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

Motif-VI loop acts as a nucleotide valve in the West Nile Virus NS3 Helicase

The Orthoflavivirus NS3 helicase (NS3h) is crucial in virus replication, representing a potential drug target for pathogenesis. NS3h utilizes nucleotide triphosphate (ATP) for hydrolysis energy to translocate on single-stranded nucleic acids, which is an important step in the unwinding of double-stranded nucleic acids. Intermediate states along the ATP hydrolysis cycle and conformational changes between these states, represent important yet difficult-to-identify targets for potential inhibitors. Extensive molecular dynamics simulations of West Nile virus NS3h+ssRNA in the apo, ATP, ADP+Pi and ADP bound states were used to model the conformational ensembles along this cycle. Energetic and structural clustering analyses depict a clear trend of differential enthalpic affinity of NS3h with ADP, demonstrating a probable mechanism of hydrolysis turnover regulated by the motif-VI loop (MVIL). Based on these results, MVIL mutants (D471L, D471N and D471E) were found to have a substantial reduction in ATPase activity and RNA replication compared to the wild-type. Simulations of the mutants in the apo state indicate a shift in MVIL populations favoring either a closed or open 'valve' conformation, affecting ATP entry or stabilization, respectively. Combining our molecular modeling with experimental evidence highlights a conformation-dependent role for MVIL as a 'valve' for the ATP-pocket, presenting a promising target for antiviral development.

Motif-VI Loop Acts as a Nucleotide Valve in the West Nile Virus NS3 Helicase

The flavivirus NS3 helicase (NS3h), a highly conserved protein, plays a pivotal role in virus replication and thus represents a potential drug target for flavivirus pathogenesis. NS3h utilizes nucleotide triphosphate, such as ATP, for hydrolysis energy (ATPase) to translocate on single-stranded nucleic acids, which is an important step in the unwinding of double-stranded nucleic acids. The intermediate states along the ATP binding and hydrolysis cycle, as well as the conformational changes between these states, represent important yet difficult-to-identify targets for potential inhibitors. We use extensive molecular dynamics simulations of apo, ATP, ADP+Pi, and ADP bound to WNV NS3h+ssRNA to model the conformational ensembles along this cycle. Energetic and structural clustering analyses on these trajectories depict a clear trend of differential enthalpic affinity of NS3h with ADP, demonstrating a probable mechanism of hydrolysis turnover regulated by the motif-VI loop (MVIL). These findings were experimentally corroborated using viral replicons encoding three mutations at the D471 position. Replication assays using these mutants demonstrated a substantial reduction in viral replication compared to the wild-type. Molecular simulations of the D471 mutants in the apo state indicate a shift in MVIL populations favoring either a closed or open 'valve' conformation, affecting ATP entry or stabilization, respectively. Combining our molecular modeling with experimental evidence highlights a conformation-dependent role for MVIL as a 'valve' for the ATP-pocket, presenting a promising target for antiviral development.

Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics

The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.

Dengue Virus NS4b N-Terminus Disordered Region Interacts with NS3 Helicase C-Terminal Subdomain to Enhance Helicase Activity

Dengue virus replicates its single-stranded RNA genome in membrane-bound complexes formed on the endoplasmic reticulum, where viral non-structural proteins (NS) and RNA co-localize. The NS proteins interact with one another and with the host proteins. The interaction of the viral helicase and protease, NS3, with the RNA-dependent RNA polymerase, NS5, and NS4b proteins is critical for replication. In vitro, NS3 helicase activity is enhanced by interaction with NS4b. We characterized the interaction between NS3 and NS4b and explained a possible mechanism for helicase activity modulation by NS4b. Our bacterial two-hybrid assay results showed that the N-terminal 57 residues region of NS4b is enough to interact with NS3. The molecular docking of the predicted NS4b structure onto the NS3 structure revealed that the N-terminal disordered region of NS4b wraps around the C-terminal subdomain (CTD) of the helicase. Further, NS3 helicase activity is enhanced upon interaction with NS4b. Molecular dynamics simulations on the NS4b-docked NS3 crystal structure and intrinsic tryptophan fluorescence studies suggest that the interaction results in NS3 CTD domain motions. Based on the interpretation of our results in light of the mechanism explained for NS3 helicase, NS4b–NS3 interaction modulating CTD dynamics is a plausible explanation for the helicase activity enhancement.

