Large Conformational Transitions Research Articles

Enhanced sampling strategies for molecular simulation of DNA

AbstractMolecular dynamics (MD) simulations can provide detailed insights into complex molecular systems, such as DNA, at high resolution in space and time. Using current computer architectures, time scales of tens of microseconds are feasible with contemporary all‐atom force fields. However, these timescales are insufficient to accurately characterize large conformational transitions in DNA and compare calculations to experimental data. This review discusses the advantages and drawbacks of two simulation approaches to overcome the timescale challenge. The first approach is based on adding biasing potentials to the system to drive transitions. Umbrella sampling, steered MD, and metadynamics are examples of these methods. A key challenge of such methods is the necessity of selecting one or a few efficient coordinates, commonly referred to as collective variables (CVs), along which to apply the biasing potential. The path‐metadynamics methodology addresses this issue by finding the optimal route(s) between states in a multi‐dimensional CV space. The second strategy is path sampling, which focuses MD simulations on the transitions. The assumption is that even though transitions between states are rare, they are generally fast. Stopping the simulations as soon as they reach a stable state can significantly increase simulation efficiency. We introduce these methods on the two‐dimensional Müller–Brown potential. DNA applications are featured for two different processes: the Watson–Crick–Franklin to Hoogsteen transition in adenine–thymine base pairs and the binding of a DNA‐binding protein domain to DNA.This article is categorized under: Molecular and Statistical Mechanics Molecular Dynamics and Monte‐Carlo Methods Molecular and Statistical Mechanics Free Energy Methods Software Simulation Methods

A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data.

X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.

Evaluation of conformational transitions of h-BRCA2 functional domain and unclassified variant Arg2502Cys using multimodal approach

Breast cancer type 2 susceptibility (BRCA2) protein plays an essential role in the repair mechanism of DNA double-strand breaks and interstrand cross-links by Homologous recombination. Germline mutations identified in the BRCA2 gene confer an increased risk of hereditary breast and ovarian cancer. Missense mutations are identified all over the gene, including the DNA binding region of BRCA2 that interacts with FANCD2. However, the majority of these missense mutations are classified as ‘Variants of Uncertain Significance’ due to a lack of structural, functional and clinical correlations. Therefore, multi-disciplinary in-silico, in-vitro and biophysical approaches have been explored to characterize an unclassified missense mutation, BRCA2 Arg2502Cys, identified from a case-control study. Circular-dichroism and Fluorescence spectroscopy show that the Arg2502Cys mutation in hBRCA2 (residues 2350–2545) decreases the α-helical/β-sheet propensity of the wild-type protein and perturb the tertiary structure conformation. Molecular dynamics simulations revealed alteration in the intramolecular H-bonds, overall compactness and stability of the hydrophobic core were observed in the mutant protein. Principle component analysis indicated that Arg2502Cys mutant exhibited comparatively large conformational transitions and periodic fluctuation. Therefore, to our conclusion, BRCA2 Arg2502Cys mutant perturbed the structural integrity and conformational dynamics of BRCA2.

Deciphering collaborative sidechain motions in proteins during molecular dynamics simulations

The dynamic structure of proteins is essential for their functions and may include large conformational transitions which can be studied by molecular dynamics (MD) simulations. However, details of these transitions are difficult to automatically track. To facilitate their analysis, we developed two scores of correlation between sidechain dihedral angles. The CIRCULAR and OMES scores are computed from, respectively, dihedral angle values and rotamer distributions. As a case study, we applied our methods to an activation-like transition of the chemokine receptor CXCR4, observed during accelerated MD simulations. The principal component analysis of the correlation matrices was consistent with the networking structure of the top ranking pairs. Both scores identify a set of residues whose “collaborative” sidechain rotamerization immediately preceded or accompanied the conformational transition of CXCR4. Detailed analysis of the sequential order of these rotamerizations suggests that an allosteric mechanism, involving the outward motion of an asparagine residue in transmembrane helix 3, might be a prerequisite to the large scale conformational transition of CXCR4. This case study provides the proof-of-concept that the correlation methods developed here are valuable exploratory techniques to help decipher complex reactional pathways.

The Answer Lies in the Energy: How Simple Atomistic Molecular Dynamics Simulations May Hold the Key to Epitope Prediction on the Fully Glycosylated SARS-CoV-2 Spike Protein.

