The importance of slow motions for protein functional loops

The Structural Role of N170 in Substrate-Assisted Deacylation in KPC-2 β-Lactamase

The amino acid substitutions in Klebsiella pneumoniae carbapenemase 2 (KPC-2) that have arisen in the clinic are observed to lead to the development of resistance to ceftazidime-avibactam, a preferred treatment for KPC bearing Gram-negative bacteria. Specific substitutions in the omega loop (R164-D179) result in changes in the structure and function of the enzyme, leading to alterations in substrate specificity, decreased stability, and more recently observed, increased resistance to ceftazidime/avibactam. Using accelerated rare-event sampling well-tempered metadynamics simulations, we explored in detail the structural role of R164 and D179 variants that are described to confer ceftazidime/avibactam resistance. The buried conformation of D179 substitutions produce a pronounced structural disorder in the omega loop - more than R164 mutants, where the crystallographic omega loop structure remains mostly intact. Our findings also reveal that the conformation of N170 plays an underappreciated role impacting drug binding and restricting deacylation. The results further support the hypothesis that KPC-2 D179 variants employ substrate-assisted catalysis for ceftazidime hydrolysis, involving the ring amine of the aminothiazole group to promote deacylation and catalytic turnover. Moreover, the shift in the WT conformation of N170 contributes to reduced deacylation and an altered spectrum of enzymatic activity.

Emerging variants of SARS-CoV-2 NSP10 highlight strong functional conservation of its binding to two non-structural proteins, NSP14 and NSP16

The coronavirus SARS-CoV-2 protects its RNA from being recognized by host immune responses by methylation of its 5' end, also known as capping. This process is carried out by two enzymes, non-structural protein 16 (NSP16) containing 2'-O-methyltransferase and NSP14 through its N7 methyltransferase activity, which are essential for the replication of the viral genome as well as evading the host's innate immunity. NSP10 acts as a crucial cofactor and stimulator of NSP14 and NSP16. To further understand the role of NSP10, we carried out a comprehensive analysis of >13 million globally collected whole-genome sequences (WGS) of SARS-CoV-2 obtained from the Global Initiative Sharing All Influenza Data (GISAID) and compared it with the reference genome Wuhan/WIV04/2019 to identify all currently known variants in NSP10. T12I, T102I, and A104V in NSP10 have been identified as the three most frequent variants and characterized using X-ray crystallography, biophysical assays, and enhanced sampling simulations. In contrast to other proteins such as spike and NSP6, NSP10 is significantly less prone to mutation due to its crucial role in replication. The functional effects of the variants were examined for their impact on the binding affinity and stability of both NSP14-NSP10 and NSP16-NSP10 complexes. These results highlight the limited changes induced by variant evolution in NSP10 and reflect on the critical roles NSP10 plays during the SARS-CoV-2 life cycle. These results also indicate that there is limited capacity for the virus to overcome inhibitors targeting NSP10 via the generation of variants in inhibitor binding pockets.

The Assembly Switch Mechanism of FtsZ Filament Revealed by All-Atom Molecular Dynamics Simulations and Coarse-Grained Models

Bacterial cytoskeletal protein FtsZ binds and hydrolyzes GTP, and assembles into dynamic filaments that are essential for cell division. Here, we used a multi-scale computational strategy that combined all-atom molecular dynamics (MD) simulations and coarse-grained models to reveal the conformational dynamics of assembled FtsZ. We found that the top end of a filament is highly dynamic and can undergo T-to-R transitions in both GTP- and GDP-bound states. We observed several subcategories of nucleation related dimer species, which leading to a feasible nucleation pathway. In addition, we observed that FtsZ filament exhibits noticeable amounts of twisting, indicating a substantial helicity of the FtsZ filament. These results agree with the previously models and experimental data. Anisotropy network model (ANM) analysis revealed a polymerization enhanced assembly cooperativity, and indicated that the cooperative motions in FtsZ are encoded in the structure. Taken together, our study provides a molecular-level understanding of the diversity of the structural states of FtsZ and the relationships among polymerization, hydrolysis, and cooperative assembly, which should shed new light on the molecular basis of FtsZ’s cooperativity.