Identification of key sites controlling protein functional motions by using elastic network model combined with internal coordinates

The elastic network model (ENM) is an effective method to extract the intrinsic dynamical properties encoded in protein tertiary structures. We have proposed a new ENM-based analysis method to reveal the motion modes directly responsible for a specific protein function, in which an internal coordinate related to the specific function was introduced to construct the internal/Cartesian hybrid coordinate space. In the present work, the function-related internal coordinates combined with a linear perturbation method were applied to identify the key sites controlling specific protein functional motions. The change in the fluctuations of the internal coordinate in response to residue perturbation was calculated in the hybrid coordinate space by using the linear response theory. The residues with the large fluctuation changes were identified to be the key sites that allosterically control the specific protein function. Two proteins, i.e., human DNA polymerase β and the chaperonin from Methanococcus maripaludis, were investigated as case studies, in which several collective and local internal coordinates were applied to identify the functionally key residues of these two studied proteins. The calculation results are consistent with the experimental observations. It is found that different collective internal coordinates lead to similar results, where the predicted functionally key sites are located at similar positions in the protein structure. While for the local internal coordinates, the predicted key sites tend to be situated at the region near to the coordinate-involving residues. Our studies provide a starting point for further exploring other function-related internal coordinates for other interesting proteins.

Dissecting conformational changes in APP's transmembrane domain linked to ε-efficiency in familial Alzheimer's disease

The mechanism by which familial Alzheimer's disease (FAD) mutations within the transmembrane domain (TMD) of the Amyloid Precursor Protein (APP) affect ε-endoproteolysis is only poorly understood. Thereby, mutations in the cleavage domain reduce ε-efficiency of γ-secretase cleavage and some even shift entry into production lines. Since cleavage occurs within the TMD, a relationship between processing and TMD structure and dynamics seems obvious. Using molecular dynamic simulations, we dissect the dynamic features of wild-type and seven FAD-mutants into local and global components. Mutations consistently enhance hydrogen-bond fluctuations upstream of the ε-cleavage sites but maintain strong helicity there. Dynamic perturbation-response scanning reveals that FAD-mutants target backbone motions utilized in the bound state. Those motions, obscured by large-scale motions in the pre-bound state, provide (i) a dynamic mechanism underlying the proposed coupling between binding and ε-cleavage, (ii) key sites consistent with experimentally determined docking sites, and (iii) the distinction between mutants and wild-type.

Allostery in the dengue virus NS3 helicase: Insights into the NTPase cycle from molecular simulations

The C-terminus domain of non-structural 3 (NS3) protein of the Flaviviridae viruses (e.g. HCV, dengue, West Nile, Zika) is a nucleotide triphosphatase (NTPase) -dependent superfamily 2 (SF2) helicase that unwinds double-stranded RNA while translocating along the nucleic polymer. Due to these functions, NS3 is an important target for antiviral development yet the biophysics of this enzyme are poorly understood. Microsecond-long molecular dynamic simulations of the dengue NS3 helicase domain are reported from which allosteric effects of RNA and NTPase substrates are observed. The presence of a bound single-stranded RNA catalytically enhances the phosphate hydrolysis reaction by affecting the dynamics and positioning of waters within the hydrolysis active site. Coupled with results from the simulations, electronic structure calculations of the reaction are used to quantify this enhancement to be a 150-fold increase, in qualitative agreement with the experimental enhancement factor of 10–100. Additionally, protein-RNA interactions exhibit NTPase substrate-induced allostery, where the presence of a nucleotide (e.g. ATP or ADP) structurally perturbs residues in direct contact with the phosphodiester backbone of the RNA. Residue-residue network analyses highlight pathways of short ranged interactions that connect the two active sites. These analyses identify motif V as a highly connected region of protein structure through which energy released from either active site is hypothesized to move, thereby inducing the observed allosteric effects. These results lay the foundation for the design of novel allosteric inhibitors of NS3.

Non-structural protein 3 (NS3) is a Flaviviridae (e.g. Hepatitis C, dengue, and Zika viruses) helicase that unwinds double stranded RNA while translocating along the nucleic polymer during viral genome replication. As a member of superfamily 2 (SF2) helicases, NS3 utilizes the free energy of nucleotide triphosphate (NTP) binding, hydrolysis, and product unbinding to perform its functions. While much is known about SF2 helicases, the pathways and mechanisms through which free energy is transduced between the NTP hydrolysis active site and RNA binding cleft remains elusive. Here we present a multiscale computational study to characterize the allosteric effects induced by the RNA and NTPase substrates (ATP, ADP, and P_i) as well as the pathways of short-range, residue-residue interactions that connect the two active sites. Results from this body of molecular dynamics simulations and electronic structure calculations are highlighted in context to the NTPase enzymatic cycle, allowing for development of testable hypotheses for validation of these simulations. Our insights, therefore, provide novel details about the biophysics of NS3 and guide the next generation of experimental studies.

