Using Structural Kinetic Modeling To Identify Key Determinants of Stability in Reaction Networks.

Kinetic modeling is increasingly used to understand the reaction dynamics of metabolic systems. However, one major drawback of kinetic modeling is that appropriate rate parameters required to implement such models are often unavailable. To circumvent this limitation, an approach known as structural kinetic modeling was developed as a way to understand the dynamics of reaction networks without explicitly requiring rate parameters. This study describes a novel approach to use structural kinetic modeling to identify reaction components that contribute most significantly to mediating network stability. We applied this method to analyze the metabolic pathway of glycolysis in yeast. As a result, we identified specific metabolic components that contribute most significantly to defining the stability properties of the glycolysis reaction network and predict the responses of these components to perturbations. These results were validated via comparison to a conventional kinetic model of glycolysis. Thus, applying our approach allows more detailed information about the stability and dynamics of the metabolic network to now be accessible without requiring rate parameters. We anticipate that this method can focus efforts of experimental studies by identifying the susceptibility of reaction components to metabolic engineering. The approach may be applied to a variety of complex reaction networks.

Molecular simulations to delineate functional conformational transitions in the HCV polymerase.

Hepatitis C virus (HCV) is a global health concern for which there is no vaccine available. The HCV polymerase is responsible for the critical function of replicating the RNA genome of the virus. Transitions between at least two conformations (open and closed) are necessary to allow the enzyme to replicate RNA. In this study, molecular dynamic simulations were initiated from multiple crystal structures to understand the free energy landscape (FEL) explored by the enzyme as it interconverts between these conformations. Our studies reveal the location of distinct states within the FEL as well as the molecular interactions associated with these states. Specific hydrogen bonds appear to play a key role in modulating conformational transitions. This knowledge is essential to elucidate the role of these conformations in replication and may also be valuable in understanding the basis by which this enzyme is inhibited by small molecules. © 2016 Wiley Periodicals, Inc.

Computational predictions suggest that structural similarity in viral polymerases may lead to comparable allosteric binding sites.

The identification of ligand-binding sites is often the first step in drug targeting and design. To date there are numerous computational tools available to predict ligand binding sites. These tools can guide or mitigate the need for experimental methods to identify binding sites, which often require significant resources and time. Here, we evaluate four ligand-binding site predictor (LBSP) tools for their ability to predict allosteric sites within the Hepatitis C Virus (HCV) polymerase. Our results show that the LISE LBSP is able to identify all three target allosteric sites within the HCV polymerase as well as a known allosteric site in the Coxsackievirus polymerase. LISE was then employed to identify novel binding sites within the polymerases of the Dengue, West Nile, and Foot-and-mouth Disease viruses. Our results suggest that all three viral polymerases have putative sites that share structural or chemical similarities with allosteric pockets of the HCV polymerase. Thus, these binding locations may represent an evolutionarily conserved structural feature of several viral polymerases that could be exploited for the development of small molecule therapeutics.

Using the Hepatitis C Virus RNA-Dependent RNA Polymerase as a Model to Understand Viral Polymerase Structure, Function and Dynamics.

Viral polymerases replicate and transcribe the genomes of several viruses of global health concern such as Hepatitis C virus (HCV), human immunodeficiency virus (HIV) and Ebola virus. For this reason they are key targets for therapies to treat viral infections. Although there is little sequence similarity across the different types of viral polymerases, all of them present a right-hand shape and certain structural motifs that are highly conserved. These features allow their functional properties to be compared, with the goal of broadly applying the knowledge acquired from studying specific viral polymerases to other viral polymerases about which less is known. Here we review the structural and functional properties of the HCV RNA-dependent RNA polymerase (NS5B) in order to understand the fundamental processes underlying the replication of viral genomes. We discuss recent insights into the process by which RNA replication occurs in NS5B as well as the role that conformational changes play in this process.

Dual Allosteric Inhibitors Jointly Modulate Protein Structure and Dynamics in the Hepatitis C Virus Polymerase.

