Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

A molecular dynamics simulation study decodes the Zika virus NS5 methyltransferase bound to SAH and RNA analogue

Since 2015, widespread Zika virus outbreaks in Central and South America have caused increases in microcephaly cases, and this acute problem requires urgent attention. We employed molecular dynamics and Gaussian accelerated molecular dynamics techniques to investigate the structure of Zika NS5 protein with S-adenosyl-L-homocysteine (SAH) and an RNA analogue, namely 7-methylguanosine 5'-triphosphate (m7GTP). For the binding motif of Zika virus NS5 protein and SAH, we suggest that the four Zika NS5 substructures (residue orders: 101-112, 54-86, 127-136 and 146-161) and the residues (Ser56, Gly81, Arg84, Trp87, Thr104, Gly106, Gly107, His110, Asp146, Ile147, and Gly148) might be responsible for the selectivity of the new Zika virus drugs. For the binding motif of Zika NS5 protein and m7GTP, we suggest that the three Zika NS5 substructures (residue orders: 11-31, 146-161 and 207-218) and the residues (Asn17, Phe24, Lys28, Lys29, Ser150, Arg213, and Ser215) might be responsible for the selectivity of the new Zika virus drugs.

Dynamic Consequences of Mutation of Tryptophan 215 in Thrombin

Thrombin normally cleaves fibrinogen to promote coagulation; however, binding of thrombomodulin to thrombin switches the specificity of thrombin toward protein C, triggering the anticoagulation pathway. The W215A thrombin mutant was reported to have decreased activity toward fibrinogen without significant loss of activity toward protein C. To understand how mutation of Trp215 may alter thrombin specificity, hydrogen-deuterium exchange experiments (HDXMS), accelerated molecular dynamics (AMD) simulations, and activity assays were carried out to compare the dynamics of Trp215 mutants with those of wild type (WT) thrombin. Variation in NaCl concentration had no detectable effect on the sodium-binding (220s_CT) loop, but appeared to affect other surface loops. Trp215 mutants showed significant increases in amide exchange in the 170s_CT loop consistent with a loss of H-bonding in this loop identified by the AMD simulations. The W215A thrombin showed increased amide exchange in the 220s_CT loop and in the N-terminus of the heavy chain. The AMD simulations showed that a transient conformation of the W215A thrombin has a distorted catalytic triad. HDXMS experiments revealed that mutation of Phe227, which engages in a π-stacking interaction with Trp215, also caused significantly increased amide exchange in the 170s_CT loop. Activity assays showed that only the F227V mutant had wild type catalytic activity, whereas all other mutants showed markedly lower activity. Taken together, the results explain the reduced pro-coagulant activity of the W215A mutant and demonstrate the allosteric connection between Trp215, the sodium-binding loop, and the active site.

Computational Exploration of Conformational Transitions in Protein Drug Targets

Protein drug targets vary from highly structured to completely disordered; either way dynamics governs function. Hence, understanding the dynamical aspects of how protein targets function can enable improved interventions with drug molecules. Computational approaches offer highly detailed structural models of protein dynamics which are becoming more predictive as model quality and sampling power improve. However, the most advanced and popular models still have errors owing to imperfect parameter sets and often cannot access longer timescales of many crucial biological processes. Experimental approaches offer more certainty but can struggle to detect and measure lightly populated conformations of target proteins and subtle allostery. An emerging solution is to integrate available experimental data into advanced molecular simulations. In the future, molecular simulation in combination with experimental data may be able to offer detailed models of important drug targets such that improved functional mechanisms or selectivity can be accessed.

Elucidation of potential sites for antibody engineering by fluctuation editing

Target-specific monoclonal antibodies can be routinely acquired, but the sequences of naturally acquired antibodies are not always affinity-matured and methods that increase antigen affinity are desirable. Most biophysical studies have focused on the complementary determining region (CDR), which directly contacts the antigen; however, it remains difficult to increase the affinity as much as desired. While strategies to alter the CDR to increase antibody affinity are abundant, those that target non-CDR regions are scarce. Here we describe a new method, designated fluctuation editing, which identifies potential mutation sites and engineers a high-affinity antibody based on conformational fluctuations observed by NMR relaxation dispersion. Our data show that relaxation dispersion detects important fluctuating residues that are not located in the CDR and that increase antigen–antibody affinity by point mutation. The affinity-increased mutants are shown to fluctuate less in their free form and to form a more packed structure in their antigen-bound form.

Solution NMR views of dynamical ordering of biomacromolecules

BACKGROUND

To understand the mechanisms related to the 'dynamical ordering' of macromolecules and biological systems, it is crucial to monitor, in detail, molecular interactions and their dynamics across multiple timescales. Solution nuclear magnetic resonance (NMR) spectroscopy is an ideal tool that can investigate biophysical events at the atomic level, in near-physiological buffer solutions, or even inside cells.

SCOPE OF REVIEW

In the past several decades, progress in solution NMR has significantly contributed to the elucidation of three-dimensional structures, the understanding of conformational motions, and the underlying thermodynamic and kinetic properties of biomacromolecules. This review discusses recent methodological development of NMR, their applications and some of the remaining challenges.