Inactivation of PP2A by a recurrent mutation drives resistance to MEK inhibitors

The serine/threonine Protein Phosphatase 2A (PP2A) functions as a tumor suppressor by negatively regulating multiple oncogenic signaling pathways. The canonical PP2A holoenzyme comprises a scaffolding subunit (PP2A Aα/β), which serves as the platform for binding of both the catalytic C subunit and one regulatory B subunit. Somatic heterozygous missense mutations in PPP2R1A, the gene encoding the PP2A Aα scaffolding subunit, have been identified across multiple cancer types, but the effects of the most commonly mutated residue, Arg-183, on PP2A function have yet to be fully elucidated. In this study, we used a series of cellular and in vivo models and discovered that the most frequent Aα R183W mutation formed alternative holoenzymes by binding of different PP2A regulatory subunits compared with wild-type Aα, suggesting a rededication of PP2A functions. Unlike wild-type Aα, which suppressed tumorigenesis, the R183W mutant failed to suppress tumor growth in vivo through activation of the MAPK pathway in RAS-mutant transformed cells. Furthermore, cells expressing R183W were less sensitive to MEK inhibitors. Taken together, our results demonstrate that the R183W mutation in PP2A Aα scaffold abrogates the tumor suppressive actions of PP2A, thereby potentiating oncogenic signaling and reducing drug sensitivity of RAS-mutant cells.

The Highly Recurrent PP2A Aα-Subunit Mutation P179R Alters Protein Structure and Impairs PP2A Enzyme Function to Promote Endometrial Tumorigenesis

Somatic mutation of the protein phosphatase 2A (PP2A) Aα-subunit gene PPP2R1A is highly prevalent in high-grade endometrial carcinoma. The structural, molecular, and biological basis by which the most recurrent endometrial carcinoma-specific mutation site P179 facilitates features of endometrial carcinoma malignancy has yet to be fully determined. Here, we used a series of structural, biochemical, and biological approaches to investigate the impact of the P179R missense mutation on PP2A function. Enhanced sampling molecular dynamics simulations showed that arginine-to-proline substitution at the P179 residue changes the protein's stable conformation profile. A crystal structure of the tumor-derived PP2A mutant revealed marked changes in A-subunit conformation. Binding to the PP2A catalytic subunit was significantly impaired, disrupting holoenzyme formation and enzymatic activity. Cancer cells were dependent on PP2A disruption for sustained tumorigenic potential, and restoration of wild-type Aα in a patient-derived P179R-mutant cell line restored enzyme function and significantly attenuated tumorigenesis and metastasis in vivo. Furthermore, small molecule-mediated therapeutic reactivation of PP2A significantly inhibited tumorigenicity in vivo. These outcomes implicate PP2A functional inactivation as a critical component of high-grade endometrial carcinoma disease pathogenesis. Moreover, they highlight PP2A reactivation as a potential therapeutic strategy for patients who harbor P179R PPP2R1A mutations. SIGNIFICANCE: This study characterizes a highly recurrent, disease-specific PP2A PPP2R1A mutation as a driver of endometrial carcinoma and a target for novel therapeutic development.See related commentary by Haines and Huang, p. 4009.

Deciphering the Evolution of Cephalosporin Resistance to Ceftolozane-Tazobactam in Pseudomonas aeruginosa

The presence of β-lactamases (e.g., PDC-3) that have naturally evolved and acquired the ability to break down β-lactam antibiotics (e.g., ceftazidime and ceftolozane) leads to highly resistant and potentially lethal Pseudomonas aeruginosa infections. We show that wild-type PDC-3 β-lactamase forms an acyl enzyme complex with ceftazidime, but it cannot accommodate the structurally similar ceftolozane that has a longer R2 side chain with increased basicity. A single amino acid substitution from a glutamate to a lysine at position 221 in PDC-3 (E221K) causes the tyrosine residue at 223 to adopt a new position poised for efficient hydrolysis of both cephalosporins. The importance of the mechanism of action of the E221K variant, in particular, is underscored by its evolutionary recurrences in multiple bacterial species. Understanding the biochemical and molecular basis for resistance is key to designing effective therapies and developing new β-lactam/β-lactamase inhibitor combinations.

