The interplay of structure and dynamics: insights from a survey of HIV-1 reverse transcriptase crystal structures

Surveying nonvisual arrestins reveals allosteric interactions between functional sites

Arrestins are important scaffolding proteins that are expressed in all vertebrate animals. They regulate cell-signaling events upon binding to active G-protein coupled receptors (GPCR) and trigger endocytosis of active GPCRs. While many of the functional sites on arrestins have been characterized, the question of how these sites interact is unanswered. We used anisotropic network modeling (ANM) together with our covariance compliment techniques to survey all the available structures of the nonvisual arrestins to map how structural changes and protein-binding affect their structural dynamics. We found that activation and clathrin binding have a marked effect on arrestin dynamics, and that these dynamics changes are localized to a small number of distant functional sites. These sites include α-helix 1, the lariat loop, nuclear localization domain, and the C-domain β-sheets on the C-loop side. Our techniques suggest that clathrin binding and/or GPCR activation of arrestin perturb the dynamics of these sites independent of structural changes.

Coarse grained modelling highlights the binding differences in the two different allosteric sites of the Human Kinesin EG5 and its implications in inhibitor design

Kinesins involved in mitotic cell division have gained prominence as promising chemotherapy targets. One such kinesin, EG5, a motor protein responsible for cell division, is a validated chemotherapy target with several compounds at various stages of clinical trials. EG5 has an active site and two different allosteric sites that are known to have ligand specificity. Upon ligand binding, EG5's motor domain will no longer undergo nucleotide-dependent conformational changes required to complete the catalytic cycle. However, there is a lack of in-depth knowledge on the mechanism of inhibitor binding to the two different allosteric sites. To understand the EG5's inhibition mechanism and interactions at allosteric sites and other functionally important regions, we generated two coarse-grained models, Gaussian Network Model (GNM) and Anisotropic Network Model (ANM), to identify the dynamics and its correlation to EG5's function. The first three slowest modes of GNM showed marked differences between the various models of EG5. In the first mode, when the inhibitor is bound at allosteric site 1, there is a presence of a hinge region around residue 166, which is not found when the inhibitor is bound at allosteric site 2 or allosteric sites 1 and 2. The third slowest mode showed a distinctive positively correlated region when the inhibitor is bound at allosteric site 2. These differences indicated that the mechanism of binding at allosteric site 1 and allosteric site 2 are unique. Further, it was observed that the simultaneous ligand binding at allosteric sites 1 and 2 shares structural dynamics and interactions that were found while ligand binds at allosteric sites 1 and 2 independently, leading to a new mechanism. Taken together, our observations suggest that there are different mechanisms at play in each inhibitor bound system considered.

Mutations in PBP2 from ceftriaxone-resistant Neisseria gonorrhoeae alter the dynamics of the β3-β4 loop to favor a low-affinity drug-binding state

Resistance to the extended-spectrum cephalosporin ceftriaxone in the pathogenic bacteria Neisseria gonorrhoeae is conferred by mutations in penicillin-binding protein 2 (PBP2), the lethal target of the antibiotic, but how these mutations exert their effect at the molecular level is unclear. Using solution NMR, X-ray crystallography, and isothermal titration calorimetry, we report that WT PBP2 exchanges dynamically between a low-affinity state with an extended β3–β4 loop conformation and a high-affinity state with an inward β3–β4 loop conformation. Histidine-514, which is located at the boundary of the β4 strand, plays an important role during the exchange between these two conformational states. We also find that mutations present in PBP2 from H041, a ceftriaxone-resistant strain of N. gonorrhoeae, increase resistance to ceftriaxone by destabilizing the inward β3–β4 loop conformation or stabilizing the extended β3–β4 loop conformation to favor the low-affinity drug-binding state. These observations reveal a unique mechanism for ceftriaxone resistance, whereby mutations in PBP2 lower the proportion of target molecules in the high-affinity drug-binding state and thus reduce inhibition at lower drug concentrations.

Using normal mode analysis on protein structural models. How far can we go on our predictions?