MAJOR CONCLUSIONS

Although a major drawback of NMR is its difficulty in studying the dynamical ordering of larger biomolecular systems, current technologies have achieved considerable success in the structural analysis of substantially large proteins and biomolecular complexes over 1MDa and have characterised a wide range of timescales across which biomolecular motion exists. While NMR is well suited to obtain local structure information in detail, it contributes valuable and unique information within hybrid approaches that combine complementary methodologies, including solution scattering and microscopic techniques.

GENERAL SIGNIFICANCE

For living systems, the dynamic assembly and disassembly of macromolecular complexes is of utmost importance for cellular homeostasis and, if dysregulated, implied in human disease. It is thus instructive for the advancement of the study of the dynamical ordering to discuss the potential possibilities of solution NMR spectroscopy and its applications. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.

Calcium-Mediated Control of S100 Proteins: Allosteric Communication via an Agitator/Signal Blocking Mechanism

Allosteric proteins possess dynamically coupled residues for the propagation of input signals to distant target binding sites. The input signals usually correspond to "effector is present" or "effector is not present". Many aspects of allosteric regulation remain incompletely understood. This work focused on S100A11, a dimeric EF-hand protein with two hydrophobic target binding sites. An annexin peptide (Ax) served as the target. Target binding is allosterically controlled by Ca²⁺ over a distance of ∼26 Å. Ca²⁺ promotes formation of a [Ca₄ S100 Ax₂] complex, where the Ax peptides are accommodated between helices III/IV and III'/IV'. Without Ca²⁺ these binding sites are closed, precluding interactions with Ax. The allosteric mechanism was probed by microsecond MD simulations in explicit water, complemented by hydrogen exchange mass spectrometry (HDX/MS). Consistent with experimental data, MD runs in the absence of Ca²⁺ and Ax culminated in target binding site closure. In simulations on [Ca₄ S100] the target binding sites remained open. These results capture the essence of allosteric control, revealing how Ca²⁺ prevents binding site closure. Both HDX/MS and MD data showed that the metalation sites become more dynamic after Ca²⁺ loss. However, these enhanced dynamics do not represent the primary trigger of the allosteric cascade. Instead, a labile salt bridge acts as an incessantly active "agitator" that destabilizes the packing of adjacent residues, causing a domino chain of events that culminates in target binding site closure. This agitator represents the starting point of the allosteric signal propagation pathway. Ca²⁺ binding rigidifies elements along this pathway, thereby blocking signal transmission. This blocking mechanism does not conform to the commonly held view that allosteric communication pathways generally originate at the sites where effectors interact with the protein.

Gaussian Accelerated Molecular Dynamics: Theory, Implementation, and Applications

A novel Gaussian Accelerated Molecular Dynamics (GaMD) method has been developed for simultaneous unconstrained enhanced sampling and free energy calculation of biomolecules. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of the biomolecules. Furthermore, by constructing a boost potential that follows a Gaussian distribution, accurate reweighting of GaMD simulations is achieved via cumulant expansion to the second order. The free energy profiles obtained from GaMD simulations allow us to identify distinct low energy states of the biomolecules and characterize biomolecular structural dynamics quantitatively. In this chapter, we present the theory of GaMD, its implementation in the widely used molecular dynamics software packages (AMBER and NAMD), and applications to the alanine dipeptide biomolecular model system, protein folding, biomolecular large-scale conformational transitions and biomolecular recognition.

Understanding the molecular basis of agonist/antagonist mechanism of human mu opioid receptor through gaussian accelerated molecular dynamics method

The most powerful analgesic and addictive properties of opiate alkaloids are mediated by the μ opioid receptor (MOR). The MOR has been extensively investigated as a drug target in the twentieth century, with numerous compounds of varying efficacy being identified. We employed molecular dynamics and Gaussian accelerated molecular dynamics techniques to identify the binding mechanisms of MORs to BU72 (agonist) and β-funaltrexamine (antagonist). Our approach theoretically suggests that the 34 residues (Lys209–Phe221 and Ile301–Cys321) of the MORs were the key regions enabling the two compounds to bind to the active site of the MORs. When the MORs were in the holo form, the key region was in the open conformation. When the MORs were in the apo form, the key region was in the closed conformation. The key region might be responsible for the selectivity of new MOR agonists and antagonists.

Recent advances in measuring the kinetics of biomolecules by NMR relaxation dispersion spectroscopy

Protein function can be modulated or dictated by the amplitude and timescale of biomolecular motion, therefore it is imperative to study protein dynamics. Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful technique capable of studying timescales of motion that range from those faster than molecular reorientation on the picosecond timescale to those that occur in real-time. Across this entire regime, NMR observables can report on the amplitude of atomic motion, and the kinetics of atomic motion can be ascertained with a wide variety of experimental techniques from real-time to milliseconds and several nanoseconds to picoseconds. Still a four orders of magnitude window between several nanoseconds and tens of microseconds has remained elusive. Here, we highlight new relaxation dispersion NMR techniques that serve to cover this "hidden-time" window up to hundreds of nanoseconds that achieve atomic resolution while studying the molecule under physiological conditions.

