基于弹性网络模型的蛋白质变构路径与关键残基识别研究

目的 变构效应在蛋白质生物学功能执行过程中发挥着重要的调控作用，如何基于蛋白质空间结构，有效识别变构信号的传播路径和关键的残基位点是蛋白质结构-功能关系研究领域的热点科学问题。方法 本研究利用基于弹性网络模型（elastic network model，ENM）的力分布计算方法，通过分析蛋白质对外力的响应过程，来识别体系的变构路径以及变构过程中的关键残基。在该方法中，对蛋白质的关键变构位点施加外力，通过对体系形变以及内力分布情况的分析，有效识别与外力承载区域形变相耦合的关键残基，从而得到力信号在蛋白质结构内的传播路径。结果 利用该方法研究了人类磷酸甘油酸激酶（human phosphoglycerate kinase，hPGK）和蛋白质酪氨酸磷酸酶（protein tyrosine phosphatase，PTP）PDZ2结构域的变构调控路径和关键残基。对于hPGK，识别出从底物结合位点到铰链区的两条变构信号传导路径。对于PTP PDZ2，也成功识别出从配体结合位点传递到蛋白质远端的两条长程变构调控路径。计算结果与实验和分子动力学（molecular dynamics，MD）模拟得到的结果一致。结论 本研究为蛋白质体系关键残基识别及变构路径研究提供了有效的分析方法。     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Conformational changes and allosteric communications in human serum albumin due to ligand binding

It is well recognized that knowledge of structure alone is not sufficient to understand the fundamental mechanism of biomolecular recognition. Information of dynamics is necessary to describe motions involving relevant conformational states of functional importance. We carried out principal component analysis (PCA) of structural ensemble, derived from 84 crystal structures of human serum albumin (HSA) with different ligands and/or different conditions, to identify the functionally important collective motions, and compared with the motions along the low-frequency modes obtained from normal mode analysis of the elastic network model (ENM) of unliganded HSA. Significant overlap is observed in the collective motions derived from PCA and ENM. PCA and ENM analysis revealed that ligand selects the most favored conformation from accessible equilibrium structures of unliganded HSA. Further, we analyzed dynamic network obtained from molecular dynamics simulations of unliganded HSA and fatty acids- bound HSA. Our results show that fatty acids-bound HSA has more robust community network with several routes to communicate among different parts of the protein. Critical nodes (residues) identified from dynamic network analysis are in good agreement with allosteric residues obtained from sequence-based statistical coupling analysis method. This work underscores the importance of intrinsic structural dynamics of proteins in ligand recognition and can be utilized for the development of novel drugs with optimum activity.     

Multiscale modeling of structural dynamics underlying force generation and product release in actomyosin complex

To decrypt the mechanistic basis of myosin motor function, it is essential to probe the conformational changes in actomyosin with high spatial and temporal resolutions. In a computational effort to meet this challenge, we have performed a multiscale modeling of the allosteric couplings and transition pathway of actomyosin complex by combining coarse‐grained modeling of the entire complex with all‐atom molecular dynamics simulations of the active site. Our modeling of allosteric couplings at the pre‐powerstroke state has pinpointed key actin‐activated couplings to distant myosin parts which are critical to force generation and the sequential release of phosphate and ADP. At the post‐powerstroke state, we have identified isoform‐dependent couplings which underlie the reciprocal coupling between actin binding and nucleotide binding in fast Myosin II, and load‐dependent ADP release in Myosin V. Our modeling of transition pathway during powerstroke has outlined a clear sequence of structural events triggered by actin binding, which lead to subsequent force generation, twisting of central β‐sheet, and the sequential release of phosphate and ADP. Finally we have performed atomistic simulations of active‐site dynamics based on an on‐path “transition‐state” myosin conformation, which has revealed significantly weakened coordination of phosphate by Switch II, and a disrupted key salt bridge between Switch I and II. Meanwhile, the coordination of MgADP by Switch I and P loop is less perturbed. As a result, the phosphate can be released prior to MgADP. This study has shed new lights on the controversy over the structural mechanism of actin‐activated phosphate release and force generation in myosin motor. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Mode coupling points to functionally important residues in myosin II

Relevance of mode coupling to energy/information transfer during protein function, particularly in the context of allosteric interactions is widely accepted. However, existing evidence in favor of this hypothesis comes essentially from model systems. We here report a novel formal analysis of the near‐native dynamics of myosin II, which allows us to explore the impact of the interaction between possibly non‐Gaussian vibrational modes on fluctutational dynamics. We show that an information‐theoretic measure based on mode coupling alone yields a ranking of residues with a statistically significant bias favoring the functionally critical locations identified by experiments on myosin II. Proteins 2014; 82:1777–1786. © 2014 Wiley Periodicals, Inc.     

