Probing the Transition State of the Allosteric Pathway of the Shaker Kv Channel Pore by Linear Free-Energy Relations

Long-range coupling between distant functional elements of proteins may rely on allosteric communication trajectories lying along the protein structure, as described in the case of the Shaker voltage-activated potassium (Kv) channel model allosteric system. Communication between the distant Kv channel activation and slow inactivation pore gates was suggested to be mediated by a network of local pairwise and higher-order interactions among the functionally unique residues that constitute the allosteric trajectory. The mechanism by which conformational changes propagate along the Kv channel allosteric trajectory to achieve pore opening, however, remains unclear. Such conformational changes may propagate in either a concerted or a sequential manner during the reaction coordinate of channel opening. Residue-level structural information on the transition state of channel gating is required to discriminate between these possibilities. Here, we combine patch-clamp electrophysiology recordings of Kv channel gating and analysis using linear free-energy relations, focusing on a select set of residues spanning the allosteric trajectory of the Kv channel pore. We show that all allosteric trajectory residues tested exhibit an open-like conformation in the transition state of channel opening, implying that coupling interactions occur along the trajectory break in a concerted manner upon moving from the closed to the open state. Energetic coupling between the Kv channel gates thus occurs in a concerted fashion in both the spatial and the temporal dimensions, strengthening the notion that such trajectories correspond to pathways of mechanical deformation along which conformational changes propagate.     

Pump-probe molecular dynamics as a tool for studying protein motion and long range coupling

A new method for analyzing the dynamics of proteins is developed and tested. The method, pump-probe molecular dynamics, excites selected atoms or residues with a set of oscillating forces, and the transmission of the impulse to other parts of the protein is probed using Fourier transform of the atomic motions. From this analysis, a coupling profile can be determined which quantifies the degree of interaction between pump and probe residues. Various physical properties of the method such as reciprocity and speed of transmission are examined to establish the soundness of the method. The coupling strength can be used to address questions such as the degree of interaction between different residues at the level of dynamics, and identify propagation of influence of one part of the protein on another via "pathways" through the protein. The method is illustrated by analysis of coupling between different secondary structure elements in the allosteric protein calmodulin, and by analysis of pathways of residue-residue interaction in the PDZ domain protein previously elucidated by genomics and mutational studies.     

Modeling Signal Propagation Mechanisms and Ligand-Based Conformational Dynamics of the Hsp90 Molecular Chaperone Full-Length Dimer

Hsp90 is a molecular chaperone essential for protein folding and activation in normal homeostasis and stress response. ATP binding and hydrolysis facilitate Hsp90 conformational changes required for client activation. Hsp90 plays an important role in disease states, particularly in cancer, where chaperoning of the mutated and overexpressed oncoproteins is important for function. Recent studies have illuminated mechanisms related to the chaperone function. However, an atomic resolution view of Hsp90 conformational dynamics, determined by the presence of different binding partners, is critical to define communication pathways between remote residues in different domains intimately affecting the chaperone cycle. Here, we present a computational analysis of signal propagation and long-range communication pathways in Hsp90. We carried out molecular dynamics simulations of the full-length Hsp90 dimer, combined with essential dynamics, correlation analysis, and a signal propagation model. All-atom MD simulations with timescales of 70 ns have been performed for complexes with the natural substrates ATP and ADP and for the unliganded dimer. We elucidate the mechanisms of signal propagation and determine “hot spots” involved in interdomain communication pathways from the nucleotide-binding site to the C-terminal domain interface. A comprehensive computational analysis of the Hsp90 communication pathways and dynamics at atomic resolution has revealed the role of the nucleotide in effecting conformational changes, elucidating the mechanisms of signal propagation. Functionally important residues and secondary structure elements emerge as effective mediators of communication between the nucleotide-binding site and the C-terminal interface. Furthermore, we show that specific interdomain signal propagation pathways may be activated as a function of the ligand. Our results support a “conformational selection model” of the Hsp90 mechanism, whereby the protein may exist in a dynamic equilibrium between different conformational states available on the energy landscape and binding of a specific partner can bias the equilibrium toward functionally relevant complexes.     

Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models

BackgroundAccumulated evidence indicates that bacterial ribosome employs allostery throughout its structure for protein synthesis. The nature of the allosteric communication between remote functional sites remains unclear, but the contact topology and dynamics of residues may play role in transmission of a perturbation to distant sites.Methods/resultsWe employ two computationally efficient approaches – graph and elastic network modeling to gain insights about the allosteric communication in ribosome. Using graph representation of the structure, we perform k-shortest pathways analysis between peptidyl transferase center-ribosomal tunnel, decoding center-peptidyl transferase center - previously reported functional sites having allosteric communication. Detailed analysis on intact structures points to common and alternative shortest pathways preferred by different states of translation. All shortest pathways capture drug target sites and allosterically important regions. Elastic network model further reveals that residues along all pathways have the ability of quickly establishing pair-wise communication and to help the propagation of a perturbation in long-ranges during functional motions of the complex.ConclusionsContact topology and inherent dynamics of ribosome configure potential communication pathways between functional sites in different translation states. Inter-subunit bridges B2a, B3 and P-tRNA come forward for their high potential in assisting allostery during translation. Especially B3 emerges as a potential druggable site.General significanceThis study indicates that the ribosome topology forms a basis for allosteric communication, which can be disrupted by novel drugs to kill drug-resistant bacteria. Our computationally efficient approach not only overlaps with experimental evidence on allosteric regulation in ribosome but also proposes new druggable sites.     

Predicting allosteric communication in myosin via a pathway of conserved residues

We present a computational method that predicts a pathway of residues that mediate protein allosteric communication. The pathway is predicted using only a combination of distance constraints between contiguous residues and evolutionary data. We applied this analysis to find pathways of conserved residues connecting the myosin ATP binding site to the lever arm. These pathway residues may mediate the allosteric communication that couples ATP hydrolysis to the lever arm recovery stroke. Having examined pre-stroke conformations of Dictyostelium, scallop, and chicken myosin II as well as Dictyostelium myosin I, we observed a conserved pathway traversing switch II and the relay helix, which is consistent with the understood need for allosteric communication in this conformation. We also examined post-rigor and rigor conformations across several myosin species. Although initial residues of these paths are more heterogeneous, all but one of these paths traverse a consistent set of relay helix residues to reach the beginning of the lever arm. We discuss our results in the context of structural elements and reported mutational experiments, which substantiate the significance of the pre-stroke pathways. Our method provides a simple, computationally efficient means of predicting a set of residues that mediate allosteric communication. We provide a refined, downloadable application and source code (on https://simtk.org) to share this tool with the wider community (https://simtk.org/home/allopathfinder).     

Computation of Conformational Coupling in Allosteric Proteins

In allosteric regulation, an effector molecule binding a protein at one site induces conformational changes, which alter structure and function at a distant active site. Two key challenges in the computational modeling of allostery are the prediction of the structure of one allosteric state starting from the structure of the other, and elucidating the mechanisms underlying the conformational coupling of the effector and active sites. Here we approach these two challenges using the Rosetta high-resolution structure prediction methodology. We find that the method can recapitulate the relaxation of effector-bound forms of single domain allosteric proteins into the corresponding ligand-free states, particularly when sampling is focused on regions known to change conformation most significantly. Analysis of the coupling between contacting pairs of residues in large ensembles of conformations spread throughout the landscape between and around the two allosteric states suggests that the transitions are built up from blocks of tightly coupled interacting sets of residues that are more loosely coupled to one another.     

Structure-based rebuilding of coevolutionary information reveals functional modules in rhodopsin structure

Correlated mutation analysis (CMA) has been used to investigate protein functional sites. However, CMA has suffered from low signal-to-noise ratio caused by meaningless phylogenetic signals or structural constraints. We present a new method, Structure-based Correlated Mutation Analysis (SCMA), which encodes coevolution scores into a protein structure network. A path-based network model is adapted to describe information transfer between residues, and the statistical significance is estimated by network shuffling. This model intrinsically assumes that residues in physical contact have a more reliable coevolution score than distant residues, and that coevolution in distant residues likely arises from a series of contacting and coevolving residues. In addition, coevolutionary coupling is statistically controlled to remove the structural effects. When applied to the rhodopsin structure, the SCMA method identified a much higher percentage of functional residues than the typical coevolution score (61% vs. 22%). In addition, statistically significant residues are used to construct the coevolved residue-residue subnetwork. The network has one highly connected node (retinal bound Lys296), indicating that Lys296 can induce and regulate most other coevolved residues in a variety of locations. The coevolved network consists of a few modular clusters which have distinct functional roles. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.     