Single Mutations Reshape the Structural Correlation Network of the DMXAA-Human STING Complex

Subtle changes in protein sequences are able to alter ligand-protein interactions. Unraveling the mechanism of such phenomena is important for understanding ligand-protein interactions, including the DMXAA-STING interaction. DMXAA specifically binds to mouse STING instead of human STING. However, the S162A mutation and a newly discovered E260I mutation endow human STING^AQ with DMXAA sensitivity. Through molecular dynamics simulations, we revealed how these single mutations alter the DMXAA-STING interaction. Compared to mutated systems, structural correlations in the interaction of STING^AQ with DMXAA are stronger, and the correlations are cross-protomers in the dimeric protein. Analyses on correlation coefficients lead to the identification of two key interactions that mediate the strong cross-protomer correlation in the DMXAA-STING^AQ interaction network: DMXAA-267T-162S* and 238R-260E*. These two interactions are partially and totally interrupted by the S162A and E260I mutations, respectively. Moreover, a smaller number of water molecules are displaced upon DMXAA binding to STING^AQ than that on binding to its mutants, leading to a larger entropic penalty for the former. Considering the sensitivity of STING^AQ and two of its mutants to DMXAA, a strong structural correlation appears to discourage DMXAA-STING binding. Such an observation suggests that DMXAA derivatives, which are deprived of hydrogen-bond interaction with both 162S* and 267T, are potential agonists of human STING.

Mutation of a kinase allosteric node uncouples dynamics linked to phosphotransfer

The expertise of protein kinases lies in their dynamic structure, wherein they are able to modulate cellular signaling by their phosphotransferase activity. Only a few hundreds of protein kinases regulate key processes in human cells, and protein kinases play a pivotal role in health and disease. The present study dwells on understanding the working of the protein kinase-molecular switch as an allosteric network of "communities" composed of congruently dynamic residues that make up the protein kinase core. Girvan-Newman algorithm-based community maps of the kinase domain of cAMP-dependent protein kinase A allow for a molecular explanation for the role of protein conformational entropy in its catalytic cycle. The community map of a mutant, Y204A, is analyzed vis-à-vis the wild-type protein to study the perturbations in its dynamic profile such that it interferes with transfer of the γ-phosphate to a protein substrate. Conventional biochemical measurements are used to ascertain the effect of these dynamic perturbations on the kinetic profiles of both proteins. These studies pave the way for understanding how mutations far from the kinase active site can alter its dynamic properties and catalytic function even when major structural perturbations are not obvious from static crystal structures.

NMR reveals a dynamic allosteric pathway in thrombin

Although serine proteases are found ubiquitously in both eukaryotes and prokaryotes, and they comprise the largest of all of the peptidase families, their dynamic motions remain obscure. The backbone dynamics of the coagulation serine protease, apo-thrombin (S195M-thrombin), were compared to the substrate-bound form (PPACK-thrombin). R₁, R₂, ¹⁵N-{¹H}NOEs, and relaxation dispersion NMR experiments were measured to capture motions across the ps to ms timescale. The ps-ns motions were not significantly altered upon substrate binding. The relaxation dispersion data revealed that apo-thrombin is highly dynamic, with μs-ms motions throughout the molecule. The region around the N-terminus of the heavy chain, the Na⁺-binding loop, and the 170 s loop, all of which are implicated in allosteric coupling between effector binding sites and the active site, were dynamic primarily in the apo-form. Most of the loops surrounding the active site become more ordered upon PPACK-binding, but residues in the N-terminal part of the heavy chain, the γ-loop, and anion-binding exosite 1, the main allosteric binding site, retain μs-ms motions. These residues form a dynamic allosteric pathway connecting the active site to the main allosteric site that remains in the substrate-bound form.

Unidirectional allostery in the regulatory subunit RIα facilitates efficient deactivation of protein kinase A

The holoenzyme complex of protein kinase A is in an inactive state; activation involves ordered cAMP binding to two tandem domains of the regulatory subunit and release of the catalytic subunit. Deactivation has been less studied, during which the two cAMPs unbind from the regulatory subunit to allow association of the catalytic subunit to reform the holoenzyme complex. Unbinding of the cAMPs appears ordered as indicated by a large difference in unbinding rates from the two sites, but the cause has remained elusive given the structural similarity of the two tandem domains. Even more intriguingly, NMR data show that allosteric communication between the two domains is unidirectional. Here, we present a mechanism for the unidirectionality, developed from extensive molecular dynamics simulations of the tandem domains in different cAMP-bound forms. Disparate responses to cAMP releases from the two sites (A and B) in conformational flexibility and chemical shift perturbation confirmed unidirectional allosteric communication. Community analysis revealed that the A-site cAMP, by forming across-domain interactions, bridges an essential pathway for interdomain communication. The pathway is impaired when this cAMP is removed but remains intact when only the B-site cAMP is removed. Specifically, removal of the A-site cAMP leads to the separation of the two domains, creating room for binding the catalytic subunit. Moreover, the A-site cAMP, by maintaining interdomain coupling, retards the unbinding of the B-site cAMP and stalls an unproductive pathway of cAMP release. Our work expands the perspective on allostery and implicates functional importance for the directionality of allostery.