Large‐scale comparison of protein essential dynamics from molecular dynamics simulations and coarse‐grained normal mode analyses

A large‐scale comparison of essential dynamics (ED) modes from molecular dynamic simulations and normal modes from coarse‐grained normal mode methods (CGNM) was performed on a dataset of 335 proteins. As CGNM methods, the elastic network model (ENM) and the rigid cluster normal mode analysis (RCNMA) were used. Low‐frequency normal modes from ENM correlate very well with ED modes in terms of directions of motions and relative amplitudes of motions. Notably, a similar performance was found if normal modes from RCNMA were used, despite a higher level of coarse graining. On average, the space spanned by the first quarter of ENM modes describes 84% of the space spanned by the five ED modes. Furthermore, no prominent differences for ED and CGNM modes among different protein structure classes (CATH classification) were found. This demonstrates the general potential of CGNM approaches for describing intrinsic motions of proteins with little computational cost. For selected cases, CGNM modes were found to be more robust among proteins that have the same topology or are of the same homologous superfamily than ED modes. In view of recent evidence regarding evolutionary conservation of vibrational dynamics, this suggests that ED modes, in some cases, might not be representative of the underlying dynamics that are characteristic of a whole family, probably due to insufficient sampling of some of the family members by MD. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Toward the mechanism of dynamical couplings and translocation in hepatitis C virus NS3 helicase using elastic network model

Hepatitis C virus NS3 helicase is an enzyme that unwinds double-stranded polynucleotides in an ATP-dependent reaction. It provides a promising target for small molecule therapeutic agents against hepatitis C. Design of such drugs requires a thorough understanding of the dynamical nature of the mechanochemical functioning of the helicase. Despite recent progress, the detailed mechanism of the coupling between ATPase activity and helicase activity remains unclear. Based on an elastic network model (ENM), we apply two computational analysis tools to probe the dynamical mechanism underlying the allosteric coupling between ATP binding and polynucleotide binding in this enzyme. The correlation analysis identifies a network of hot-spot residues that dynamically couple the ATP-binding site and the polynucleotide-binding site. Several of these key residues have been found by mutational experiments as functionally important, while our analysis also reveals previously unexplored hot-spot residues that are potential targets for future mutational studies. The conformational changes between different crystal structures of NS3 helicase are found to be dominated by the lowest frequency mode solved from the ENM. This mode corresponds to a hinge motion of the highly flexible domain 2. This motion simultaneously modulates the opening/closing of the domains 1-2 cleft where ATP binds, and the domains 2-3 cleft where the polynucleotide binds. Additionally, a small twisting motion of domain 1, observed in both mode 1 and the computed ATP binding induced conformational change, fine-tunes the binding affinity of the domains 1-3 interface for the polynucleotide. The combination of these motions facilitates the translocation of a single-stranded polynucleotide in an inchworm-like manner.     

How an Inhibitor Bound to Subunit Interface Alters Triosephosphate Isomerase Dynamics

The tunnel region at triosephosphate isomerase (TIM)’s dimer interface, distant from its catalytic site, is a target site for certain benzothiazole derivatives that inhibit TIM’s catalytic activity in Trypanosoma cruzi, the parasite that causes Chagas disease. We performed multiple 100-ns molecular-dynamics (MD) simulations and elastic network modeling (ENM) on both apo and complex structures to shed light on the still unclear inhibitory mechanism of one such inhibitor, named bt10. Within the time frame of our MD simulations, we observed stabilization of aromatic clusters at the dimer interface and enhancement of intersubunit hydrogen bonds in the presence of bt10, which point to an allosteric effect rather than destabilization of the dimeric structure. The collective dynamics dictated by the topology of TIM is known to facilitate the closure of its catalytic loop over the active site that is critical for substrate entrance and product release. We incorporated the ligand’s effect on vibrational dynamics by applying mixed coarse-grained ENM to each one of 54,000 MD snapshots. Using this computationally efficient technique, we observed altered collective modes and positive shifts in eigenvalues due to the constraining effect of bt10 binding. Accordingly, we observed allosteric changes in the catalytic loop’s dynamics, flexibility, and correlations, as well as the solvent exposure of catalytic residues. A newly (to our knowledge) introduced technique that performs residue-based ENM scanning of TIM revealed the tunnel region as a key binding site that can alter global dynamics of the enzyme.     