"Fluctuograms" reveal the intermittent intra-protein communication in subtilisin Carlsberg and correlate mechanical coupling with co-evolution

The mechanism of intra-protein communication and allosteric coupling is key to understanding the structure-property relationship of protein function. For subtilisin Carlsberg, the Ca2+-binding loop is distal to substrate-binding and active sites, yet the serine protease function depends on Ca2+ binding. The atomic molecular dynamics (MD) simulations of apo and Ca2+-bound subtilisin show similar structures and there is no direct evidence that subtilisin has alternative conformations. To model the intra-protein communication due to Ca2+ binding, we transform the sequential segments of an atomic MD trajectory into separate elastic network models to represent anharmonicity and nonlinearity effectively as the temporal and spatial variation of the mechanical coupling network. In analogy to the spectrogram of sound waves, this transformation is termed the "fluctuogram" of protein dynamics. We illustrate that the Ca2+-bound and apo states of subtilisin have different fluctuograms and that intra-protein communication proceeds intermittently both in space and in time. We found that residues with large mechanical coupling variation due to Ca2+ binding correlate with the reported mutation sites selected by directed evolution for improving the stability of subtilisin and its activity in a non-aqueous environment. Furthermore, we utilize the fluctuograms calculated from MD to capture the highly correlated residues in a multiple sequence alignment. We show that in addition to the magnitude, the variance of coupling strength is also an indicative property for the sequence correlation observed in a statistical coupling analysis. The results of this work illustrate that the mechanical coupling networks calculated from atomic details can be used to correlate with functionally important mutation sites and co-evolution.     

Calcium-induced conformational switching of Paramecium calmodulin provides evidence for domain coupling

Calmodulin (CaM) is an intracellular calcium-binding protein essential for many pathways in eukaryotic signal transduction. Although a structure of Ca(2+)-saturated Paramecium CaM at 1.0 A resolution (1EXR.pdb) provides the highest level of detail about side-chain orientations in CaM, information about an end state alone cannot explain driving forces for the transitions that occur during Ca(2+)-induced conformational switching and why the two domains of CaM are saturated sequentially rather than simultaneously. Recent studies focus attention on the contributions of interdomain linker residues. Electron paramagnetic resonance showed that Ca(2+)-induced structural stabilization of residues 76-81 modulates domain coupling [Qin and Squier (2001) Biophys. J. 81, 2908-2918]. Studies of N-domain fragments of Paramecium CaM showed that residues 76-80 increased thermostability of the N-domain but lowered the Ca(2+) affinity of sites I and II [Sorensen et al. (2002) Biochemistry 41, 15-20]. To probe domain coupling during Ca(2+) binding, we have used (1)H-(15)N HSQC NMR to monitor more than 40 residues in Paramecium CaM. The titrations demonstrated that residues Glu78 to Glu84 (in the linker and cap of helix E) underwent sequential phases of conformational change. Initially, they changed in volume (slow exchange) as sites III and IV titrated, and subsequently, they changed in frequency (fast exchange) as sites I and II titrated. These studies provide evidence for Ca(2+)-dependent communication between the domains, demonstrating that spatially distant residues respond to Ca(2+) binding at sites I and II in the N-domain of CaM.     

The role of mobile genetic elements in bacterial adaptation to xenobiotic organic compounds

Retrospective studies clearly indicate that mobile genetic elements (MGEs) play a major role in the in situ spread and even de novo construction of catabolic pathways in bacteria, allowing bacterial communities to rapidly adapt to new xenobiotics. The construction of novel pathways seems to occur by an assembly process that involves horizontal gene transfer: different appropriate genes or gene modules that encode different parts of the novel pathway are recruited from phylogenetically related or distant hosts into one single host. Direct evidence for the importance of catabolic MGEs in bacterial adaptation to xenobiotics stems from observed correlations between catabolic gene transfer and accelerated biodegradation in several habitats and from studies that monitor catabolic MGEs in polluted sites.     

Conformational dynamics of supramolecular protein assemblies

Supramolecular protein assemblies including molecular motors, cytoskeletal filaments, chaperones, and ribosomes play a central role in a broad array of cellular functions ranging from cell division and motility to RNA and protein synthesis and folding. Single-particle reconstructions of such assemblies have been growing rapidly in recent years, providing increasingly high resolution structural information under native conditions. While the static structure of these assemblies provides essential insight into their mechanism of biological function, their dynamical motions provide additional important information that cannot be inferred from structure alone. Here we present an unsupervised computational framework for the analysis of high molecular weight protein assemblies and use it to analyze the conformational dynamics of structures deposited in the Electron Microscopy Data Bank. Protein assemblies are modeled using a recently introduced coarse-grained modeling framework based on the finite element method, which is used to compute equilibrium thermal fluctuations, elastic strain energy distributions associated with specific conformational transitions, and dynamical correlations in distant molecular domains. Results are presented in detail for the ribosome-bound termination factor RF2 from Escherichia coli, the nuclear pore complex from Dictyostelium discoideum, and the chaperonin GroEL from E. coli. Elastic strain energy distributions reveal hinge-regions associated with specific conformational change pathways, and correlations in collective molecular motions reveal dynamical coupling between distant molecular domains that suggest new, as well as confirm existing, allosteric mechanisms. Results are publically available for use in further investigation and interpretation of biological function including cooperative transitions, allosteric communication, and molecular mechanics, as well as in further classification and refinement of electron microscopy based structures.     

