six residues along the communication paths have been examined by mutations (single and double) and shown to mediate a coordinated coupling between anticodon recognition and activation of amino acid at the active site. This study on CysRS clearly shows that specific key residues, which are involved in communication between distal sites in allosteric proteins but may be elusive in direct structure analysis, can be identified from dynamics of protein structure networks.     

Pocketome via comprehensive identification and classification of ligand binding envelopes

We developed a new computational algorithm for the accurate identification of ligand binding envelopes rather than surface binding sites. We performed a large scale classification of the identified envelopes according to their shape and physicochemical properties. The predicting algorithm, called PocketFinder, uses a transformation of the Lennard-Jones potential calculated from a three-dimensional protein structure and does not require any knowledge about a potential ligand molecule. We validated this algorithm using two systematically collected data sets of ligand binding pockets from complexed (bound) and uncomplexed (apo) structures from the Protein Data Bank, 5616 and 11,510, respectively. As many as 96.8% of experimental binding sites were predicted at better than 50% overlap level. Furthermore 95.0% of the asserted sites from the apo receptors were predicted at the same level. We demonstrate that conformational differences between the apo and bound pockets do not dramatically affect the prediction results. The algorithm can be used to predict ligand binding pockets of uncharacterized protein structures, suggest new allosteric pockets, evaluate feasibility of protein-protein interaction inhibition, and prioritize molecular targets. Finally the data base of the known and predicted binding pockets for the human proteome structures, the human pocketome, was collected and classified. The pocketome can be used for rapid evaluation of possible binding partners of a given chemical compound.