How Computational Models Enable Mechanistic Insights into Virus Infection

An implicit aim in cellular infection biology is to understand the mechanisms how viruses, microbes, eukaryotic parasites, and fungi usurp the functions of host cells and cause disease. Mechanistic insight is a deep understanding of the biophysical and biochemical processes that give rise to an observable phenomenon. It is typically subject to falsification, that is, it is accessible to experimentation and empirical data acquisition. This is different from logic and mathematics, which are not empirical, but built on systems of inherently consistent axioms. Here, we argue that modeling and computer simulation, combined with mechanistic insights, yields unprecedented deep understanding of phenomena in biology and especially in virus infections by providing a way of showing sufficiency of a hypothetical mechanism. This ideally complements the necessity statements accessible to empirical falsification by additional positive evidence. We discuss how computational implementations of mathematical models can assist and enhance the quantitative measurements of infection dynamics of enveloped and non-enveloped viruses and thereby help generating causal insights into virus infection biology.

Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc.

Molecular mechanism of divalent-metal-induced activation of NS3 helicase and insights into Zika virus inhibitor design

Zika virus has attracted increasing attention because of its potential for causing human neural disorders, including microcephaly in infants and Guillain–Barré syndrome. Its NS3 helicase domain plays critical roles in NTP-dependent RNA unwinding and translocation during viral replication. Our structural analysis revealed a pre-activation state of NS3 helicase in complex with GTPγS, in which the triphosphate adopts a compact conformation in the absence of any divalent metal ions. In contrast, in the presence of a divalent cation, GTPγS adopts an extended conformation, and the Walker A motif undergoes substantial conformational changes. Both features contribute to more extensive interactions between the GTPγS and the enzyme. Thus, this study provides structural evidence on the allosteric modulation of MgNTP²⁻ on the NS3 helicase activity. Furthermore, the compact conformation of inhibitory NTP identified in this study provides precise information for the rational drug design of small molecule inhibitors for the treatment of ZIKV infection.

A combined coarse-grained and all-atom simulation of TRPV1 channel gating and heat activation

Coarse-grained modeling and all-atom molecular dynamics simulation provide insight into the mechanism for heat activation of TRPV1 gating.

The transient receptor potential (TRP) channels act as key sensors of various chemical and physical stimuli in eukaryotic cells. Despite years of study, the molecular mechanisms of TRP channel activation remain unclear. To elucidate the structural, dynamic, and energetic basis of gating in TRPV1 (a founding member of the TRPV subfamily), we performed coarse-grained modeling and all-atom molecular dynamics (MD) simulation based on the recently solved high resolution structures of the open and closed form of TRPV1. Our coarse-grained normal mode analysis captures two key modes of collective motions involved in the TRPV1 gating transition, featuring a quaternary twist motion of the transmembrane domains (TMDs) relative to the intracellular domains (ICDs). Our transition pathway modeling predicts a sequence of structural movements that propagate from the ICDs to the TMDs via key interface domains (including the membrane proximal domain and the C-terminal domain), leading to sequential opening of the selectivity filter followed by the lower gate in the channel pore (confirmed by modeling conformational changes induced by the activation of ICDs). The above findings of coarse-grained modeling are robust to perturbation by lipids. Finally, our MD simulation of the ICD identifies key residues that contribute differently to the nonpolar energy of the open and closed state, and these residues are predicted to control the temperature sensitivity of TRPV1 gating. These computational predictions offer new insights to the mechanism for heat activation of TRPV1 gating, and will guide our future electrophysiology and mutagenesis studies.

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Towards structural systems pharmacology to study complex diseases and personalized medicine

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

Analysis of protein conformational transitions using elastic network model

In this chapter, we demonstrate the usage of a coarse-grained elastic network model to analyze protein conformational transitions in the NS3 helicase (NS3hel) of Hepatitis C virus (HCV). This analysis allows us to identify and visualize collective domain motions involved in the conformational transitions and predict the order of structural events during the transitions. It is highly efficient and applicable to many multi-domain protein structures which undergo large conformational changes to fulfill their functions. This method is made available through a Web server ( http://enm.lobos.nih.gov ).