Normal mode analysis (NMA) is a fast and inexpensive approach that is largely used to gain insight into functional protein motions, and more recently to create conformations for further computational studies. However, when the protein structure is unknown, the use of computational models is necessary. Here, we analyze the capacity of NMA in internal coordinate space to predict protein motion, its intrinsic flexibility, and atomic displacements, using protein models instead of native structures, and the possibility to use it for model refinement. Our results show that NMA is quite insensitive to modeling errors, but that calculations are strictly reliable only for very accurate models. Our study also suggests that internal NMA is a more suitable tool for the improvement of structural models, and for integrating them with experimental data or in other computational techniques, such as protein docking or more refined molecular dynamics simulations.

Mutations in penicillin-binding protein 2 from cephalosporin-resistant Neisseria gonorrhoeae hinder ceftriaxone acylation by restricting protein dynamics

The global incidence of the sexually transmitted disease gonorrhea is expected to rise due to the spread of Neisseria gonorrhoeae strains with decreased susceptibility to extended-spectrum cephalosporins (ESCs). ESC resistance is conferred by mosaic variants of penicillin-binding protein 2 (PBP2) that have diminished capacity to form acylated adducts with cephalosporins. To elucidate the molecular mechanisms of ESC resistance, we conducted a biochemical and high-resolution structural analysis of PBP2 variants derived from the decreased-susceptibility N. gonorrhoeae strain 35/02 and ESC-resistant strain H041. Our data reveal that mutations both lower affinity of PBP2 for ceftriaxone and restrict conformational changes that normally accompany acylation. Specifically, we observe that a G545S substitution hinders rotation of the β3 strand necessary to form the oxyanion hole for acylation and also traps ceftriaxone in a noncanonical configuration. In addition, F504L and N512Y substitutions appear to prevent bending of the β3-β4 loop that is required to contact the R1 group of ceftriaxone in the active site. Other mutations also appear to act by reducing flexibility in the protein. Overall, our findings reveal that restriction of protein dynamics in PBP2 underpins the ESC resistance of N. gonorrhoeae.

Small Conformational Changes Underlie Evolution of Resistance to NNRTI in HIV Reverse Transcriptase

Despite achieving considerable success in reducing the number of fatalities due to acquired immunodeficiency syndrome, emergence of resistance against the reverse transcriptase (RT) inhibitor drugs remains one of the biggest challenges of the human immunodeficiency virus antiretroviral therapy (ART). Non-nucleoside reverse transcriptase inhibitors (NNRTIs) form a large class of drugs and a crucial component of ART. In NNRTIs, even a single resistance mutation is known to make the drugs completely ineffective. Additionally, several inhibitor-bound RTs with single resistance mutations do not exhibit any significant variations in their three-dimensional structures compared with the inhibitor-bound RT but completely nullify their inhibitory functions. This makes understanding the structural mechanism of these resistance mutations crucial for drug development. Here, we study several single resistance mutations in the allosteric inhibitor (nevirapine)-bound RT to analyze the mechanism of small structural changes leading to these large functional effects. In this study, we have shown that in absence of significant conformational variations in the inhibitor-bound wild-type RT and RT with single resistance mutations, the protein contact network analysis of their static structures, along with molecular dynamics simulations, can be a useful approach to understand the functional effect of small local conformational variations. The simple network analysis exposes the localized contact changes that lead to global rearrangement in the communication pattern within RT. Furthermore, these conformational changes have implications on the overall dynamics of RT. Using various measures, we show that a single resistance mutation can change the network structure and dynamics of RT to behave more like unbound RT, even in the presence of the inhibitor. This combined coarse-grained contact network and molecular dynamics approach promises to be a useful tool to analyze structure-function studies of proteins that show large functional changes with negligible variations in their overall conformation.