A Combinatorial Approach to Detect Coevolved Amino Acid Networks in Protein Families of Variable Divergence

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.     

Evolutionarily conserved networks of residues mediate allosteric communication in proteins

A fundamental goal in cellular signaling is to understand allosteric communication, the process by which signals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Here, we describe a sequence-based statistical method for quantitatively mapping the global network of amino acid interactions in a protein. Application of this method for three structurally and functionally distinct protein families (G protein-coupled receptors, the chymotrypsin class of serine proteases and hemoglobins) reveals a surprisingly simple architecture for amino acid interactions in each protein family: a small subset of residues forms physically connected networks that link distant functional sites in the tertiary structure. Although small in number, residues comprising the network show excellent correlation with the large body of mechanistic data available for each family. The data suggest that evolutionarily conserved sparse networks of amino acid interactions represent structural motifs for allosteric communication in proteins.     

Structure and function of chromophores in R-Phycoerythrin at 1.9 A resolution

The crystal structure of R-Phycoerythrin (R-PE) from Polysiphonia urceolata has been refined to a resolution of 1.9 A, based on the atomic coordinates of R-PE determined at 2.8 A resolution, through the use of difference Fourier method and steorochemistry parameters restrained refinement with model adjustment according to the electron density map. Crystallographic R-factor of the refined model is 0.195 (Rfree = 0.282) from 8-1.9 A. High resolution structure of R-PE showed precise interactions between the chromophores and protein residues, which explained the spectrum characteristic and function of chromophores. Four chiral atoms of phycourobilin (PUB) were identified as C(4)-S, C(16)-S, C(21)-S, and C(20)-R. In addition to the coupling distances of 19 A to 45 A between the chromophores which were observed and involved in the energy transfer pathway, high resolution structure of R-PE suggested other pathways of energy transfer, such as the ultrashort distance between alpha140a and beta155. It has been proposed that aromatic residues in linker proteins not only influence the conformation of chromophore, but may also bridge chromophores to improve the energy transfer efficiency.     

Chasing long-range evolutionary couplings in the AlphaFold era

Coevolution between protein residues is normally interpreted as direct contact. However, the evolutionary record of a protein sequence contains rich information that may include long-range functional couplings, couplings that report on homo-oligomeric states or even conformational changes. Due to the complexity of the sequence space and the lack of structural information on various members of a protein family, it has been difficult to effectively mine the additional information encoded in a multiple sequence alignment (MSA). Here, taking advantage of the recent release of the AlphaFold (AF) database we attempt to identify coevolutionary couplings that cannot be explained simply by spatial proximity. We propose a simple computational method that performs direct coupling analysis on a MSA and searches for couplings that are not satisfied in any of the AF models of members of the identified protein family. Application of this method on 2012 protein families suggests that ~12% of the total identified coevolving residue pairs are spatially distant and more likely to be disordered than their contacting counterparts. We expect that this analysis will help improve the quality of coevolutionary distance restraints used for structure determination and will be useful in identifying potentially functional/allosteric cross-talk between distant residues.     

Mechanical Signaling on the Single Protein Level Studied Using Steered Molecular Dynamics

Efficient communication between the cell and its external environment is of the utmost importance to the function of multicellular organisms. While signaling events can be generally characterized as information exchange by means of controlled energy conversion, research efforts have hitherto mainly been concerned with mechanisms involving chemical and electrical energy transfer. Here, we review recent computational efforts addressing the function of mechanical force in signal transduction. Specifically, we focus on the role of steered molecular dynamics (SMD) simulations in providing details at the atomic level on a group of protein domains, which play a fundamental role in signal exchange by responding properly to mechanical strain. We start by giving a brief introduction to the SMD technique and general properties of mechanically stable protein folds, followed by specific examples illustrating three general regimes of signal transfer utilizing mechanical energy: purely mechanical, mechanical to chemical, and chemical to mechanical. Whenever possible the physiological importance of the example at hand is stressed to highlight the diversity of the processes in which mechanical signaling plays a key role. We also provide an overview of future challenges and perspectives for this rapidly developing field.     