Computational biology approach to uncover hepatitis C virus helicase operation

Hepatitis C virus (HCV) helicase is a molecular motor that splits nucleic acid duplex structures during viral replication, therefore representing a promising target for antiviral treatment. Hence, a detailed understanding of the mechanism by which it operates would facilitate the development of efficient drug-assisted therapies aiming to inhibit helicase activity. Despite extensive investigations performed in the past, a thorough understanding of the activity of this important protein was lacking since the underlying internal conformational motions could not be resolved. Here we review investigations that have been previously performed by us for HCV helicase. Using methods of structure-based computational modelling it became possible to follow entire operation cycles of this motor protein in structurally resolved simulations and uncover the mechanism by which it moves along the nucleic acid and accomplishes strand separation. We also discuss observations from that study in the light of recent experimental studies that confirm our findings.

Multiple pathways promote dynamical coupling between catalytic domains in Escherichia coli prolyl-tRNA synthetase

Aminoacyl-tRNA synthetases are multidomain enzymes that catalyze covalent attachment of amino acids to their cognate tRNA. Cross-talk between functional domains is a prerequisite for this process. In this study, we investigate the molecular mechanism of site-to-site communication in Escherichia coli prolyl-tRNA synthetase (Ec ProRS). Earlier studies have demonstrated that evolutionarily conserved and/or co-evolved residues that are engaged in correlated motion are critical for the propagation of functional conformational changes from one site to another in modular proteins. Here, molecular simulation and bioinformatics-based analysis were performed to identify dynamically coupled and evolutionarily constrained residues that form contiguous pathways of residue-residue interactions between the aminoacylation and editing domains of Ec ProRS. The results of this study suggest that multiple pathways exist between these two domains to maintain the dynamic coupling essential for enzyme function. Moreover, residues in these interaction networks are generally highly conserved. Site-directed changes of on-pathway residues have a significant impact on enzyme function and dynamics, suggesting that any perturbation along these pathways disrupts the native residue-residue interactions that are required for effective communication between the two functional domains. Free energy analysis revealed that communication between residues within a pathway and cross-talk between pathways are important for coordinating functions of different domains of Ec ProRS for efficient catalysis.

Structure-based simulations of the translocation mechanism of the hepatitis C virus NS3 helicase along single-stranded nucleic acid

The NS3 helicase of Hepatitis C virus is an ATP-fueled molecular motor that can translocate along single-stranded (ss) nucleic acid, and unwind double-stranded nucleic acids. It makes a promising antiviral target and an important prototype system for helicase research. Despite recent progress, the detailed mechanism of NS3 helicase remains unknown. In this study, we have combined coarse-grained (CG) and atomistic simulations to probe the translocation mechanism of NS3 helicase along ssDNA. At the residue level of detail, our CG simulations have captured functionally important interdomain motions of NS3 helicase and reproduced single-base translocation of NS3 helicase along ssDNA in the 3'-5' direction, which is in good agreement with experimental data and the inchworm model. By combining the CG simulations with residue-specific perturbations to protein-DNA interactions, we have identified a number of key residues important to the translocation machinery that agree with previous structural and mutational studies. Additionally, our atomistic simulations with targeted molecular dynamics have corroborated the findings of CG simulations and further revealed key protein-DNA hydrogen bonds that break/form during the transitions. This study offers, to our knowledge, the most detailed and realistic simulations of translocation mechanism of NS3 helicase. The simulation protocol established in this study will be useful for designing inhibitors that target the translocation machinery of NS3 helicase, and for simulations of a variety of nucleic-acid-based molecular motors.

Coarse-grained modeling of the structural states and transition underlying the powerstroke of dynein motor domain

This study aims to model a minimal dynein motor domain capable of motor function, which consists of the linker domain, six AAA+ modules (AAA1-AAA6), coiled coil stalk, and C-terminus domain. To this end, we have used the newly solved X-ray structures of dynein motor domain to perform a coarse-grained modeling of dynein's post- and pre-powerstroke conformation and the conformational transition between them. First, we have used normal mode analysis to identify a single normal mode that captures the coupled motions of AAA1-AAA2 closing and linker domain rotation, which enables the ATP-driven recovery stroke of dynein. Second, based on the post-powerstroke conformation solved crystallographically, we have modeled dynein's pre-powerstroke conformation by computationally inducing AAA1-AAA2 closing and sliding of coiled coil stalk, and the resulting model features a linker domain near the pre-powerstroke position and a slightly tilted stalk. Third, we have modeled the conformational transition from pre- to post-powerstroke conformation, which predicts a clear sequence of structural events that couple microtubule binding, powerstroke and product release, and supports a signaling path from stalk to AAA1 via AAA3 and AAA4. Finally, we have found that a closed AAA3-AAA4 interface (compatible with nucleotide binding) is essential to the mechano-chemical coupling in dynein. Our modeling not only offers unprecedented structural insights to the motor function of dynein as described by past single-molecule, fluorescence resonance energy transfer, and electron microscopy studies, but also provides new predictions for future experiments to test.