New strategy for identifying potential natural HIV-1 non-nucleoside reverse transcriptase inhibitors against drug-resistance: an in silico study

Non-nucleosides reverse transcriptase inhibitors (NNRTIs), specifically targeting the HIV-1 reverse transcriptase (RT), play a unique role in anti-AIDS agents due to their high antiviral potency, structural diversity, and low toxicity in antiretroviral combination therapies used to treat HIV. However, due to the emergence of new drug-resistant strains, the development of novel NNRTIs with adequate potency, improved resistance profiles and less toxicity is highly required. In this work, a novel virtual screening strategy combined with structure-based drug design was proposed to discover the potential inhibitors against drug-resistant HIV strains. Seven structure-variant RTs, ranging from the wild type to a hypothetical multi-mutant were regarded as target proteins to perform structure-based virtual screening. Totally 23 small molecules with good binding affinity were identified from the Traditional Chinese Medicine database (TCM) as potential NNRTIs candidates. Among these hits, (+)-Hinokinin has confirmed anti-HIV activity, and some hits are structurally identical with anti-HIV compounds. Almost all these hits are consistent with external experimental results. Molecular simulations analysis revealed that top 2 hits (Pallidisetin A and Pallidisetin B) bind stably and in high affinity to HIV-RT, which are ready to be experimental confirmed. These results suggested that the strategy we proposed is feasible, trustworthy and effective. Our finding might be helpful in the identification of novel NNRTIs against drug-resistant, and also provide a new clue for the discovery of HIV drugs in natural products.Communicated by Ramaswamy H. Sarma.

Enzymatic Transition States and Drug Design

Transition state theory teaches that chemically stable mimics of enzymatic transition states will bind tightly to their cognate enzymes. Kinetic isotope effects combined with computational quantum chemistry provides enzymatic transition state information with sufficient fidelity to design transition state analogues. Examples are selected from various stages of drug development to demonstrate the application of transition state theory, inhibitor design, physicochemical characterization of transition state analogues, and their progress in drug development.

Structural database resources for biological macromolecules

This Briefing reviews the widely used, currently active, up-to-date databases derived from the worldwide Protein Data Bank (PDB) to facilitate browsing, finding and exploring its entries. These databases contain visualization and analysis tools tailored to specific kinds of molecules and interactions, often including also complex metrics precomputed by experts or external programs, and connections to sequence and functional annotation databases. Importantly, updates of most of these databases involves steps of curation and error checks based on specific expertise about the subject molecules or interactions, and removal of sequence redundancy, both leading to better data sets for mining studies compared with the full list of raw PDB entries. The article presents the databases in groups such as those aimed to facilitate browsing through PDB entries, their molecules and their general information, those built to link protein structure with sequence and dynamics, those specific for transmembrane proteins, nucleic acids, interactions of biomacromolecules with each other and with small molecules or metal ions, and those concerning specific structural features or specific protein families. A few webservers directly connected to active databases, and a few databases that have been discontinued but would be important to have back, are also briefly commented on. Along the Briefing, sample cases where these databases have been used to aid structural studies or advance our knowledge about biological macromolecules are referenced. A few specific examples are also given where using these databases is easier and more informative than using raw PDB data.

Decoding HIV resistance: from genotype to therapy

Genetic variation in HIV poses a major challenge for prevention and treatment of the AIDS pandemic. Resistance occurs by mutations in the target proteins that lower affinity for the drug or alter the protein dynamics, thereby enabling viral replication in the presence of the drug. Due to the prevalence of drug-resistant strains, monitoring the genotype of the infecting virus is recommended. Computational approaches for predicting resistance from genotype data and guiding therapy are discussed. Many prediction methods rely on rules derived from known resistance-associated mutations, however, statistical or machine learning can improve the classification accuracy and assess unknown mutations. Adding classifiers such as information on the atomic structure of the protein can further enhance the predictions.

Conformational Plasticity of the NNRTI-Binding Pocket in HIV-1 Reverse Transcriptase: A Fluorine Nuclear Magnetic Resonance Study

HIV-1 reverse transcriptase (RT) is a major drug target in the treatment of HIV-1 infection. RT inhibitors currently in use include non-nucleoside, allosteric RT inhibitors (NNRTIs), which bind to a hydrophobic pocket, distinct from the enzyme's active site. We investigated RT-NNRTI interactions by solution (19)F nuclear magnetic resonance (NMR), using singly (19)F-labeled RT proteins. Comparison of (19)F chemical shifts of fluorinated RT and drug-resistant variants revealed that the fluorine resonance is a sensitive probe for identifying mutation-induced changes in the enzyme. Our data show that in the unliganded enzyme, the NNRTI-binding pocket is highly plastic and not locked into a single conformation. Upon inhibitor binding, the binding pocket becomes rigidified. In the inhibitor-bound state, the (19)F signal of RT is similar to that of drug-resistant mutant enzymes, distinct from what is observed for the free state. Our results demonstrate the power of (19)F NMR spectroscopy to characterize conformational properties using selectively (19)F-labeled protein.