Pseudomonas aeruginosa produces a class C β-lactamase (e.g., PDC-3) that robustly hydrolyzes early generation cephalosporins often at the diffusion limit; therefore, bacteria possessing these β-lactamases are resistant to many β-lactam antibiotics. In response to this significant clinical threat, ceftolozane, a 3′ aminopyrazolium cephalosporin, was developed. Combined with tazobactam, ceftolozane promised to be effective against multidrug-resistant P. aeruginosa. Alarmingly, Ω-loop variants of the PDC β-lactamase (V213A, G216R, E221K, E221G, and Y223H) were identified in ceftolozane/tazobactam-resistant P. aeruginosa clinical isolates. Herein, we demonstrate that the Escherichia coli strain expressing the E221K variant of PDC-3 had the highest minimum inhibitory concentrations (MICs) against a panel of β-lactam antibiotics, including ceftolozane and ceftazidime, a cephalosporin that differs in structure largely in the R2 side chain. The k_cat values of the E221K variant for both substrates were equivalent, whereas the K_m for ceftolozane (341 ± 64 µM) was higher than that for ceftazidime (174 ± 20 µM). Timed mass spectrometry, thermal stability, and equilibrium unfolding studies revealed key mechanistic insights. Enhanced sampling molecular dynamics simulations identified conformational changes in the E221K variant Ω-loop, where a hidden pocket adjacent to the catalytic site opens and stabilizes ceftolozane for efficient hydrolysis. Encouragingly, the diazabicyclooctane β-lactamase inhibitor avibactam restored susceptibility to ceftolozane and ceftazidime in cells producing the E221K variant. In addition, a boronic acid transition state inhibitor, LP-06, lowered the ceftolozane and ceftazidime MICs by 8-fold for the E221K-expressing strain. Understanding these structural changes in evolutionarily selected variants is critical toward designing effective β-lactam/β-lactamase inhibitor therapies for P. aeruginosa infections.

Detecting transitions in protein dynamics using a recurrence quantification analysis based bootstrap method

Background

Proteins undergo conformational transitions over different time scales. These transitions are closely intertwined with the protein’s function. Numerous standard techniques such as principal component analysis are used to detect these transitions in molecular dynamics simulations. In this work, we add a new method that has the ability to detect transitions in dynamics based on the recurrences in the dynamical system. It combines bootstrapping and recurrence quantification analysis. We start from the assumption that a protein has a “baseline” recurrence structure over a given period of time. Any statistically significant deviation from this recurrence structure, as inferred from complexity measures provided by recurrence quantification analysis, is considered a transition in the dynamics of the protein.

Results

We apply this technique to a 132 ns long molecular dynamics simulation of the β-Lactamase Inhibitory Protein BLIP. We are able to detect conformational transitions in the nanosecond range in the recurrence dynamics of the BLIP protein during the simulation. The results compare favorably to those extracted using the principal component analysis technique.

Conclusions

The recurrence quantification analysis based bootstrap technique is able to detect transitions between different dynamics states for a protein over different time scales. It is not limited to linear dynamics regimes, and can be generalized to any time scale. It also has the potential to be used to cluster frames in molecular dynamics trajectories according to the nature of their recurrence dynamics. One shortcoming for this method is the need to have large enough time windows to insure good statistical quality for the recurrence complexity measures needed to detect the transitions.

The adaptive nature of protein residue networks

Protein residue networks PRNs are used to describe proteins. These networks are usually based on an average structure for the protein. However, proteins are dynamic entities that are affected by their surroundings. In this work, we study the effect of temperatures above and below the protein dynamical transition temperature(≈200 K), on three important network parameters gleaned from weighted PRNs for the solvated β-lactamase inhibitory protein BLIP: the betweenness centrality B, the closeness centrality C, and the clustering coefficient CC. The B and C values will be extracted for each node from PRNs at six different temperatures: 150 K, 180 K, 200 K, 220 K, 250 K, and 310 K respectively. The average value for the CC for each PRN will also be calculated at each temperature, respectively. We find that at temperatures ≤200 K, the network nodes with the most significant B and C values tend to have lower relative solvent accessibility RSA values, and to fall within the protein secondary structure elements (α helices and β sheets). At temperatures >200 K, the significant nodes in terms of B and C tend to have larger RSA values, and to fall on the connecting loops in the protein. The average CC decreases in value for the PRNs up to 200 K, and then remains basically constant above 200 K. This clearly shows that any conclusions based on static PRNs should be handled with care. The dynamic nature of proteins and its coupling to the surrounding environment should be taken into consideration when using the PRN paradigm. Proteins 2017; 85:917-923. © 2016 Wiley Periodicals, Inc.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events.