SARS-CoV-2 is a health threat with dire socioeconomical consequences. As the crucial mediator of infection, the viral glycosylated spike protein (S) has attracted the most attention and is at the center of efforts to develop therapeutics and diagnostics. Herein, we use an original decomposition approach to identify energetically uncoupled substructures as antibody binding sites on the fully glycosylated S. Crucially, all that is required are unbiased MD simulations; no prior knowledge of binding properties or ad hoc parameter combinations is needed. Our results are validated by experimentally confirmed structures of S in complex with anti- or nanobodies. We identify poorly coupled subdomains that are poised to host (several) epitopes and potentially involved in large functional conformational transitions. Moreover, we detect two distinct behaviors for glycans: those with stronger energetic coupling are structurally relevant and protect underlying peptidic epitopes, and those with weaker coupling could themselves be prone to antibody recognition.

On the activation and deactivation pathways of the Lck kinase domain: a computational study.

Here we report the description of the conformational pathways connecting the Lck active and inactive states by means of all-atoms molecular dynamics simulations coupled to an enhancing sampling methodology. By such an approach, we describe the major structural determinants characterizing these large conformational transitions and compare such pathways to those obtained for a similar kinase, i.e. c-Src. Our results show that both the activation and deactivation processes could follow distinct pathways, differentiated by the order by which the A-loop and the C-helix regions rearrange.

Single Molecule FRET Reveals Lipid Induced Conformational Changes in Cytoplasmic Domain of Kir2.1

Anionic phospholipids are common regulators of ion channel activity, including Kir2.1, an inward rectifying potassium channel crucial for setting and maintaining resting membrane potential in many tissues, which is activated specifically by PIP2 and phosphatidyl glycerol (PG). Crystal structures indicate that a simple upward translocation of the cytoplasmic Kir domain is induced by PIP2 and PG binding. However, recent computational and single-molecule FRET experiments show more complex intra-domain movements and rotation in the Kir domain of prokaryotic KirBac1.1 upon PIP2 binding. Single molecule FRET measurements on eukaryotic human Kir2.1 indicate similar complex motions that are not detected in static crystal structures. Our measurements indicate dynamic conformational ‘breathing’ throughout the Kir domain, suggesting greater flexibility in the intracellular domain of ion channels than may be apparent in structural studies. Specifically, our data indicate a PIP2 dependent shifts in average single molecule FRET (smFRET) distributions, with outward motions seen prior to the slide helix (residue 59) and an inward motion seen at the base (residues 286 and 288) consistent with a twisting motion of the Kir domain that was previously shown to be associated with opening in KirBac1.1. In the absence of PIP2, smFRET signals are very dynamic with relatively large (>20A) motions at specific residues. PIP2 stabilizes the conformational dynamics of the Kir domain, with less transitions between structural states, and reduction in the occurrence of large conformational transitions.

Charge Transfer and Chemo-Mechanical Coupling in Respiratory Complex I

The mitochondrial respiratory chain formed by five protein complexes utilizes energy from catabolic processes to synthesize ATP. Complex I, the first and the largest protein complex of the chain, harvests electrons from NADH to reduce quinone, while pumping protons across the mitochondrial membrane. Detailed knowledge of the working principle of such coupled charge-transfer processes remains fragmentary due to bottlenecks arising from large conformational transitions and their interplay with the hydrated proton pathways. A recent study has reported the crystallographic structure of complex I from Thermus thermophilus, encasing 16 subunits with 9 iron-sulfur clusters, which are reduced by electrons from NADH. Here, we have used large-scale molecular dynamics simulations to study the chemo-mechanical coupling between redox changes of the iron-sulfur clusters and conformational transitions across complex I. First, we identify the redox switches within complex I, which couple the dynamics of the quinone binding pocket to the site of NADH reduction. Second, our free-energy calculations reveal that the affinity of the quinone, specifically menaquinone, for the binding-site is higher than that of its reduced, menaquinol form – a design essential for menaquinol release. Third, long-range hydrogen-bond networks connecting the quinone-binding site to the TM subunits are found to be responsible for proton pumping. Random insertion of molecular oxygen in reduced complex I illuminates an enhanced access to the iron-sulfur clusters, conducive to the formation of reactive oxygen species. Our simulations reveal molecular design principles linking redox reactions and proton translocation in complex I.

Efficient and Accurate Modeling of Conformational Transitions in Proteins: The Case of c-Src Kinase.