Mechanism of flexibility control for ATP access of hepatitis C virus NS3 helicase

Hepatitis C virus (HCV) NS3 helicase couples adenosine triphosphate (ATP) binding and hydrolysis to polynucleotide unwinding. Understanding the regulation mechanism of ATP binding will facilitate targeting of the ATP-binding site for potential therapeutic development for hepatitis C. T324, an amino acid residue connecting domains 1 and 2 of NS3 helicase, has been suggested as part of a flexible hinge for opening of the ATP-binding cleft, although the detailed mechanism remains largely unclear. We used computational simulation to examine the mutational effect of T324 on the dynamics of the ATP-binding site. A mutant model, T324A, of the NS3 helicase apo structure was created and energy was minimized. Molecular dynamics simulation was conducted for both wild type and the T324A mutant apo structures to compare their differences. For the mutant structure, histogram analysis of pairwise distances between residues in domains 1 and 2 (E291-Q460, K210-R464 and R467-T212) showed that separation between the two domains was reduced by ~10% and the standard deviation by ~33%. Root mean square fluctuation (RMSF) analysis demonstrated that residues in close proximity to residue 324 have at least 30% RMSF value reductions in the mutant structure. Solvent RMSF analysis showed that more water molecules were trapped near D290 and H293 in domain 1 to form an extensive interaction network constraining cleft opening. We also demonstrated that the T324A mutation established a new atomic interaction with V331, revealing that an atomic interaction cascade from T324 to residues in domains 1 and 2 controls the flexibility of the ATP-binding cleft.

Looking for a sequence based allostery definition: a statistical journey at different resolution scales

The aim of this work was to detect allosteric hotspots signatures characterizing protein regions acting as the 'key drivers' of global allosteric conformational change. We computationally estimated the relative strength of intra-molecular interaction in allosteric proteins between two putative allostery-susceptible sites using a co-evolution model based upon the optimization of the cross-correlation in terms of free-energy-transfer hydrophobicity scale (Tanford scale) distribution along the chain. Cross-Recurrence Quantification Analysis (Cross-RQA) applied on the sequences of allostery susceptible sites showed evidence of strong interaction amongst allosteric susceptible sites. This could be due to transient weak molecular bonds between allostery susceptible patches enabling regions far-apart to come together. Further, using a large protein dataset, by comparing allosteric protein set with a randomly generated sequence population as well as a generic protein set, we reconfirmed our earlier findings that hydrophobicity patterning (as formalized by Recurrence Quantification Analysis (RQA) descriptors) may serve as determinant of allostery and its relevance in the transmission of allosteric conformational change. We applied RQA to free-energy-transfer hydrophobicity-transformed amino acid sequences of the allostery dataset to extract allostery specific global sequence features. These free-energy-transfer hydrophobicity-based RQA markers proved to be representative of allosteric signatures and not related to the differences between randomly generated and real proteins. These free-energy-transfer hydrophobicity-based RQA markers when evaluated by pattern recognition tools could distinguish allosteric proteins with 92% accuracy.

Separating the role of protein restraints and local metal-site interaction chemistry in the thermodynamics of a zinc finger protein

We express the effective Hamiltonian of an ion-binding site in a protein as a combination of the Hamiltonian of the ion-bound site in vacuum and the restraints of the protein on the site. The protein restraints are described by the quadratic elastic network model. The Hamiltonian of the ion-bound site in vacuum is approximated as a generalized Hessian around the minimum energy configuration. The resultant of the two quadratic Hamiltonians is cast into a pure quadratic form. In the canonical ensemble, the quadratic nature of the resultant Hamiltonian allows us to express analytically the excess free energy, enthalpy, and entropy of ion binding to the protein. The analytical expressions allow us to separate the roles of the dynamic restraints imposed by the protein on the binding site and the temperature-independent chemical effects in metal-ligand coordination. For the consensus zinc-finger peptide, relative to the aqueous phase, the calculated free energy of exchanging Zn(2+) with Fe(2+), Co(2+), Ni(2+), and Cd(2+) are in agreement with experiments. The predicted excess enthalpy of ion exchange between Zn(2+) and Co(2+) also agrees with the available experimental estimate. The free energy of applying the protein restraints reveals that relative to Zn(2+), the Co(2+), and Cd(2+)-site clusters are more destabilized by the protein restraints. This leads to an experimentally testable hypothesis that a tetrahedral metal binding site with minimal protein restraints will be less selective for Zn(2+) over Co(2+) and Cd(2+) compared to a zinc finger peptide. No appreciable change is expected for Fe(2+) and Ni(2+). The framework presented here may prove useful in protein engineering to tune metal selectivity.