Structure-Encoded Global Motions and Their Role in Mediating Protein-Substrate Interactions

Recent structure-based computational studies suggest that, in contrast to the classical description of equilibrium fluctuations as wigglings and jigglings, proteins have access to well-defined spectra of collective motions, called intrinsic dynamics, encoded by their structure under native state conditions. In particular, the global modes of motions (at the low frequency end of the spectrum) are shown by multiple studies to be highly robust to minor differences in the structure or to detailed interactions at the atomic level. These modes, encoded by the overall fold, usually define the mechanisms of interactions with substrates. They can be estimated by low-resolution models such as the elastic network models (ENMs) exclusively based on interresidue contact topology. The ability of ENMs to efficiently assess the global motions intrinsically favored by the overall fold as well as the relevance of these predictions to the dominant changes in structure experimentally observed for a given protein in the presence of different substrates suggest that the intrinsic dynamics plays a role in mediating protein-substrate interactions. These observations underscore the functional significance of structure-encoded dynamics, or the importance of the predisposition to favor functional global modes in the evolutionary selection of structures.

Searching for novel scaffold of triazole non-nucleoside inhibitors of HIV-1 reverse transcriptase

Azoles are a promising class of the new generation of HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). From thousands of reported compounds, many possess the same basic structure of an aryl substituted azole ring linked by a thioglycolamide chain with another aromatic ring. In order to find novel extensions for this basic scaffold, we explored the 5-position substitution pattern of triazole NNRTIs using molecular docking followed by the synthesis of selected compounds. We found that heterocyclic substituents in the 5-position of the triazole ring are detrimental to the inhibitory activity of compounds with four-membered thioglycolamide linker and this substitution seems to be viable only for compounds with shorter two-membered linker. Promising compound, N-(4-carboxy-2-chlorophenyl)-2-((4-benzyl-5-methyl-4H-1,2,4-triazol-3-yl)sulfanyl)acetamide, with potent inhibitory activity and acceptable aqueous solubility has been identified in this study that could serve as lead scaffold for the development of novel water-soluble salts of triazole NNRTIs.

WEBnm@ v2.0: Web server and services for comparing protein flexibility

BACKGROUND

Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics-function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins.

RESULTS

We have developed an automated tool for comparative NMA of a set of pre-aligned protein structures. The user can submit a sequence alignment in the FASTA format and the corresponding coordinate files in the Protein Data Bank (PDB) format. The computed normalised squared atomic fluctuations and atomic deformation energies of the submitted structures can be easily compared on graphs provided by the web user interface. The web server provides pairwise comparison of the dynamics of all proteins included in the submitted set using two measures: the Root Mean Squared Inner Product and the Bhattacharyya Coefficient. The Comparative Analysis has been implemented on our web server for NMA, WEBnm@, which also provides recently upgraded functionality for NMA of single protein structures. This includes new visualisations of protein motion, visualisation of inter-residue correlations and the analysis of conformational change using the overlap analysis. In addition, programmatic access to WEBnm@ is now available through a SOAP-based web service. Webnm@ is available at http://apps.cbu.uib.no/webnma .

CONCLUSION

WEBnm@ v2.0 is an online tool offering unique capability for comparative NMA on multiple protein structures. Along with a convenient web interface, powerful computing resources, and several methods for mode analyses, WEBnm@ facilitates the assessment of protein flexibility within protein families and superfamilies. These analyses can give a good view of how the structures move and how the flexibility is conserved over the different structures.

Lightweight object oriented structure analysis: tools for building tools to analyze molecular dynamics simulations

LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development.