The theoretical computational modeling of large conformational transitions occurring in biomolecules still represents a challenge. Here, we present an accurate "in silico" description of the activation and deactivation mechanisms of human c-Src kinases, a fundamental process regulating several crucial cell functions. Our results clearly show that by applying an efficient and automated algorithm able to drive the molecular dynamics (MD) sampling along the pathway between the two c-Src conformational states-the active state and the inactive state-it is possible to accurately describe, at reduced computational costs, the molecular mechanism underlying these large conformational rearrangements. This procedure, combining the MD simulations with the sampling along the well-defined principal motions connecting the two conformational states, allows to provide a description well beyond the present computational limits, and it is easily applicable to different systems where the structures of both the initial and final states are known.

Examining a Thermodynamic Order Parameter of Protein Folding

Dimensionality reduction with a suitable choice of order parameters or reaction coordinates is commonly used for analyzing high-dimensional time-series data generated by atomistic biomolecular simulations. So far, geometric order parameters, such as the root mean square deviation, fraction of native amino acid contacts, and collective coordinates that best characterize rare or large conformational transitions, have been prevailing in protein folding studies. Here, we show that the solvent-averaged effective energy, which is a thermodynamic quantity but unambiguously defined for individual protein conformations, serves as a good order parameter of protein folding. This is illustrated through the application to the folding-unfolding simulation trajectory of villin headpiece subdomain. We rationalize the suitability of the effective energy as an order parameter by the funneledness of the underlying protein free energy landscape. We also demonstrate that an improved conformational space discretization is achieved by incorporating the effective energy. The most distinctive feature of this thermodynamic order parameter is that it works in pointing to near-native folded structures even when the knowledge of the native structure is lacking, and the use of the effective energy will also find applications in combination with methods of protein structure prediction.

Rotation-Activated and Cooperative Zipping Characterize Class I Viral Fusion Protein Dynamics

Class I viral fusion proteins are α-helical proteins that facilitate membrane fusion between viral and host membranes through large conformational transitions. Although prefusion and postfusion crystal structures have been solved for many of these proteins, details about how they transition between these states have remained elusive. This work presents the first, to our knowledge, computational survey of transitions between pre- and postfusion configurations for several class I viral fusion proteins using structure-based models to analyze their dynamics. As suggested by their structural similarities, all proteins share common mechanistic features during their transitions that can be characterized by a diffusive rotational search followed by cooperative N- and C-terminal zipping. Instead of predicting a stable spring-loaded intermediate, our model suggests that helical bundle formation is mediated by N- and C-terminal interactions late in the transition. Shared transition features suggest a global mechanism in which fusion is activated by slow protein-core rotation.

A probabilistic network model for structural transitions in biomolecules.

Biological macromolecules often undergo large conformational rearrangements during a functional cycle. To simulate these structural transitions with full atomic detail typically demands extensive computational resources. Moreover, it is unclear how to incorporate, in a principled way, additional experimental information that could guide the structural transition. This article develops a probabilistic model for conformational transitions in biomolecules. The model can be viewed as a network of anharmonic springs that break, if the experimental data support the rupture of bonds. Hamiltonian Monte Carlo in internal coordinates is used to infer structural transitions from experimental data, thereby sampling large conformational transitions without distorting the structure. The model is benchmarked on a large set of conformational transitions. Moreover, we demonstrate the use of the probabilistic network model for integrative modeling of macromolecular complexes based on data from crosslinking followed by mass spectrometry.

Structural intermediates and directionality of the swiveling motion of Pyruvate Phosphate Dikinase

Pyruvate phosphate dikinase (PPDK) is a vital enzyme in cellular energy metabolism catalyzing the ATP- and P i -dependent formation of phosphoenolpyruvate from pyruvate in C4 -plants, but the reverse reaction forming ATP in bacteria and protozoa. The multi-domain enzyme is considered an efficient molecular machine that performs one of the largest single domain movements in proteins. However, a comprehensive understanding of the proposed swiveling domain motion has been limited by not knowing structural intermediates or molecular dynamics of the catalytic process. Here, we present crystal structures of PPDKs from Flaveria, a model genus for studying the evolution of C4 -enzymes from phylogenetic ancestors. These structures resolve yet unknown conformational intermediates and provide the first detailed view on the large conformational transitions of the protein in the catalytic cycle. Independently performed unrestrained MD simulations and configurational free energy calculations also identified these intermediates. In all, our experimental and computational data reveal strict coupling of the CD swiveling motion to the conformational state of the NBD. Moreover, structural asymmetries and nucleotide binding states in the PPDK dimer support an alternate binding change mechanism for this intriguing bioenergetic enzyme.