In silico investigation of conformational motions in superfamily 2 helicase proteins

Helicases are motor proteins that play a central role in the metabolism of DNA and RNA in biological cells. Using the energy of ATP molecules, they are able to translocate along the nucleic acids and unwind their duplex structure. They have been extensively characterized in the past and grouped into superfamilies based on structural similarities and sequential motifs. However, their functional aspects and the mechanism of their operation are not yet well understood. Here, we consider three helicases from the major superfamily 2 - Hef, Hel308 and XPD - and study their conformational dynamics by using coarse-grained relaxational elastic network models. Specifically, their responses to mechanical perturbations are analyzed. This enables us to identify robust and ordered conformational motions which may underlie the functional activity of these proteins. As we show, such motions are well-organized and have large amplitudes. Their possible roles in the processing of nucleic substrate are discussed.

Dynamics studies of luciferase using elastic network model: how the sequence distribution of luciferase determines its color

Luciferase exhibits a broad range of emitting frequencies. Light emission from the bioluminescence of luciferase makes it an excellent tool for monitoring gene expression, thus the control of its bioluminescence color has great bio-analytical applications. Here I use an elastic network model to examine how the sequence distribution of luciferase is related to bioluminescence multicolor emission. Based on the open and closed forms of crystal structures for luciferase, several computational analysis tools are applied to characterize the functionally relevant dynamical features within luciferase, and probe the dynamical mechanisms underlying the interactions between luciferin (a light-emitting substrate) and luciferase. Perturbation-based correlation analysis is used to identify hot-spot residues that are dynamically coupled to the active site of luciferase, and the results show that the sequence region of subdomain B of luciferase is largely responsible for determining the emitting color of bioluminescence. Moreover, the mode decomposition analysis reveals that the lowest frequency mode is the major contributor to the dynamical couplings between the hot-spot residues and the binding site in luciferase.

Tracing entire operation cycles of molecular motor hepatitis C virus helicase in structurally resolved dynamical simulations

Hepatitis C virus helicase is a molecular motor that splits duplex DNA while actively moving over it. An approximate coarse-grained dynamical description of this protein, including its interactions with DNA and ATP, is constructed. Using such a mechanical model, entire operation cycles of an important protein machine could be followed in structurally resolved dynamical simulations. Ratcheting inchworm translocation and spring-loaded DNA unwinding, suggested by experimental data, were reproduced. Thus, feasibility of coarse-grained simulations, bridging a gap between full molecular dynamics and reduced phenomenological theories of molecular motors, has been demonstrated.

Predicting order of conformational changes during protein conformational transitions using an interpolated elastic network model

The decryption of sequence of structural events during protein conformational transitions is essential to a detailed understanding of molecular functions of various biological nanomachines. Coarse-grained models have proven useful by allowing highly efficient simulations of protein conformational dynamics. By combining two coarse-grained elastic network models constructed based on the beginning and end conformations of a transition, we have developed an interpolated elastic network model to generate a transition pathway between the two protein conformations. For validation, we have predicted the order of local and global conformational changes during key ATP-driven transitions in three important biological nanomachines (myosin, F(1) ATPase and chaperonin GroEL). We have found that the local conformational change associated with the closing of active site precedes the global conformational change leading to mechanical motions. Our finding is in good agreement with the distribution of intermediate experimental structures, and it supports the importance of local motions at active site to drive or gate various conformational transitions underlying the workings of a diverse range of biological nanomachines.

Deciphering the deformation modes associated with function retention and specialization in members of the Ras superfamily

The evolutionary and physical deformability patterns of members of the Ras GTPase superfamily were investigated by Principal Component and Elastic Network-Normal Mode analyses. The study helped to decipher the dynamics information encrypted into the conserved core and to separate the trans-family intrinsic flexibility associated with a common function from the protein motions related to functional specialization of selected families or family members. The conserved core is dynamically divided into two lobes. The deformation modes, which allow the Ras GTPases to accomplish their switching function, are conserved along evolution and are localized in lobe 1 portions close to the nucleotide. These modes lead to functional specialization when associated with evolution-driven deformations of protein portions essentially located in lobe 2, distal from the nucleotide, and involved in peculiar interactions with membrane, guanine nucleotide exchange factors, or effectors. Overall, a complete picture of the functional and evolutionary dynamics of the Ras superfamily emerges.