Computational approaches to investigating allostery

Allosteric regulation plays a key role in many biological processes, such as signal transduction, transcriptional regulation, and many more. It is rooted in fundamental thermodynamic and dynamic properties of macromolecular systems that are still poorly understood and are moreover modulated by the cellular context. Here we review the computational approaches used in the investigation of allosteric processes in protein systems. We outline how the models of allostery have evolved from their initial formulation in the sixties to the current views, which more fully account for the roles of the thermodynamic and dynamic properties of the system. We then describe the major classes of computational approaches employed to elucidate the mechanisms of allostery, the insights they have provided, as well as their limitations. We complement this analysis by highlighting the role of computational approaches in promising practical applications, such as the engineering of regulatory modules and identifying allosteric binding sites.

Accelerated molecular dynamics simulations of ligand binding to a muscarinic G-protein-coupled receptor

Elucidating the detailed process of ligand binding to a receptor is pharmaceutically important for identifying druggable binding sites. With the ability to provide atomistic detail, computational methods are well poised to study these processes. Here, accelerated molecular dynamics (aMD) is proposed to simulate processes of ligand binding to a G-protein-coupled receptor (GPCR), in this case the M3 muscarinic receptor, which is a target for treating many human diseases, including cancer, diabetes and obesity. Long-timescale aMD simulations were performed to observe the binding of three chemically diverse ligand molecules: antagonist tiotropium (TTP), partial agonist arecoline (ARc) and full agonist acetylcholine (ACh). In comparison with earlier microsecond-timescale conventional MD simulations, aMD greatly accelerated the binding of ACh to the receptor orthosteric ligand-binding site and the binding of TTP to an extracellular vestibule. Further aMD simulations also captured binding of ARc to the receptor orthosteric site. Additionally, all three ligands were observed to bind in the extracellular vestibule during their binding pathways, suggesting that it is a metastable binding site. This study demonstrates the applicability of aMD to protein-ligand binding, especially the drug recognition of GPCRs.

Molecular Mechanism of Biased Ligand Conformational Changes in CC Chemokine Receptor 7

Biased ligand binding to G protein-coupled receptors enables functional selectivity of intracellular effectors to mediate cellular function. Despite the significant advances made in characterizing the conformational states (transmembrane helical arrangements) capable of discriminating between G protein and arrestin binding, the role of the ligand in stabilizing such conformations remains unclear. To address this issue, we simulate microsecond dynamics of CC chemokine receptor 7 (CCR7) bound to its native biased ligands, CCL19 and CCL21, and detect a series of molecular switches that are mediated by various ligand-induced allosteric events. These molecular switches involve three tyrosine residues (Y112(3.32), Y255(6.51), and Y288(7.39)), three phenylalanine residues (F116(3.36), F208(5.47), and F248(6.44)), and a polar interaction between Q252(6.48) and R294(7.45) in the transmembrane domain of CCR7. Conformational changes within these switches, particularly hydrogen bond formation between Y112(3.32) and Y255(6.51), lead to global helical movements in the receptor's transmembrane helices and contribute to the transitioning of the receptor to distinct states. Ligand-induced helical movements in the receptor highlight the ability of biased ligands to stabilize the receptor in different states through a dynamic network of allosteric events.

Allosteric Inhibition of Factor XIIIa. Non-Saccharide Glycosaminoglycan Mimetics, but Not Glycosaminoglycans, Exhibit Promising Inhibition Profile

Factor XIIIa (FXIIIa) is a transglutaminase that catalyzes the last step in the coagulation process. Orthostery is the only approach that has been exploited to design FXIIIa inhibitors. Yet, allosteric inhibition of FXIIIa is a paradigm that may offer a key advantage of controlled inhibition over orthosteric inhibition. Such an approach is likely to lead to novel FXIIIa inhibitors that do not carry bleeding risks. We reasoned that targeting a collection of basic amino acid residues distant from FXIIIa’s active site by using sulfated glycosaminoglycans (GAGs) or non-saccharide GAG mimetics (NSGMs) would lead to the discovery of the first allosteric FXIIIa inhibitors. We tested a library of 22 variably sulfated GAGs and NSGMs against human FXIIIa to discover promising hits. Interestingly, although some GAGs bound to FXIIIa better than NSGMs, no GAG displayed any inhibition. An undecasulfated quercetin analog was found to inhibit FXIIIa with reasonable potency (efficacy of 98%). Michaelis-Menten kinetic studies revealed an allosteric mechanism of inhibition. Fluorescence studies confirmed close correspondence between binding affinity and inhibition potency, as expected for an allosteric process. The inhibitor was reversible and at least 9-fold- and 26-fold selective over two GAG-binding proteins factor Xa (efficacy of 71%) and thrombin, respectively, and at least 27-fold selective over a cysteine protease papain. The inhibitor also inhibited the FXIIIa-mediated polymerization of fibrin in vitro. Overall, our work presents the proof-of-principle that FXIIIa can be allosterically modulated by sulfated non-saccharide agents much smaller than GAGs, which should enable the design of selective and safe anticoagulants.