Dynamical persistence of active sites identified in maltose-binding protein

This study identifies dynamical properties of maltose-binding protein (MBP) useful in unveiling active site residues susceptible to ligand binding. The described methodology has been previously used in support of novel topological techniques of persistent homology and statistical inference in complex, multi-scale, high-dimensional data often encountered in computational biophysics. Here we outline a computational protocol that is based on the anisotropic elastic network models of 14 all-atom three-dimensional protein structures. We introduce the notion of dynamical distance matrices as a measure of correlated interactions among 370 amino acid residues that constitute a single protein. The dynamical distance matrices serve as an input for a persistent homology suite of codes to further distinguish a small subset of residues with high affinity for ligand binding and allosteric activity. In addition, we show that ligand-free closed MBP structures require lower deformation energies than open MBP structures, which may be used in categorization of time-evolving molecular dynamics structures. Analysis of the most probable allosteric coupling pathways between active site residues and the protein exterior is also presented.     

Influence of oligomerization on the dynamics of G-protein coupled receptors as assessed by normal mode analysis

The recently discovered impact of oligomerization on G-protein coupled receptor (GPCR) function further complicates the already challenging goal of unraveling the molecular and dynamic mechanisms of these receptors. To help understand the effect of oligomerization on the dynamics of GPCRs, we have compared the motion of monomeric, dimeric, and tetrameric arrangements of the prototypic GPCR rhodopsin, using an approximate-yet powerful-normal mode analysis (NMA) technique termed elastic network model (ENM). Moreover, we have used ENM to discriminate between putative dynamic mechanisms likely to account for the recently observed conformational rearrangement of the TM4,5-TM4,5 dimerization interface of GPCRs that occurs upon activation. Our results indicate: (1) significant perturbation of the normal modes (NMs) of the rhodopsin monomer upon oligomerization, which is mainly manifested at interfacial regions; (2) increased positive correlation among the transmembrane domains (TMs) and between the extracellular loop (EL) and TM regions of the rhodopsin protomer; (3) highest interresidue positive correlation at the interfaces between protomers; and (4) experimentally testable hypotheses of differential motional changes within different putative oligomeric arrangements.     

Close correspondence between the motions from principal component analysis of multiple HIV-1 protease structures and elastic network modes

The large number of available HIV-1 protease structures provides a remarkable sampling of conformations of the different conformational states, which can be viewed as direct structural information about the dynamics of the HIV-1 protease. After structure matching, we apply principal component analysis (PCA) to obtain the important apparent motions for both bound and unbound structures. There are significant similarities between the first few key motions and the first few low-frequency normal modes calculated from a static representative structure with an elastic network model (ENM), strongly suggesting that the variations among the observed structures and the corresponding conformational changes are facilitated by the low-frequency, global motions intrinsic to the structure. Similarities are also found when the approach is applied to an NMR ensemble, as well as to molecular dynamics (MD) trajectories. Thus, a sufficiently large number of experimental structures can directly provide important information about protein dynamics, but ENM can also provide similar sampling of conformations.     

The biological functions of low-frequency vibrations (phonons) 5. A phenomenological theory

Low-frequency internal motions of a biomacromolecule are thought to possess significant biological function from the dynamic point of view. In this paper, a general phenomenological theory is established by which it is clearly verified that low-frequency resonance plays a central role in the energy transmission required during the cooperative interaction between subunits in a protein oligomer. According to the present theory, it is found that the energy transmission between a pair of diagonal subunits in a protein oligomer with a polygon arrangement is the most efficient, so as to in a sense further predict that after a ligand is bound to a subunit by random collision, its diagonal subunit in the same protein oligomer will possess the greatest probability of binding with the next ligand. Furthermore, based on the concept of the 'resonance-controlled trigger' derived from the phenomenological theory, it is feasible to estimate the lower time limit of allosteric transition from one subunit to the other. Such a time limit depends on the dominant low-frequency mode of each subunit, the ratio of the coupling force constant to the corresponding inherent force constant, as well as the geometrical arrangement of subunits in a protein oligomer. So far none of the allosteric transitions observed in proteins has exceeded the time limit as defined here, indicating a logical consistency between our theory and the experiments.     