The hepatitis C virus (HCV) infects close to 200 million people globally, resulting in a significant need for effective HCV therapies. The HCV polymerase (gene product NS5B) is a valuable target for therapeutics because of its role in replicating the viral genome. Various studies have identified inhibitors for this enzyme, including non-nucleoside inhibitors (NNIs) that bind distal to the enzyme active site. Recently, it has been shown that simultaneously challenging the enzyme with two NNIs results in enhanced inhibition relative to that observed after challenge with individual inhibitors, suggesting that employing multiple NNIs might be the basis of more effective therapeutics. Nevertheless, the molecular mechanisms responsible for this enhanced inhibition remain unclear. We employ molecular dynamics simulations to determine the origin of enhanced inhibition when two NNIs bind to NS5B. Our results suggest that nonoverlapping NNI sites are compatible with simultaneous binding of dual NNIs. We observe that both inhibitors act in concert to induce novel enzyme conformations and dynamics, allowing us to identify molecular mechanisms underlying enhanced inhibition of NS5B. This knowledge will be useful in optimizing combinations of NNIs to target NS5B, helping to prevent the acquisition of viral resistance that remains a significant barrier to the development of HCV therapeutics.

Allosteric inhibitors have distinct effects, but also common modes of action, in the HCV polymerase.

The RNA-dependent RNA polymerase from the Hepatitis C Virus (gene product NS5B) is a validated drug target because of its critical role in genome replication. There are at least four distinct allosteric sites on the polymerase to which several small molecule inhibitors bind. In addition, numerous crystal structures have been solved with different allosteric inhibitors bound to the polymerase. However, the molecular mechanisms by which these small molecules inhibit the enzyme have not been fully elucidated. There is evidence that allosteric inhibitors alter the intrinsic motions and distribution of conformations sampled by the enzyme. In this study we use molecular dynamics simulations to understand the structural and dynamic changes that result when inhibitors are bound at three different allosteric binding sites on the enzyme. We observe that ligand binding at each site alters the structure and dynamics of NS5B in a distinct manner. Nonetheless, our studies also highlight commonalities in the mechanisms of action of the different inhibitors. Each inhibitor alters the conformational states sampled by the enzyme, either by rigidifying the enzyme and preventing transitions between functional conformational states or by destabilizing the enzyme and preventing functionally relevant conformations from being adequately sampled. By illuminating the molecular mechanisms of allosteric inhibition, these studies delineate the intrinsic functional properties of the enzyme and pave the way for designing novel and more effective polymerase inhibitors. This information may also be important to understand how allosteric regulation occurs in related viral polymerases and other enzymes.

Molecular simulations illuminate the role of regulatory components of the RNA polymerase from the hepatitis C virus in influencing protein structure and dynamics.

The RNA polymerase (gene product NS5B) from the hepatitis C virus is responsible for replication of the viral genome and is a validated drug target for new therapeutic agents. NS5B has a structure resembling an open right hand (containing the fingers, palm, and thumb subdomains), a hydrophobic C-terminal region, and two magnesium ions coordinated in the palm domain. Biochemical data suggest that the magnesium ions provide structural stability and are directly involved in catalysis, while the C-terminus plays a regulatory role in NS5B function. Nevertheless, the molecular mechanisms by which these two features regulate polymerase activity remain unclear. To answer this question, we performed molecular dynamics simulations of NS5B variants with different C-terminal lengths in the presence or absence of magnesium ions to determine the impact on enzyme properties. We observed that metal binding increases both the magnitude and the degree of correlated enzyme motions. In contrast, we observed that the C-terminus restricts enzyme dynamics. Under certain conditions, our simulations revealed a fully closed conformation of NS5B that may facilitate de novo initiation of RNA replication. This knowledge is important because it fosters the development of a comprehensive description of RNA replication by NS5B and is relevant to understanding the functional properties of a broad class of related RNA polymerases such as 3D-pol from poliovirus. Ultimately, this information may also be pertinent to designing novel NS5B therapeutics.

Inhibitors for the hepatitis C virus RNA polymerase explored by SAR with advanced machine learning methods.