Similarity in Shape Dictates Signature Intrinsic Dynamics Despite No Functional Conservation in TIM Barrel Enzymes

The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 β-strand-α-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the β-barrel core is highly rigid, while the α-helices that flank the β-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the α-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design.

How an Inhibitor Bound to Subunit Interface Alters Triosephosphate Isomerase Dynamics

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

Structural and functional analysis of Hikeshi, a new nuclear transport receptor of Hsp70s

Hikeshi is a nuclear transport receptor required for cell survival after stress. It mediates heat-shock-induced nuclear import of 70 kDa heat-shock proteins (Hsp70s) through interactions with FG-nucleoporins (FG-Nups), which are proteins in nuclear pore complexes (NPCs). Here, the crystal structure of human Hikeshi is presented at 1.8 Å resolution. Hikeshi forms an asymmetric homodimer that is responsible for the interaction with Hsp70s. The asymmetry of Hikeshi arises from the distinct conformation of the C-terminal domain (CTD) and the flexibility of the linker regions of each monomer. Structure-guided mutational analyses showed that both the flexible linker region and the CTD are important for nuclear import of Hsp70. Pull-down assays revealed that only full-length Hsp70s can interact with Hikeshi. The N-terminal domain (NTD) consists of a jelly-roll/β-sandwich fold structure which contains hydrophobic pockets involved in FG-Nup recognition. A unique extended loop (E-loop) in the NTD is likely to regulate the interactions of Hikeshi with FG-Nups. The crystal structure of Hikeshi explains how Hikeshi participates in the regulation of nuclear import through the recognition of FG-Nups and which part of Hikeshi affects its binding to Hsp70. This study is the first to yield structural insight into this highly unique import receptor.

Common functionally important motions of the nucleotide-binding domain of Hsp70

The 70 kDa heat shock proteins (Hsp70) are a family of molecular chaperones involved in protein folding, aggregate prevention, and protein disaggregation. They consist of the substrate-binding domain (SBD) that binds client substrates, and the nucleotide-binding domain (NBD), whose cycles of nucleotide hydrolysis and exchange underpin the activity of the chaperone. To characterize the structure-function relationships that link the binding state of the NBD to its conformational behavior, we analyzed the dynamics of the NBD of the Hsp70 chaperone from Bos taurus (PDB 3C7N:B) by all-atom canonical molecular dynamics simulations. It was found that essential motions within the NBD fall into three major classes: the mutual class, reflecting tendencies common to all binding states, and the ADP- and ATP-unique classes, which reflect conformational trends that are unique to either the ADP- or ATP-bound states, respectively. "Mutual" class motions generally describe "in-plane" and/or "out-of-plane" (scissor-like) rotation of the subdomains within the NBD. This result is consistent with experimental nuclear magnetic resonance data on the NBD. The "unique" class motions target specific regions on the NBD, usually surface loops or sites involved in nucleotide binding and are, therefore, expected to be involved in allostery and signal transmission. For all classes, and especially for those of the "unique" type, regions of enhanced mobility can be identified; these are termed "hot spots," and their locations generally parallel those found by NMR spectroscopy. The presence of magnesium and potassium cations in the nucleotide-binding pocket was also found to influence the dynamics of the NBD significantly.