How well can we understand large-scale protein motions using normal modes of elastic network models?

In this article, we apply a coarse-grained elastic network model (ENM) to study conformational transitions to address the following questions: How well can a conformational change be predicted by the mode motions? Is there a way to improve the model to gain better results? To answer these questions, we use a dataset of 170 pairs having "open" and "closed" structures from Gerstein's protein motion database. Our results show that the conformational transitions fall into three categories: 1), the transitions of these proteins that can be explained well by ENM; 2), the transitions that are not explained well by ENM, but the results are significantly improved after considering the rigidity of some residue clusters and modeling them accordingly; and 3), the intrinsic nature of these transitions, specifically the low degree of collectivity, prevents their conformational changes from being represented well with the low frequency modes of any elastic network models. Our results thus indicate that the applicability of ENM for explaining conformational changes is not limited by the size of the studied protein or even the scale of the conformational change. Instead, it depends strongly on how collective the transition is.     

Thermodynamic features of myosin filament suspensions: implications for the modeling of muscle contraction.

The analysis of myosin filament suspensions shows that these solutions are characterized by highly nonideal behavior. From these data a model is constructed that allows us to predict that 1) when subjected to an increasing protein osmotic pressure, myosin filaments experience an elastic deformation, which is not linearly related to the acting force; and 2) at constant protein osmotic pressure, when the cross-bridges of the myosin filaments are subjected to an external, nonosmotic force parallel to the filament axis, they are deformed and the water activity coefficient is altered. As a consequence, in muscle, passive and active shortening of the sarcomere is expected to promote the change of the water-water and of the water-protein interactions. We thus propose to depict muscle contraction as a chemo-osmoelastic transduction, where the analysis of the energy partition during the power stroke requires consideration of the osmotic factor in addition to the chemoelastic ones.     

Conserved tertiary couplings stabilize elements in the PDZ fold,leading to characteristic patterns of domain conformational flexibility

Single‐domain allostery has been postulated to occur through intramolecular pathways of signaling within a protein structure. We had previously investigated these pathways by introducing a local thermal perturbation and analyzed the anisotropic propagation of structural changes throughout the protein. Here, we develop an improved approach, the Rotamerically Induced Perturbation (RIP), that identifies strong couplings between residues by analyzing the pathways of heat‐flow resulting from thermal excitation of rotameric rotations at individual residues. To explore the nature of these couplings, we calculate the complete coupling maps of 5 different PDZ domains. Although the PDZ domain is a well conserved structural fold that serves as a scaffold in many protein–protein complexes, different PDZ domains display unique patterns of conformational flexibility in response to ligand binding: some show a significant shift in a set of α‐helices, while others do not. Analysis of the coupling maps suggests a simple relationship between the computed couplings and observed conformational flexibility. In domains where the α‐helices are rigid, we find couplings of the α‐helices to the body of the protein, whereas in domains having ligand‐responsive α‐helices, no couplings are found. This leads to a model where the α‐helices are intrinsically dynamic but can be damped if sidechains interact at key tertiary contacts. These tertiary contacts correlate to high covariation contacts as identified by the statistical coupling analysis method. As these dynamic modules are exploited by various allosteric mechanisms, these tertiary contacts have been conserved by evolution.     

Molecular Dynamics Study of Naturally Existing Cavity Couplings in Proteins

Couplings between protein sub-structures are a common property of protein dynamics. Some of these couplings are especially interesting since they relate to function and its regulation. In this article we have studied the case of cavity couplings because cavities can host functional sites, allosteric sites, and are the locus of interactions with the cell milieu. We have divided this problem into two parts. In the first part, we have explored the presence of cavity couplings in the natural dynamics of 75 proteins, using 20 ns molecular dynamics simulations. For each of these proteins, we have obtained two trajectories around their native state. After applying a stringent filtering procedure, we found significant cavity correlations in 60% of the proteins. We analyze and discuss the structure origins of these correlations, including neighbourhood, cavity distance, etc. In the second part of our study, we have used longer simulations (≥100ns) from the MoDEL project, to obtain a broader view of cavity couplings, particularly about their dependence on time. Using moving window computations we explored the fluctuations of cavity couplings along time, finding that these couplings could fluctuate substantially during the trajectory, reaching in several cases correlations above 0.25/0.5. In summary, we describe the structural origin and the variations with time of cavity couplings. We complete our work with a brief discussion of the biological implications of these results.