Temperature-Sensitive Gating of TRPV1 Channel as Probed by Atomistic Simulations

Heat-activated transient receptor potential channel TRPV1 is one of the most studied eukaryotic proteins involved in temperature sensation. Upon heating, it exhibits rapid reversible pore gating, which depolarizes neurons and generates action potentials. Underlying molecular details of such effects in the pore region of TRPV1 is of a crucial importance to control temperature responses of the organism. Despite the spatial structure of the channel in both open (O) and closed (C) states is known, microscopic nature of channel gating and mechanism of thermal sensitivity are still poorly understood. In this work, we used unrestrained atomistic molecular dynamics simulations of TRPV1 (without N- and C-terminal cytoplasmic domains) embedded into explicit lipid bilayer in its O- and C-states [1]. We found that the pore domain with its neighboring loops undergoes large temperature-dependent conformational transitions in an asymmetric way, when fragments only one monomer move with large amplitude, freeing the pore upon heating. Such an asymmetrical gating looks rather biologically relevant because it is faster and more reliable than traditionally proposed “iris-like” symmetric scheme of channel opening. Analysis of structural, dynamic, and hydrophobic organization of the pore domain revealed entropy growth upon TRPV1 gating, which is in line with current concepts of thermal sensitivity.Acknowledgements: Authors thank Russian Science Foundation (14-14-00871), Russian Foundation for Basic Research (16-04-00578), RAS MCB Program. Access to computational facilities of the Supercomputer Center “Polytechnical” at the St. Petersburg Polytecnic University is gratefully acknowledged.Reference:[1] A.O. Chugunov et al., Scientific Reports 6 (2016) 33112.

ATP-dependent interplay between local and global conformational changes in the myosin motor.

The ATPase active site of myosin is located at the core of the motor head. During the Lymn-Taylor actomyosin contractile cycle, small conformational changes in the active site upon ATP binding, ATP hydrolysis and ADP/Pi release are accompanied by large conformational transitions of the motor domains, such as opening and closing of the actin binding cleft and the movement of lever arm. Here, our previous computational studies of myosin are summarized in a comprehensive model at the level of atomic detail. Molecular movies show how the successive domain motions during the ATP induced actin dissociation and the recovery stroke are coupled with the precise positioning of the key catalytic groups in the active site. This leads to a precise timing of the activation of the ATPase function: it allows ATP hydrolysis only after unbinding from actin and the priming of the lever arm, both pre-requisites for an efficient functioning of the motor during the subsequent power stroke. These coupling mechanisms constitute essential principles of every myosin motor, of which the ATP-site can be seen as the central allosteric control unit. © 2016 Wiley Periodicals, Inc.

Temperature-sensitive gating of TRPV1 channel as probed by atomistic simulations of its trans- and juxtamembrane domains

Heat-activated transient receptor potential channel TRPV1 is one of the most studied eukaryotic proteins involved in temperature sensation. Upon heating, it exhibits rapid reversible pore gating, which depolarizes neurons and generates action potentials. Underlying molecular details of such effects in the pore region of TRPV1 is of a crucial importance to control temperature responses of the organism. Despite the spatial structure of the channel in both open (O) and closed (C) states is known, microscopic nature of channel gating and mechanism of thermal sensitivity are still poorly understood. In this work, we used unrestrained atomistic molecular dynamics simulations of TRPV1 (without N- and C-terminal cytoplasmic domains) embedded into explicit lipid bilayer in its O- and C-states. We found that the pore domain with its neighboring loops undergoes large temperature-dependent conformational transitions in an asymmetric way, when fragments of only one monomer move with large amplitude, freeing the pore upon heating. Such an asymmetrical gating looks rather biologically relevant because it is faster and more reliable than traditionally proposed “iris-like” symmetric scheme of channel opening. Analysis of structural, dynamic, and hydrophobic organization of the pore domain revealed entropy growth upon TRPV1 gating, which is in line with current concepts of thermal sensitivity.

Coarse-Grained Simulations of Heme Proteins: Validation and Study of Large Conformational Transitions.