Accelerated molecular dynamics simulations of the octopamine receptor using GPUs: discovery of an alternate agonist-binding position

Octopamine receptors (OARs) perform key biological functions in invertebrates, making this class of G-protein coupled receptors (GPCRs) worth considering for insecticide development. However, no crystal structures and very little research exists for OARs. Furthermore, GPCRs are large proteins, are suspended in a lipid bilayer, and are activated on the millisecond timescale, all of which make conventional molecular dynamics (MD) simulations infeasible, even if run on large supercomputers. However, accelerated Molecular Dynamics (aMD) simulations can reduce this timescale to even hundreds of nanoseconds, while running the simulations on graphics processing units (GPUs) would enable even small clusters of GPUs to have processing power equivalent to hundreds of CPUs. Our results show that aMD simulations run on GPUs can successfully obtain the active and inactive state conformations of a GPCR on this reduced timescale. Furthermore, we discovered a potential alternate active-state agonist-binding position in the octopamine receptor which has yet to be observed and may be a novel GPCR agonist-binding position. These results demonstrate that a complex biological system with an activation process on the millisecond timescale can be successfully simulated on the nanosecond timescale using a simple computing system consisting of a small number of GPUs. Proteins 2016; 84:1480-1489. © 2016 Wiley Periodicals, Inc.

Biophysical and computational methods to analyze amino acid interaction networks in proteins

Globular proteins are held together by interacting networks of amino acid residues. A number of different structural and computational methods have been developed to interrogate these amino acid networks. In this review, we describe some of these methods, including analyses of X-ray crystallographic data and structures, computer simulations, NMR data, and covariation among protein sequences, and indicate the critical insights that such methods provide into protein function. This information can be leveraged towards the design of new allosteric drugs, and the engineering of new protein function and protein regulation strategies.

Detecting Allosteric Networks Using Molecular Dynamics Simulation

Allosteric networks allow enzymes to transmit information and regulate their catalytic activities over vast distances. In principle, molecular dynamics (MD) simulations can be used to reveal the mechanisms that underlie this phenomenon; in practice, it can be difficult to discern allosteric signals from MD trajectories. Here, we describe how MD simulations can be analyzed to reveal correlated motions and allosteric networks, and provide an example of their use on the coagulation enzyme thrombin. Methods are discussed for calculating residue-pair correlations from atomic fluctuations and mutual information, which can be combined with contact information to identify allosteric networks and to dynamically cluster a system into highly correlated communities. In the case of thrombin, these methods show that binding of the antagonist hirugen significantly alters the enzyme's correlation landscape through a series of pathways between Exosite I and the catalytic core. Results suggest that hirugen binding curtails dynamic diversity and enforces stricter venues of influence, thus reducing the accessibility of thrombin to other molecules.

Dabigatran and Argatroban Diametrically Modulate Thrombin Exosite Function

Thrombin is a highly plastic molecule whose activity and specificity are regulated by exosites 1 and 2, positively-charged domains that flank the active site. Exosite binding by substrates and cofactors regulates thrombin activity by localizing thrombin, guiding substrates, and by inducing allosteric changes at the active site. Although inter-exosite and exosite-to-active-site allostery have been demonstrated, the impact of active site ligation on exosite function has not been examined. To address this gap, we used surface plasmon resonance to determine the effects of dabigatran and argatroban, active site-directed inhibitors, on thrombin binding to immobilized γ_A/γ_A-fibrin or glycoprotein Ibα peptide via exosite 1 and 2, respectively, and thrombin binding to γ_A/γ′-fibrin or factor Va, which is mediated by both exosites. Whereas dabigatran attenuated binding, argatroban increased thrombin binding to γ_A/γ_A- and γ_A/γ′-fibrin and to factor Va. The results with immobilized fibrin were confirmed by examining the binding of radiolabeled thrombin to fibrin clots. Thus, dabigatran modestly accelerated the dissociation of thrombin from γ_A/γ_A-fibrin clots, whereas argatroban attenuated dissociation. Dabigatran had no effect on thrombin binding to glycoprotein Ibα peptide, whereas argatroban promoted binding. These findings not only highlight functional effects of thrombin allostery, but also suggest that individual active site-directed thrombin inhibitors uniquely modulate exosite function, thereby identifying potential novel mechanisms of action.

Bioactive Anti-Thrombotic Modification of Decellularized Matrix for Vascular Applications

The decellularized matrix derived from porcine small intestinal submucosa (SIS) is a widely used biomaterial being investigated for numerous applications. Currently, thrombus deposition and neointimal hyperplasia have limited the use of SIS in some vascular applications. To limit these detrimental processes, this work applies bioactive, endothelial-inspired properties to the material. SIS is modified with the endothelial cell membrane protein thrombomodulin and the glycosaminoglycan heparin to facilitate protein C activation and anticoagulant activity, respectively. Modifying SIS with thrombomodulin alone enables robust activated protein C (APC) generation, and thrombomodulin activity is maintained after prolonged exposure to fluid shear and blood plasma. Heparin-modified SIS has a potent anticoagulant activity. When both modifications are applied sequentially, SIS modified first with thrombomodulin then with heparin retains the full activity of each individual modification. Tubular SIS devices are connected to a baboon arteriovenous shunt to quantify thrombus deposition on these materials. After being exposed to flowing whole blood for 60 min, SIS devices modified first with thrombomodulin then with heparin have significantly less platelet accumulation compared to unmodified SIS devices. These studies demonstrate that modifying SIS with thrombomodulin and heparin confers APC generation and anticoagulant activity that results in reduced thrombogenesis.