Hepatitis C virus (HCV) is a global health challenge, affecting approximately 200 million people worldwide. In this study we developed SAR models with advanced machine learning classifiers Random Forest and k Nearest Neighbor Simulated Annealing for 679 small molecules with measured inhibition activity for NS5B genotype 1b. The activity was expressed as a binary value (active/inactive), where actives were considered molecules with IC50 ≤0.95 µM. We applied our SAR models to various drug-like databases and identified novel chemical scaffolds for NS5B inhibitors. Subsequent in vitro antiviral assays suggested a new activity for an existing prodrug, Candesartan cilexetil, which is currently used to treat hypertension and heart failure but has not been previously tested for anti-HCV activity. We also identified NS5B inhibitors with two novel non-nucleoside chemical motifs.

Thumb inhibitor binding eliminates functionally important dynamics in the hepatitis C virus RNA polymerase.

Hepatitis C virus (HCV) has infected almost 200 million people worldwide, typically causing chronic liver damage and severe complications such as liver failure. Currently, there are few approved treatments for viral infection. Thus, the HCV RNA-dependent RNA polymerase (gene product NS5B) has emerged as an important target for small molecule therapeutics. Potential therapeutic agents include allosteric inhibitors that bind distal to the enzyme active site. While their mechanism of action is not conclusively known, it has been suggested that certain inhibitors prevent a conformational change in NS5B that is crucial for RNA replication. To gain insight into the molecular origin of long-range allosteric inhibition of NS5B, we employed molecular dynamics simulations of the enzyme with and without an inhibitor bound to the thumb domain. These studies indicate that the presence of an inhibitor in the thumb domain alters both the structure and internal motions of NS5B. Principal components analysis identified motions that are severely attenuated by inhibitor binding. These motions may have functional relevance by facilitating interactions between NS5B and RNA template or nascent RNA duplex, with presence of the ligand leading to enzyme conformations with narrower and thus less accessible RNA binding channels. This study provides the first evidence for a mechanistic basis of allosteric inhibition in NS5B. Moreover, we present evidence that allosteric inhibition of NS5B results from intrinsic features of the enzyme free energy landscape, suggesting a common mechanism for the action of diverse allosteric ligands.

Exploration of transferability in multiscale coarse-grained peptide models.

Coarse-grained models can facilitate the efficient simulation of complex biological systems. In earlier studies the multiscale coarse-graining (MS-CG) method was employed to examine the folding landscape for two small peptides. In those studies, MS-CG force fields specific to each peptide were employed. We extend here the scope of that work with the goal of obtaining a transferable MS-CG force field which can be used to simulate the folded conformations of peptides with disparate structural motifs. Information obtained via MS-CG modeling was used to understand the characteristics of CG interactions which govern their capacity to be transferred between different peptide systems. We find that polar CG groups are least transferable in general, with interactions between CG sites representing the CO and NH groups on the peptide backbone being particularly resistant to facile transfer. Our results additionally suggest that, while there are limitations to the approach, the MS-CG method may provide a systematic path toward obtaining rigorously defined CG interactions with at least some degree of transferability. These studies also indicate that it may be possible to enhance the transferability of the MS-CG approach by identifying novel ways to combine information from different MS-CG force fields.

Conformational switching between protein substates studied with 2D IR vibrational echo spectroscopy and molecular dynamics simulations.

Myoglobin is an important protein for the study of structure and dynamics. Three conformational substates have been identified for the carbonmonoxy form of myoglobin (MbCO). These are manifested as distinct peaks in the IR absorption spectrum of the CO stretching mode. Ultrafast 2D IR vibrational echo chemical exchange experiments are used to observed switching between two of these substates, A(1) and A(3), on a time scale of <100 ps for two mutants of wild-type Mb. The two mutants are a single mutation of Mb, L29I, and a double mutation, T67R/S92D. Molecular dynamics (MD) simulations are used to model the structural differences between the substates of the two MbCO mutants. The MD simulations are also employed to examine the substate switching in the two mutants as a test of the ability of MD simulations to predict protein dynamics correctly for a system in which there is a well-defined transition over a significant potential barrier between two substates. For one mutant, L29I, the simulations show that translation of the His64 backbone may differentiate the two substates. The simulations accurately reproduce the experimentally observed interconversion time for the L29I mutant. However, MD simulations exploring the same His64 backbone coordinate fail to display substate interconversion for the other mutant, T67R/S92D, thus pointing to the likely complexity of the underlying protein interactions. We anticipate that understanding conformational dynamics in MbCO via ultrafast 2D IR vibrational echo chemical exchange experiments can help to elucidate fast conformational switching processes in other proteins.