Protein conformational populations and functionally relevant substates

Functioning proteins do not remain fixed in a unique structure, but instead they sample a range of conformations facilitated by motions within the protein. Even in the native state, a protein exists as a collection of interconverting conformations driven by thermodynamic fluctuations. Motions on the fast time scale allow a protein to sample conformations in the nearby area of its conformational landscape, while motions on slower time scales give it access to conformations in distal areas of the landscape. Emerging evidence indicates that protein landscapes contain conformational substates with dynamic and structural features that support the designated function of the protein. Nuclear magnetic resonance (NMR) experiments provide information about conformational ensembles of proteins. X-ray crystallography allows researchers to identify the most populated states along the landscape, and computational simulations give atom-level information about the conformational substates of different proteins. This ability to characterize and obtain quantitative information about the conformational substates and the populations of proteins within them is allowing researchers to better understand the relationship between protein structure and dynamics and the mechanisms of protein function. In this Account, we discuss recent developments and challenges in the characterization of functionally relevant conformational populations and substates of proteins. In some enzymes, the sampling of functionally relevant conformational substates is connected to promoting the overall mechanism of catalysis. For example, the conformational landscape of the enzyme dihydrofolate reductase has multiple substates, which facilitate the binding and the release of the cofactor and substrate and catalyze the hydride transfer. For the enzyme cyclophilin A, computational simulations reveal that the long time scale conformational fluctuations enable the enzyme to access conformational substates that allow it to attain the transition state, therefore promoting the reaction mechanism. In the long term, this emerging view of proteins with conformational substates has broad implications for improving our understanding of enzymes, enzyme engineering, and better drug design. Researchers have already used photoactivation to modulate protein conformations as a strategy to develop a hypercatalytic enzyme. In addition, the alteration of the conformational substates through binding of ligands at locations other than the active site provides the basis for the design of new medicines through allosteric modulation.

Coupling between catalytic loop motions and enzyme global dynamics

Catalytic loop motions facilitate substrate recognition and binding in many enzymes. While these motions appear to be highly flexible, their functional significance suggests that structure-encoded preferences may play a role in selecting particular mechanisms of motions. We performed an extensive study on a set of enzymes to assess whether the collective/global dynamics, as predicted by elastic network models (ENMs), facilitates or even defines the local motions undergone by functional loops. Our dataset includes a total of 117 crystal structures for ten enzymes of different sizes and oligomerization states. Each enzyme contains a specific functional/catalytic loop (10–21 residues long) that closes over the active site during catalysis. Principal component analysis (PCA) of the available crystal structures (including apo and ligand-bound forms) for each enzyme revealed the dominant conformational changes taking place in these loops upon substrate binding. These experimentally observed loop reconfigurations are shown to be predominantly driven by energetically favored modes of motion intrinsically accessible to the enzyme in the absence of its substrate. The analysis suggests that robust global modes cooperatively defined by the overall enzyme architecture also entail local components that assist in suitable opening/closure of the catalytic loop over the active site.

Protein loops have critical roles in ligand binding and catalysis. An unresolved issue in this context is the extent to which the intrinsic dynamics of proteins predispose loops to perform their molecular function. In this work, we (i) critically examine the structural changes undergone by functional/catalytic loops based on a set of enzyme crystal structures in the presence/absence of a ligand, and (ii) examine to what extent those motions are correlated with, or driven by, the global modes that are predictable using simplified, physics-based models. Using a dataset of 117 structures for ten enzymes of different sizes and oligomerization states, we show that the collective modes defined by the protein topology favor loop rearrangements in reasonable agreement with those experimentally observed upon activation. These results suggest that simple but robust motions encoded by the entire architecture, not the local binding site only, assist in binding of the ligand, positioning of the catalytic loop, and/or sequestration of the catalytic site, which in turn, enable efficient catalysis.

Elastic network normal modes provide a basis for protein structure refinement

It is well recognized that thermal motions of atoms in the protein native state, the fluctuations about the minimum of the global free energy, are well reproduced by the simple elastic network models (ENMs) such as the anisotropic network model (ANM). Elastic network models represent protein dynamics as vibrations of a network of nodes (usually represented by positions of the heavy atoms or by the C(α) atoms only for coarse-grained representations) in which the spatially close nodes are connected by harmonic springs. These models provide a reliable representation of the fluctuational dynamics of proteins and RNA, and explain various conformational changes in protein structures including those important for ligand binding. In the present paper, we study the problem of protein structure refinement by analyzing thermal motions of proteins in non-native states. We represent the conformational space close to the native state by a set of decoys generated by the I-TASSER protein structure prediction server utilizing template-free modeling. The protein substates are selected by hierarchical structure clustering. The main finding is that thermal motions for some substates, overlap significantly with the deformations necessary to reach the native state. Additionally, more mobile residues yield higher overlaps with the required deformations than do the less mobile ones. These findings suggest that structural refinement of poorly resolved protein models can be significantly enhanced by reduction of the conformational space to the motions imposed by the dominant normal modes.