Identifying Allosteric Hotspots with Dynamics: Application to Inter- and Intra-species Conservation

The rapidly growing volume of data being produced by next-generation sequencing initiatives is enabling more in-depth analyses of conservation than previously possible. Deep sequencing is uncovering disease loci and regions under selective constraint, despite the fact that intuitive biophysical reasons for such constraint are sometimes absent. Allostery may often provide the missing explanatory link. We use models of protein conformational change to identify allosteric residues by finding essential surface pockets and information-flow bottlenecks, and we develop a software tool that enables users to perform this analysis on their own proteins of interest. Though fundamentally 3D-structural in nature, our analysis is computationally fast, thereby allowing us to run it across the PDB and to evaluate general properties of predicted allosteric residues. We find that these tend to be conserved over diverse evolutionary time scales. Finally, we highlight examples of allosteric residues that help explain poorly understood disease-associated variants.

Rapid Characterization of Allosteric Networks with Ensemble Normal Mode Analysis

Allosteric regulation is a primary means of controlling protein function. By definition, allostery involves the propagation of structural dynamic changes between distal protein sites that yields a functional change. Gaining improved knowledge of these fundamental mechanisms is important for understanding many biomolecular processes and for guiding protein engineering and drug design efforts. In this work we compare and contrast a range of normal mode analysis (NMA) approaches together with network analysis for the prediction of structural dynamics and allosteric sites. Application to heterotrimeric G proteins, hemoglobin, and caspase 7 indicates that atomistic elastic network models provide improved predictions of experimental allosteric mutation sites. Results for G proteins also display an improved consistency with those derived from more computationally demanding MD simulations. Application of this approach across available experimental structures for a given protein family in a unified manner, that we refer to as ensemble NMA, yields the best overall predictive performance. We propose that this atomistic ensemble NMA approach represents an efficient and powerful tool for guiding the exploration of coupled motions and allosteric mechanisms in cases where multiple structures are available and where MD may prove prohibitively expensive.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Dynamical network of residue-residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation

Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue-residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general.

Timing Correlations in Proteins Predict Functional Modules and Dynamic Allostery

How protein structure encodes functionality is not fully understood. For example, long-range intraprotein communication can occur without measurable conformational change and is often not captured by existing structural correlation functions. It is shown here that important functional information is encoded in the timing of protein motions, rather than motion itself. I introduce the conditional activity function to quantify such timing correlations among the degrees of freedom within proteins. For three proteins, the conditional activities between side-chain dihedral angles were computed using the output of microseconds-long atomistic simulations. The new approach demonstrates that a sparse fraction of side-chain pairs are dynamically correlated over long distances (spanning protein lengths up to 7 nm), in sharp contrast to structural correlations, which are short-ranged (<1 nm). Regions of high self- and inter-side-chain dynamical correlations are found, corresponding to experimentally determined functional modules and allosteric connections, respectively.

Controlling Allosteric Networks in Proteins

Allosteric transition, defined as conformational changes induced by ligand binding, is one of the fundamental properties of proteins. Allostery has been observed and characterized in many proteins, and has been recently utilized to control protein function via regulation of protein activity. Here, we review the physical and evolutionary origin of protein allostery, as well as its importance to protein regulation, drug discovery, and biological processes in living systems. We describe recently developed approaches to identify allosteric pathways, connected sets of pairwise interactions that are responsible for propagation of conformational change from the ligand-binding site to a distal functional site. We then present experimental and computational protein engineering approaches for control of protein function by modulation of allosteric sites. As an example of application of these approaches, we describe a synergistic computational and experimental approach to rescue the cystic-fibrosis-associated protein cystic fibrosis transmembrane conductance regulator, which upon deletion of a single residue misfolds and causes disease. This example demonstrates the power of allosteric manipulation in proteins to both elucidate mechanisms of molecular function and to develop therapeutic strategies that rescue those functions. Allosteric control of proteins provides a tool to shine a light on the complex cascades of cellular processes and facilitate unprecedented interrogation of biological systems.

Protein Allostery and Conformational Dynamics

The functions of many proteins are regulated through allostery, whereby effector binding at a distal site changes the functional activity (e.g., substrate binding affinity or catalytic efficiency) at the active site. Most allosteric studies have focused on thermodynamic properties, in particular, substrate binding affinity. Changes in substrate binding affinity by allosteric effectors have generally been thought to be mediated by conformational transitions of the proteins or, alternatively, by changes in the broadness of the free energy basin of the protein conformational state without shifting the basin minimum position. When effector binding changes the free energy landscape of a protein in conformational space, the change affects not only thermodynamic properties but also dynamic properties, including the amplitudes of motions on different time scales and rates of conformational transitions. Here we assess the roles of conformational dynamics in allosteric regulation. Two cases are highlighted where NMR spectroscopy and molecular dynamics simulation have been used as complementary approaches to identify residues possibly involved in allosteric communication. Perspectives on contentious issues, for example, the relationship between picosecond-nanosecond local and microsecond-millisecond conformational exchange dynamics, are presented.