Molecular description of flexibility in an antibody combining site.

Mature antibodies (Abs) that are exquisitely specific for virtually any foreign molecule may be produced by affinity maturation of naïve (or germline) Abs. However, the finite number of germline Abs available suggests that, in contrast to mature Abs, germline Abs must be broadly polyspecific so that they are able to recognize a wide range of ligands. Thus, affinity maturation must play a role in mediating Ab specificity. One biophysical property that distinguishes polyspecificity from specificity is protein flexibility; a flexible combining site is able to adopt different conformations that recognize different foreign molecules (or antigens), while a rigid combining site is locked into a conformation that is specific for a given antigen. Recent studies (Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 8821-8826) have examined, at the atomic level, the structural properties that mediate changes in flexibility at four stages of affinity maturation in the 4-4-20 Ab. These studies employed molecular dynamics simulations to reveal a network of residue interactions that mediate the flexibility changes accompanying maturation. The flexibility of the Ab combining sites in these molecular systems was originally measured using three-pulse photon echo spectroscopy (3PEPS). The present investigation extends this work by providing a concrete link between structural properties of the Ab molecules and features of the spectroscopic measurements used to characterize their flexibility. Results obtained from the simulations are in good qualitative agreement with the experimental measurements and indicate that the spectroscopic signal is sensitive to protein dynamics distributed throughout the entire combining site. Thus, the simulations provide a molecular-level interpretation of the changes induced by affinity maturation of the Ab. The results suggest that 3PEPS spectroscopy in combination with molecular dynamics simulations can provide a detailed description of protein dynamics and, in this case, how it is evolved for biological function.

Peptide folding using multiscale coarse-grained models.

The multiscale coarse-graining (MS-CG) method has been previously used to describe the equilibrium properties of peptides. The present study reveals that MS-CG models of alpha-helical polyalanine and the beta-hairpin V 5PGV 5 possess the capacity to efficiently refold in simulations initiated from unfolded configurations. The MS-CG peptides exhibit free energy landscapes that are funneled toward folded configurations and two-state folding behavior, consistent with the known characteristics of small, rapidly folding peptides. Moreover, the models demonstrate enhanced sampling capabilities when compared to systems with full atomic detail. The significance of these observations with respect to the theoretical basis of the MS-CG approach is discussed. The MS-CG peptides were used to reconstruct atomically detailed configurations in order to evaluate the extent to which MS-CG ensembles embody all-atom peptide free energy landscapes. Ensembles obtained from these reconstructed configurations display good agreement with the all-atom simulation data used to generate the MS-CG models and also corroborate the presence of features observed in the MS-CG peptide free energy landscapes. These findings suggest that MS-CG models may be of significant utility in the study of peptide folding.

Origins of enhanced proton transport in the Y7F mutant of human carbonic anhydrase II.

Human carbonic anhydrase II (HCA II), among the fastest enzymes known, catalyzes the reversible hydration of CO 2 to HCO 3 (-). The rate-limiting step of this reaction is believed to be the formation of an intramolecular water wire and transfer of a proton across the active site cavity from a zinc-bound solvent to a proton shuttling residue (His64). X-ray crystallographic studies have shown this intramolecular water wire to be directly stabilized through hydrogen bonds via a small well-defined set of amino acids, namely, Tyr7, Asn62, Asn67, Thr199, and Thr200. Furthermore, X-ray crystallographic and kinetic studies have shown that the mutation of tyrosine 7 to phenylalanine, Y7F HCA II, has the effect of increasing the proton transfer rate by 7-fold in the dehydration direction of the enzyme reaction compared to wild-type (WT). This increase in the proton transfer rate is postulated to be linked to the formation of a more directional, less branched, water wire. To evaluate this proposal, molecular dynamics simulations have been employed to study water wire formation in both the WT and Y7F HCA II mutant. These studies reveal that the Y7F mutant enhances the probability of forming small water wires and significantly extends the water wire lifetime, which may account for the elevated proton transfer seen in the Y7F mutant. Correlation analysis of the enzyme and intramolecular water wire indicates that the Y7F mutant significantly alters the interaction of the active site waters with the enzyme while occupancy data of the water oxygens reveals that the Y7F mutant stabilizes the intramolecular water wire in a manner that maximizes smaller water wire formation. This increase in the number of smaller water wires is likely to elevate the catalytic turnover of an already very efficient enzyme.