Heme proteins are ubiquitous in nature and perform many diverse functions in all kingdoms of life. Many of these functions are related to large-scale conformational transitions and allosteric processes. Sampling of these large conformational changes is computationally very challenging. In this context, coarse-grain simulations emerge as an efficient approach to explore the conformational landscape. In this work, we present a coarse-grained model of the heme group and thoroughly validate this model in different benchmark examples, which include the monomeric heme proteins myoglobin and neuroglobin and the tetrameric human hemoglobin where we evaluated the method's ability to explore conformational changes (as the formation of hexacoordinated species) and allosteric transitions (as the well-known R → T transition). The obtained results are compared with atomistic molecular dynamics simulations. Overall, the results indicate that this approach conserves the essential dynamical information on different allosteric processes.

Molecular Dynamics Simulations and Classical Multidimensional Scaling Unveil New Metastable States in the Conformational Landscape of CDK2.

Protein kinases are key regulatory nodes in cellular networks and their function has been shown to be intimately coupled with their structural flexibility. However, understanding the key structural mechanisms of large conformational transitions remains a difficult task. CDK2 is a crucial regulator of cell cycle. Its activity is finely tuned by Cyclin E/A and the catalytic segment phosphorylation, whereas its deregulation occurs in many types of cancer. ATP competitive inhibitors have failed to be approved for clinical use due to toxicity issues raised by a lack of selectivity. However, in the last few years type III allosteric inhibitors have emerged as an alternative strategy to selectively modulate CDK2 activity. In this study we have investigated the conformational variability of CDK2. A low dimensional conformational landscape of CDK2 was modeled using classical multidimensional scaling on a set of 255 crystal structures. Microsecond-scale plain and accelerated MD simulations were used to populate this landscape by using an out-of-sample extension of multidimensional scaling. CDK2 was simulated in the apo-form and in complex with the allosteric inhibitor 8-anilino-1-napthalenesulfonic acid (ANS). The apo-CDK2 landscape analysis showed a conformational equilibrium between an Src-like inactive conformation and an active-like form. These two states are separated by different metastable states that share hybrid structural features with both forms of the kinase. In contrast, the CDK2/ANS complex landscape is compatible with a conformational selection picture where the binding of ANS in proximity of the αC helix causes a population shift toward the inactive conformation. Interestingly, the new metastable states could enlarge the pool of candidate structures for the development of selective allosteric CDK2 inhibitors. The method here presented should not be limited to the CDK2 case but could be used to systematically unmask similar mechanisms throughout the human kinome.

Overcoming potential energy distortions in constrained internal coordinate molecular dynamics simulations.

The Internal Coordinate Molecular Dynamics (ICMD) method is an attractive molecular dynamics (MD) method for studying the dynamics of bonded systems such as proteins and polymers. It offers a simple venue for coarsening the dynamics model of a system at multiple hierarchical levels. For example, large scale protein dynamics can be studied using torsional dynamics, where large domains or helical structures can be treated as rigid bodies and the loops connecting them as flexible torsions. ICMD with such a dynamic model of the protein, combined with enhanced conformational sampling method such as temperature replica exchange, allows the sampling of large scale domain motion involving high energy barrier transitions. Once these large scale conformational transitions are sampled, all-torsion, or even all-atom, MD simulations can be carried out for the low energy conformations sampled via coarse grained ICMD to calculate the energetics of distinct conformations. Such hierarchical MD simulations can be carried out with standard all-atom forcefields without the need for compromising on the accuracy of the forces. Using constraints to treat bond lengths and bond angles as rigid can, however, distort the potential energy landscape of the system and reduce the number of dihedral transitions as well as conformational sampling. We present here a two-part solution to overcome such distortions of the potential energy landscape with ICMD models. To alleviate the intrinsic distortion that stems from the reduced phase space in torsional MD, we use the Fixman compensating potential. To additionally alleviate the extrinsic distortion that arises from the coupling between the dihedral angles and bond angles within a force field, we propose a hybrid ICMD method that allows the selective relaxing of bond angles. This hybrid ICMD method bridges the gap between all-atom MD and torsional MD. We demonstrate with examples that these methods together offer a solution to eliminate the potential energy distortions encountered in constrained ICMD simulations of peptide molecules.

54 Protein folding simulation using temperature based cascade MD

Protein folding is a multi micro second time scale event and involves many conformational transitions. Large conformational transitions important for biological functions are difficult to capture u...