General trends of dihedral conformational transitions in a globular protein

Dihedral conformational transitions are analyzed systematically in a model globular protein, cytochrome P450cam, to examine their structural and chemical dependences through combined conventional molecular dynamics (cMD), accelerated molecular dynamics (aMD) and adaptive biasing force (ABF) simulations. The aMD simulations are performed at two acceleration levels, using dihedral and dual boost, respectively. In comparison with cMD, aMD samples protein dihedral transitions approximately two times faster on average using dihedral boost, and ∼ 3.5 times faster using dual boost. In the protein backbone, significantly higher dihedral transition rates are observed in the bend, coil, and turn flexible regions, followed by the β bridge and β sheet, and then the helices. Moreover, protein side chains of greater length exhibit higher transition rates on average in the aMD-enhanced sampling. Side chains of the same length (particularly Nχ = 2) exhibit decreasing transition rates with residues when going from hydrophobic to polar, then charged and aromatic chemical types. The reduction of dihedral transition rates is found to be correlated with increasing energy barriers as identified through ABF free energy calculations. These general trends of dihedral conformational transitions provide important insights into the hierarchical dynamics and complex free energy landscapes of functional proteins.

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Dynamic Coupling and Allosteric Networks in the α Subunit of Heterotrimeric G Proteins

G protein α subunits cycle between active and inactive conformations to regulate a multitude of intracellular signaling cascades. Important structural transitions occurring during this cycle have been characterized from extensive crystallographic studies. However, the link between observed conformations and the allosteric regulation of binding events at distal sites critical for signaling through G proteins remain unclear. Here we describe molecular dynamics simulations, bioinformatics analysis, and experimental mutagenesis that identifies residues involved in mediating the allosteric coupling of receptor, nucleotide, and helical domain interfaces of Gαi. Most notably, we predict and characterize novel allosteric decoupling mutants, which display enhanced helical domain opening, increased rates of nucleotide exchange, and constitutive activity in the absence of receptor activation. Collectively, our results provide a framework for explaining how binding events and mutations can alter internal dynamic couplings critical for G protein function.

Thrombomodulin Binding Selects the Catalytically Active Form of Thrombin

Human α-thrombin is a serine protease with dual functions. Thrombin acts as a procoagulant, cleaving fibrinogen to make the fibrin clot, but when bound to thrombomodulin (TM), it acts as an anticoagulant, cleaving protein C. A minimal TM fragment consisting of the fourth, fifth, and most of the sixth EGF-like domain (TM456m) that has been prepared has much improved solubility, thrombin binding capacity, and anticoagulant activity versus those of previous TM456 constructs. In this work, we compare backbone amide exchange of human α-thrombin in three states: apo, D-Phe-Pro-Arg-chloromethylketone (PPACK)-bound, and TM456m-bound. Beyond causing a decreased level of amide exchange at their binding sites, TM and PPACK both cause a decreased level of amide exchange in other regions including the γ-loop and the adjacent N-terminus of the heavy chain. The decreased level of amide exchange in the N-terminus of the heavy chain is consistent with the historic model of activation of serine proteases, which involves insertion of this region into the β-barrel promoting the correct conformation of the catalytic residues. Contrary to crystal structures of thrombin, hydrogen-deuterium exchange mass spectrometry results suggest that the conformation of apo-thrombin does not yet have the N-terminus of the heavy chain properly inserted for optimal catalytic activity, and that binding of TM allosterically promotes the catalytically active conformation.

Kinesin-5 allosteric inhibitors uncouple the dynamics of nucleotide, microtubule, and neck-linker binding sites

Kinesin motor domains couple cycles of ATP hydrolysis to cycles of microtubule binding and conformational changes that result in directional force and movement on microtubules. The general principles of this mechanochemical coupling have been established; however, fundamental atomistic details of the underlying allosteric mechanisms remain unknown. This lack of knowledge hampers the development of new inhibitors and limits our understanding of how disease-associated mutations in distal sites can interfere with the fidelity of motor domain function. Here, we combine unbiased molecular-dynamics simulations, bioinformatics analysis, and mutational studies to elucidate the structural dynamic effects of nucleotide turnover and allosteric inhibition of the kinesin-5 motor. Multiple replica simulations of ATP-, ADP-, and inhibitor-bound states together with network analysis of correlated motions were used to create a dynamic protein structure network depicting the internal dynamic coordination of functional regions in each state. This analysis revealed the intervening residues involved in the dynamic coupling of nucleotide, microtubule, neck-linker, and inhibitor binding sites. The regions identified include the nucleotide binding switch regions, loop 5, loop 7, α4-α5-loop 13, α1, and β4-β6-β7. Also evident were nucleotide- and inhibitor-dependent shifts in the dynamic coupling paths linking functional sites. In particular, inhibitor binding to the loop 5 region affected β-sheet residues and α1, leading to a dynamic decoupling of nucleotide, microtubule, and neck-linker binding sites. Additional analyses of point mutations, including P131 (loop 5), Q78/I79 (α1), E166 (loop 7), and K272/I273 (β7) G325/G326 (loop 13), support their predicted role in mediating the dynamic coupling of distal functional surfaces. Collectively, our results and approach, which we make freely available to the community, provide a framework for explaining how binding events and point mutations can alter dynamic couplings that are critical for kinesin motor domain function.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.