Molecular evolution of affinity and flexibility in the immune system.

The immune system responds to the introduction of foreign antigens by rapidly evolving antibodies with increasing affinity for the antigen (i.e., maturation). To investigate the factors that control this process at the molecular level, we have assessed the changes in flexibility that accompany ligand binding at four stages of maturation in the 4-4-20 antibody. Our studies, based on molecular dynamics, indicate that increased affinity for the target ligand is associated with a decreased entropic cost to binding. The entropy of binding is unfavorable, opposing favorable enthalpic contributions that arise during complex formation. Computed binding free energies for the various antibody-ligand complexes qualitatively reproduce the trends observed in the experimentally derived values, although the absolute magnitude of free-energy differences is overestimated. Our results support the existence of a correlation between high-affinity interactions and decreased protein flexibility in this series of antibody molecules. This observation is likely to be a general feature of molecular association processes and key to the molecular evolution of antibody responses.

Coarse-grained peptide modeling using a systematic multiscale approach.

A systematic new approach to derive multiscale coarse-grained (MS-CG) models has been recently developed. The approach employs information from atomistically detailed simulations to derive CG forces and associated effective potentials. In this work, the MS-CG methodology is extended to study two peptides representing distinct structural motifs, alpha-helical polyalanine and the beta-hairpin V(5)PGV(5). These studies represent the first known application of this approach to peptide systems. Good agreement between the MS-CG and atomistic models is achieved for several structural properties including radial distribution functions, root mean-square deviation, and radius of gyration. The new MS-CG models are able to preserve the native states of these peptides within approximately 1 A backbone root mean-square deviation during CG simulations. The MS-CG approach, as with most coarse-grained models, has the potential to increase the length and timescales accessible to molecular simulations. However, it is also able to maintain a clear connection to the underlying atomistic-scale interactions.

Antibody evolution constrains conformational heterogeneity by tailoring protein dynamics.

The evolution of proteins with novel function is thought to start from precursor proteins that are conformationally heterogeneous. The corresponding genes may be duplicated and then mutated to select and optimize a specific conformation. However, testing this idea has been difficult because of the challenge of quantifying protein flexibility and conformational heterogeneity as a function of evolution. Here, we report the characterization of protein heterogeneity and dynamics as a function of evolution for the antifluorescein antibody 4-4-20. Using nonlinear laser spectroscopy, surface plasmon resonance, and molecular dynamics simulations, we demonstrate that evolution localized the Ab-combining site from a heterogeneous ensemble of conformations to a single conformation by introducing mutations that act cooperatively and over significant distances to rigidify the protein. This study demonstrates how protein dynamics may be tailored by evolution and has important implications for our understanding of how novel protein functions are evolved.

Evaluating the conformational entropy of macromolecules using an energy decomposition approach.

We have developed a novel method to compute the conformational entropy of any molecular system via conventional simulation techniques. This method only requires that the total energy of the system is available and that the Hamiltonian is separable, with individual energy terms for the various degrees of freedom. Consequently the method, which we call the energy decomposition (Edcp) approach, is general and applicable to any large polymer in implicit solvent. Edcp is applied to estimate the entropy differences due to the peptide and ester groups in polyalanine and polyalanil ester. Ensembles over a wide range of temperatures were generated by replica exchange molecular dynamics, and densities of states were estimated using the weighted histogram analysis method. The results are compared with those obtained via evaluating the P ln P integral or employing the quasiharmonic approximation, other approaches widely employed to evaluate the entropy of molecular systems. Unlike the former method, Edcp can accommodate the correlations present between separate degrees of freedom. In addition, the Edcp model assumes no specific form for the underlying fluctuations present in the system, in contrast to the quasiharmonic approximation. For the molecules studied, the quasiharmonic approximation is observed to produce a good estimate of the vibrational entropy, but not of the conformational entropy. In contrast, our energy decomposition approach generates reasonable estimates for both of these entropy terms. We suggest that this approach embodies a simple yet effective solution to the problem of evaluating the conformational entropy of large macromolecules in implicit solvent.