Computer modeling of helicases using elastic network model

In this chapter, we will demonstrate the usage of a suite of computational techniques based on a coarse-grained elastic network model by applying them to a monomeric helicase-the NS3 helicase of hepatitis C virus. These techniques allow us to predict and visualize collective domain motions encoded in the protein structures, probe allosteric couplings between key functional sites (such as ATP-binding site and DNA/RNA-binding site of a helicase), and simulate ATP-binding-induced global conformational changes. These general techniques are not only applicable to NS3 but also to other multi-domain protein structures.

Structure-based predictive models for allosteric hot spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues.

Allostery is the process whereby a molecule binds to one site in a protein and alters the function of a distant site. This phenomenon is ubiquitous, as proteins frequently must adapt their behavior to changes in the cellular milieu. The mechanism(s) underlying allostery remains incompletely understood. In particular, predictive models are needed that distinguish amino-acid residues that are critical to allostery, or “hotspots”, from non-hotspots. Here we have used data-mining approaches to infer rules that distinguish hotspots from non-hotspots. Starting with a data set of known hotspot and non-hotspot residues from a diverse set of allosteric proteins, the training data set, we applied machine learning to this data to “learn” models, or sets of rules, for distinguishing hotspots and non-hotspots by inferring associations between the classification (hotspot or non-hotspot) and an associated set of calculated attributes. Many models that showed the highest predictive power on the training data also exhibited high accuracy and sensitivity when applied to an independent data set. Moreover, the pattern of predicted hotspots in the proteins we studied was consistent with known structure/function relationships and previous work suggesting that a network of essential residues mediates the allosteric transition.

Coarse-grained modeling of allosteric regulation in protein receptors

Allosteric regulation provides highly specific ligand recognition and signaling by transmembrane protein receptors. Unlike functions of protein molecular machines that rely on large-scale conformational transitions, signal transduction in receptors appears to be mediated by more subtle structural motions that are difficult to identify. We describe a theoretical model for allosteric regulation in receptors that addresses a fundamental riddle of signaling: What are the structural origins of the receptor agonism (specific signaling response to ligand binding)? The model suggests that different signaling pathways in bovine rhodopsin or human beta(2)-adrenergic receptor can be mediated by specific structural motions in the receptors. We discuss implications for understanding the receptor agonism, particularly the recently observed "biased agonism" (selected activation of specific signaling pathways), and for developing rational structure-based drug-design strategies.

Approximate normal mode analysis based on vibrational subsystem analysis with high accuracy and efficiency

Normal mode analysis (NMA) has been proven valuable in modeling slow conformational dynamics of biomolecular structures beyond the reach of direct molecular simulations. However, it remains computationally expensive to directly solve normal modes for large biomolecular systems. In this study, we have evaluated the accuracy and efficiency of two approximate NMA protocols-one based on our recently proposed vibrational subsystem analysis (VSA), the other based on the rotation translation block (RTB), in comparison with standard NMA that directly solves a full Hessian matrix. By properly accounting for flexibility within blocks of residues or atoms based on a subsystem-environment partition, VSA-based NMA has attained a much higher accuracy than RTB and much lower computing cost than standard NMA. Therefore, VSA enables accurate and efficient calculations of normal modes from all-atom or coarse-grained potential functions, which promise to improve conformational sampling driven by low-frequency normal modes.

Large-scale evaluation of dynamically important residues in proteins predicted by the perturbation analysis of a coarse-grained elastic model

Backgrounds

It is increasingly recognized that protein functions often require intricate conformational dynamics, which involves a network of key amino acid residues that couple spatially separated functional sites. Tremendous efforts have been made to identify these key residues by experimental and computational means.

Results

We have performed a large-scale evaluation of the predictions of dynamically important residues by a variety of computational protocols including three based on the perturbation and correlation analysis of a coarse-grained elastic model. This study is performed for two lists of test cases with >500 pairs of protein structures. The dynamically important residues predicted by the perturbation and correlation analysis are found to be strongly or moderately conserved in >67% of test cases. They form a sparse network of residues which are clustered both in 3D space and along protein sequence. Their overall conservation is attributed to their dynamic role rather than ligand binding or high network connectivity.

Conclusion

By modeling how the protein structural fluctuations respond to residue-position-specific perturbations, our highly efficient perturbation and correlation analysis can be used to dissect the functional conformational changes in various proteins with a residue level of detail. The predictions of dynamically important residues serve as promising targets for mutational and functional studies.