MDN: A Web Portal for Network Analysis of Molecular Dynamics Simulations

We introduce a web portal that employs network theory for the analysis of trajectories from molecular dynamics simulations. Users can create protein energy networks following methodology previously introduced by our group, and can identify residues that are important for signal propagation, as well as measure the efficiency of signal propagation by calculating the network coupling. This tool, called MDN, was used to characterize signal propagation in Escherichia coli heat-shock protein 70-kDa. Two variants of this protein experimentally shown to be allosterically active exhibit higher network coupling relative to that of two inactive variants. In addition, calculations of partial coupling suggest that this quantity could be used as part of the criteria to determine pocket druggability in drug discovery studies.

Accelerated molecular dynamics simulations of protein folding

Folding of four fast-folding proteins, including chignolin, Trp-cage, villin headpiece and WW domain, was simulated via accelerated molecular dynamics (aMD). In comparison with hundred-of-microsecond timescale conventional molecular dynamics (cMD) simulations performed on the Anton supercomputer, aMD captured complete folding of the four proteins in significantly shorter simulation time. The folded protein conformations were found within 0.2-2.1 Å of the native NMR or X-ray crystal structures. Free energy profiles calculated through improved reweighting of the aMD simulations using cumulant expansion to the second-order are in good agreement with those obtained from cMD simulations. This allows us to identify distinct conformational states (e.g., unfolded and intermediate) other than the native structure and the protein folding energy barriers. Detailed analysis of protein secondary structures and local key residue interactions provided important insights into the protein folding pathways. Furthermore, the selections of force fields and aMD simulation parameters are discussed in detail. Our work shows usefulness and accuracy of aMD in studying protein folding, providing basic references in using aMD in future protein-folding studies.

AIM for Allostery: Using the Ising Model to Understand Information Processing and Transmission in Allosteric Biomolecular Systems

In performing their biological functions, molecular machines must process and transmit information with high fidelity. Information transmission requires dynamic coupling between the conformations of discrete structural components within the protein positioned far from one another on the molecular scale. This type of biomolecular “action at a distance” is termed allostery. Although allostery is ubiquitous in biological regulation and signal transduction, its treatment in theoretical models has mostly eschewed quantitative descriptions involving the system's underlying structural components and their interactions. Here, we show how Ising models can be used to formulate an approach to allostery in a structural context of interactions between the constitutive components by building simple allosteric constructs we termed Allosteric Ising Models (AIMs). We introduce the use of AIMs in analytical and numerical calculations that relate thermodynamic descriptions of allostery to the structural context, and then show that many fundamental properties of allostery, such as the multiplicative property of parallel allosteric channels, are revealed from the analysis of such models. The power of exploring mechanistic structural models of allosteric function in more complex systems by using AIMs is demonstrated by building a model of allosteric signaling for an experimentally well-characterized asymmetric homodimer of the dopamine D2 receptor.

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([(35)S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.

Using modern tools to probe the structure-function relationship of fatty acid synthases

Fatty acid biosynthesis is essential to life and represents one of the most conserved pathways in nature, preserving the same handful of chemical reactions across all species. Recent interest in the molecular details of the de novo fatty acid synthase (FAS) has been heightened by demand for renewable fuels and the emergence of multidrug-resistant bacterial strains. Central to FAS is the acyl carrier protein (ACP), a protein chaperone that shuttles the growing acyl chain between catalytic enzymes within the FAS. Human efforts to alter fatty acid biosynthesis for oil production, chemical feedstock, or antimicrobial purposes has been met with limited success, due in part to a lack of detailed molecular information behind the ACP-partner protein interactions inherent to the pathway. This review will focus on recently developed tools for the modification of ACP and analysis of protein-protein interactions, such as mechanism-based crosslinking, and the studies exploiting them. Discussion specific to each enzymatic domain will focus first on mechanism and known inhibitors, followed by available structures and known interactions with ACP. Although significant unknowns remain, new understandings of the intricacies of FAS point to future advances in manipulating this complex molecular factory.

Tissue factor activates allosteric networks in factor VIIa through structural and dynamic changes

BACKGROUND

Tissue factor (TF) promotes colocalization of enzyme (factor VIIa) and substrate (FX or FIX), and stabilizes the active conformation of FVIIa. Details on how TF induces structural and dynamic changes in the catalytic domain of FVIIa to enhance its efficiency remain elusive.

OBJECTIVE

To elucidate the activation of allosteric networks in the catalytic domain of the FVIIa protease it is when bound to TF.

METHODS

Long-timescale molecular dynamics simulations of FVIIa, free and in complex with TF, were executed and analyzed by dynamic network analysis.

RESULTS

Allosteric paths of correlated motion from the TF contact point, Met306, in FVIIa to the active site triad can be described and quantified. In particular, the shortest paths from Met306 to Ser344 and His193 are 16% and 8% longer in free FVIIa than in TF-FVIIa, and they encompass previously undiscovered residue-residue interactions that are not likely to be inferred from mutagenesis studies. Furthermore, paths from Met306 to Ile153 (N-terminus) and Trp364, both representing hallmark residues of allostery, are 7% and 37% longer, respectively, in free FVIIa. Thus, there is significantly weaker coupling between the TF contact point and key residues in the catalytic domain of FVIIa, causing the active site triad to disintegrate in the simulation when TF is not present.

CONCLUSIONS

These findings complement our current understanding of how the protease FVIIa is stimulated by TF. We demonstrate allosteric networks in the catalytic domain that are activated by TF and help to make FVIIa an efficient catalyst of FIX and FX activation.