Non-additivity in protein-protein interactions

The energy of binding between proteins may be seen as the sum of the contributions of the individual amino acid residues. These contributions are additive when the binding energy, due to different amino acid residues, is independent of the interactions between amino acids in the same polypeptide chain. A measure of non-additivity is the coupling free energy. In this communication it is shown that: (1) the coupling free energy is the sum of intramolecular and intermolecular contributions; and (2), when additivity exists, experimentally determined values for the free energy of transfer of amino acids from water to the hydrophobic protein-protein interface are a very good approximation of their contribution to the energy of binding. Additivity cycles can be useful in determining the precise conditions where this approximation holds.     

Electron tunneling through proteins

Electron transfer processes are vital elements of energy transduction pathways in living cells. More than a half century of research has produced a remarkably detailed understanding of the factors that regulate these 'currents of life'. We review investigations of Ru-modified proteins that have delineated the distance- and driving-force dependences of intra-protein electron-transfer rates. We also discuss electron transfer across protein-protein interfaces that has been probed both in solution and in structurally characterized crystals. It is now clear that electrons tunnel between sites in biological redox chains, and that protein structures tune thermodynamic properties and electronic coupling interactions to facilitate these reactions. Our work has produced an experimentally validated timetable for electron tunneling across specified distances in proteins. Many electron tunneling rates in cytochrome c oxidase and photosynthetic reaction centers agree well with timetable predictions, indicating that the natural reactions are highly optimized, both in terms of thermodynamics and electronic coupling. The rates of some reactions, however, significantly exceed timetable predictions: it is likely that multistep tunneling is responsible for these anomalously rapid charge transfer events.     

Simulating proton translocations in proteins: probing proton transfer pathways in the Rhodobacter sphaeroides reaction center.

A general method for simulating proton translocations in proteins and for exploring the role of different proton transfer pathways is developed and examined. The method evaluates the rate constants for proton transfer processes using the energetics of the relevant proton configurations. The energies (DeltaG((m))) of the different protonation states are evaluated in two steps. First, the semimicroscopic version of the protein dipole Langevin dipole (PDLD/S) method is used to evaluate the intrinsic energy of bringing the protons to their protein sites, when the charges of all protein ionized residues are set to zero. Second, the interactions between the charged groups are evaluated by using a Coulomb's Law with an effective dielectric constant. This approach, which was introduced in an earlier study by one of the authors of the current report, allows for a very fast determination of any DeltaG((m)) and for practical evaluation of the time-dependent proton population: That is, the rate constants for proton transfer processes are evaluated by using the corresponding DeltaG((m)) values and a Marcus type relationship. These rate constants are then used to construct a master equation, the integration of which by a fourth-order Runge-Kutta method yields the proton population as a function of time. The integration evaluates, 'on the fly,' the changes of the rate constants as a result of the time-dependent changes in charge-charge interaction, and this feature benefits from the fast determination of DeltaG((m)). The method is demonstrated in a preliminary study of proton translocation processes in the reaction center of Rhodobacter sphaeroides. It is found that proton transfer across water chains involves significant activation barriers and that ionized protein residues probably are involved in the proton transfer pathways. The potential of the present method in analyzing mutation experiments is discussed briefly and illustrated. The present study also examines different views of the nature of proton translocations in proteins. It is shown that such processes are controlled mainly by the electrostatic interaction between the proton site and its surroundings rather than by the local bond rearrangements of water molecules that are involved in the proton pathways. Thus, the overall rate of proton transport frequently is controlled by the highest barrier along the conduction pathway. Proteins 1999;36:484-500.     

The Ising model for prediction of disordered residues from protein sequence alone

Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered residues and disordered regions in protein chains using protein sequence alone. A new method (IsUnstruct) based on the Ising model for prediction of disordered residues from protein sequence alone has been developed. According to this model, each residue can be in one of two states: ordered or disordered. The model is an approximation of the Ising model in which the interaction term between neighbors has been replaced by a penalty for changing between states (the energy of border). The IsUnstruct has been compared with other available methods and found to perform well. The method correctly finds 77% of disordered residues as well as 87% of ordered residues in the CASP8 database, and 72% of disordered residues as well as 85% of ordered residues in the DisProt database.