Comparing the intrinsic dynamics of multiple protein structures using elastic network models

BACKGROUND

Elastic network models (ENMs) are based on the simple idea that a protein can be described as a set of particles connected by springs, which can then be used to describe its intrinsic flexibility using, for example, normal mode analysis. Since the introduction of the first ENM by Monique Tirion in 1996, several variants using coarser protein models have been proposed and their reliability for the description of protein intrinsic dynamics has been widely demonstrated. Lately an increasing number of studies have focused on the meaning of slow dynamics for protein function and its potential conservation through evolution. This leads naturally to comparisons of the intrinsic dynamics of multiple protein structures with varying levels of similarity.

SCOPE OF REVIEW

We describe computational strategies for calculating and comparing intrinsic dynamics of multiple proteins using elastic network models, as well as a selection of examples from the recent literature.

MAJOR CONCLUSIONS

The increasing interest for comparing dynamics across protein structures with various levels of similarity, has led to the establishment and validation of reliable computational strategies using ENMs. Comparing dynamics has been shown to be a viable way for gaining greater understanding for the mechanisms employed by proteins for their function. Choices of ENM parameters, structure alignment or similarity measures will likely influence the interpretation of the comparative analysis of protein motion.

GENERAL SIGNIFICANCE

Understanding the relation between protein function and dynamics is relevant to the fundamental understanding of protein structure-dynamics-function relationship. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Structure-based simulations reveal concerted dynamics of GPCR activation

G protein-coupled receptors (GPCRs) are a vital class of proteins that transduce biological signals across the cell membrane. However, their allosteric activation mechanism is not fully understood; crystal structures of active and inactive receptors have been reported, but the functional pathway between these two states remains elusive. Here, we use structure-based (Gō-like) models to simulate activation of two GPCRs, rhodopsin and the β₂ adrenergic receptor (β₂AR). We used data-derived reaction coordinates that capture the activation mechanism for both proteins, showing that activation proceeds through quantitatively different paths in the two systems. Both reaction coordinates are determined from the dominant concerted motions in the simulations so the technique is broadly applicable. There were two surprising results. First, the main structural changes in the simulations were distributed throughout the transmembrane bundle, and not localized to the obvious areas of interest, such as the intracellular portion of Helix 6. Second, the activation (and deactivation) paths were distinctly nonmonotonic, populating states that were not simply interpolations between the inactive and active structures. These transitions also suggest a functional explanation for β₂AR's basal activity: it can proceed through a more broadly defined path during the observed transitions.

Molecular dynamics study of HIV-1 RT-DNA-nevirapine complexes explains NNRTI inhibition and resistance by connection mutations

HIV-1 reverse transcriptase (RT) is a multifunctional enzyme that is targeted by nucleoside analogs (NRTIs) and non-nucleoside RT inhibitors (NNRTIs). NNRTIs are allosteric inhibitors of RT, and constitute an integral part of several highly active antiretroviral therapy regimens. Under selective pressure, HIV-1 acquires resistance against NNRTIs primarily by selecting mutations around the NNRTI pocket. Complete RT sequencing of clinical isolates revealed that spatially distal mutations arising in connection and the RNase H domain also confer NNRTI resistance and contribute to NRTI resistance. However, the precise structural mechanism by which the connection domain mutations confer NNRTI resistance is poorly understood. We performed 50-ns molecular dynamics (MD) simulations, followed by essential dynamics, free-energy landscape analyses, and network analyses of RT-DNA, RT-DNA-nevirapine (NVP), and N348I/T369I mutant RT-DNA-NVP complexes. MD simulation studies revealed altered global motions and restricted conformational landscape of RT upon NVP binding. Analysis of protein structure network parameters demonstrated a dissortative hub pattern in the RT-DNA complex and an assortative hub pattern in the RT-DNA-NVP complex suggesting enhanced rigidity of RT upon NVP binding. The connection subdomain mutations N348I/T369I did not induce any significant structural change; rather, these mutations modulate the conformational dynamics and alter the long-range allosteric communication network between the connection subdomain and NNRTI pocket. Insights from the present study provide a structural basis for the biochemical and clinical findings on drug resistance caused by the connection and RNase H mutations.