Coupling between normal modes drives protein conformational dynamics: illustrations using allosteric transitions in myosin II

Structure-based elastic network models (ENMs) have been remarkably successful in describing conformational transitions in a variety of biological systems. Low-frequency normal modes are usually calculated from the ENM that characterizes elastic interactions between residues in contact in a given protein structure with a uniform force constant. To explore the dynamical effects of nonuniform elastic interactions, we calculate the robustness and coupling of the low-frequency modes in the presence of nonuniform variations in the ENM force constant. The variations in the elastic interactions, approximated here by Gaussian noise, approximately account for perturbation effects of heterogeneous residue-residue interactions or evolutionary sequence changes within a protein family. First-order perturbation theory provides an efficient and qualitatively correct estimate of the mode robustness and mode coupling for finite perturbations to the ENM force constant. The mode coupling analysis and the mode robustness analysis identify groups of strongly coupled modes that encode for protein functional motions. We illustrate the new concepts using myosin II motor protein as an example. The biological implications of mode coupling in tuning the allosteric couplings among the actin-binding site, the nucleotide-binding site, and the force-generating converter and lever arm in myosin isoforms are discussed. We evaluate the robustness of the correlation functions that quantify the allosteric couplings among these three key structural motifs.

Insights into RNA unwinding and ATP hydrolysis by the flavivirus NS3 protein

Together with the NS5 polymerase, the NS3 helicase has a pivotal function in flavivirus RNA replication and constitutes an important drug target. We captured the dengue virus NS3 helicase at several stages along the catalytic pathway including bound to single-stranded (ss) RNA, to an ATP analogue, to a transition-state analogue and to ATP hydrolysis products. RNA recognition appears largely sequence independent in a way remarkably similar to eukaryotic DEAD box proteins Vasa and eIF4AIII. On ssRNA binding, the NS3 enzyme switches to a catalytic-competent state imparted by an inward movement of the P-loop, interdomain closure and a change in the divalent metal coordination shell, providing a structural basis for RNA-stimulated ATP hydrolysis. These structures demonstrate for the first time large quaternary changes in the flaviviridae helicase, identify the catalytic water molecule and point to a beta-hairpin that protrudes from subdomain 2, as a critical element for dsRNA unwinding. They also suggest how NS3 could exert an effect as an RNA-anchoring device and thus participate both in flavivirus RNA replication and assembly.

Multiscale methods for macromolecular simulations

In this article we review the key modeling tools available for simulating biomolecular systems. We consider recent developments and representative applications of mixed quantum mechanics/molecular mechanics (QM/MM), elastic network models (ENMs), coarse-grained molecular dynamics, and grid-based tools for calculating interactions between essentially rigid protein assemblies. We consider how the different length scales can be coupled, both in a sequential fashion (e.g. a coarse-grained or grid model using parameterization from MD simulations), and via concurrent approaches, where the calculations are performed together and together control the progression of the simulation. We suggest how the concurrent coupling approach familiar in the context of QM/MM calculations can be generalized, and describe how this has been done in the CHARMM macromolecular simulation package.

Two-state model for helicase translocation and unwinding of nucleic acids

Helicases are molecular motors that unwind double-stranded nucleic acids (dsNA), such as DNA and RNA. Typically a helicase translocates along one of the NA single strands while unwinding and uses adenosine triphosphate (ATP) hydrolysis as an energy source. Here we model a helicase motor that can switch between two states, which could represent two different points in the ATP hydrolysis cycle. Our model is an extension of the earlier Betterton-Jülicher model of helicases to incorporate switching between two states. The main predictions of the model are the speed of unwinding of the dsNA and fluctuations around the average unwinding velocity. Motivated by a recent claim that the NS3 helicase of Hepatitis C virus follows a flashing-ratchet mechanism, we have compared the experimental results for the NS3 helicase with a special limit of our model which corresponds to the flashing-ratchet scenario. Our model accounts for one key feature of the experimental data on NS3 helicase. However, contradictory observations in experiments carried out under different conditions limit the ability to compare the model to experiments.

Dealing with structural variability in molecular replacement and crystallographic refinement through normal-mode analysis

Normal-mode analysis (NMA) can be used to generate multiple structural variants of a given template model, thereby increasing the chance of finding the molecular-replacement solution. Here, it is shown that it is also possible to directly refine the amplitudes of the normal modes against experimental data (X-ray or cryo-EM), generalizing rigid-body refinement methods by adding just a few additional degrees of freedom that sample collective and large-amplitude movements. It is also argued that the situation where several (conformations of) models are present simultaneously in the crystal can be studied with adjustable occupancies using techniques derived from statistical thermodynamics and already used in molecular modelling.