Mert Gur

Exploring the conformational transitions of biomolecular systems using a simple two-state anisotropic network model.

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results.

Pre-existing soft modes of motion uniquely defined by native contact topology facilitate ligand binding to proteins.

Modeling protein flexibility constitutes a major challenge in accurate prediction of protein–ligand and protein–protein interactions in docking simulations. The lack of a reliable method for predicting the conformational changes relevant to substrate binding prevents the productive application of computational docking to proteins that undergo large structural rearrangements. Here, we examine how coarse‐grained normal mode analysis has been advantageously applied to modeling protein flexibility associated with ligand binding. First, we highlight recent studies that have shown that there is a close agreement between the large‐scale collective motions of proteins predicted by elastic network models and the structural changes experimentally observed upon ligand binding. Then, we discuss studies that have exploited the predicted soft modes in docking simulations. Two general strategies are noted: pregeneration of conformational ensembles that are then utilized as input for standard fixed‐backbone docking and protein structure deformation along normal modes concurrent to docking. These studies show that the structural changes apparently “induced” upon ligand binding occur selectively along the soft modes accessible to the protein prior to ligand binding. They further suggest that proteins offer suitable means of accommodating/facilitating the recognition and binding of their ligand, presumably acquired by evolutionary selection of the suitable three‐dimensional structure.

Global motions exhibited by proteins in micro- to milliseconds simulations concur with anisotropic network model predictions

The Anton supercomputing technology recently developed for efficient molecular dynamics simulations permits us to examine micro- to milli-second events at full atomic resolution for proteins in explicit water and lipid bilayer. It also permits us to investigate to what extent the collective motions predicted by network models (that have found broad use in molecular biophysics) agree with those exhibited by full-atomic long simulations. The present study focuses on Anton trajectories generated for two systems: the bovine pancreatic trypsin inhibitor, and an archaeal aspartate transporter, GltPh. The former, a thoroughly studied system, helps benchmark the method of comparative analysis, and the latter provides new insights into the mechanism of function of glutamate transporters. The principal modes of motion derived from both simulations closely overlap with those predicted for each system by the anisotropic network model (ANM). Notably, the ANM modes define the collective mechanisms, or the pathways on conformational energy landscape, that underlie the passage between the crystal structure and substates visited in simulations. In particular, the lowest frequency ANM modes facilitate the conversion between the most probable substates, lending support to the view that easy access to functional substates is a robust determinant of evolutionarily selected native contact topology.

Global Transitions of Proteins Explored by a Multiscale Hybrid Methodology: Application to Adenylate Kinase

Efficient and accurate mapping of transition pathways is a challenging problem in allosteric proteins. We propose here a to our knowledge new methodology called collective molecular dynamics (coMD). coMD takes advantage of the collective modes of motions encoded by the fold, simultaneously evaluating the interactions and energetics via a full-atomic MD simulation protocol. The basic approach is to deform the structure collectively along the modes predicted by the anisotropic network model, upon selecting them via a Monte Carlo/Metropolis algorithm from among the complete pool of all accessible modes. Application to adenylate kinase, an allosteric enzyme composed of three domains, CORE, LID, and NMP, shows that both open-to-closed and closed-to-open transitions are readily sampled by coMD, with large-scale motions of the LID dominating. An energy-barrier crossing occurs during the NMP movements. The energy barrier originates from a switch between the salt bridges K136-D118 at the LID-CORE interface and K57-E170 and D33-R156 at the CORE-NMP and LID-NMP interfaces, respectively. Despite its simplicity and computing efficiency, coMD yields ensembles of transition pathways in close accord with detailed full atomic simulations, lending support to its utility as a multiscale hybrid method for efficiently exploring the allosteric transitions of multidomain or multimeric proteins.

Microseconds simulations reveal a new sodium-binding site and the mechanism of sodium-coupled substrate uptake by LeuT.

Background: LeuT is a homologue of neurotransmitter transporters. Results: Microseconds simulations disclose multiple translocation sites for Na+, including a new site for initial binding. Conclusion: Coupled Na+- and substrate-binding events are accompanied by local and global (interhelical) rearrangements in the outward facing structure. Significance: New insights are gained into Na+ and substrate uptake/efflux mechanisms of LeuT. The bacterial sodium-coupled leucine/alanine transporter LeuT is broadly used as a model system for studying the transport mechanism of neurotransmitters because of its structural and functional homology to mammalian transporters such as serotonin, dopamine, or norepinephrine transporters, and because of the resolution of its structure in different states. Although the binding sites (S1 for substrate, and Na1 and Na2 for two co-transported sodium ions) have been resolved, we still lack a mechanistic understanding of coupled Na+- and substrate-binding events. We present here results from extensive (>20 μs) unbiased molecular dynamics simulations generated using the latest computing technology. Simulations show that sodium binds initially the Na1 site, but not Na2, and, consistently, sodium unbinding/escape to the extracellular (EC) region first takes place at Na2, succeeded by Na1. Na2 diffusion back to the EC medium requires prior dissociation of substrate from S1. Significantly, Na+ binding (and unbinding) consistently involves a transient binding to a newly discovered site, Na1″, near S1, as an intermediate state. A robust sequence of substrate uptake events coupled to sodium bindings and translocations between those sites assisted by hydration emerges from the simulations: (i) bindings of a first Na+ to Na1″, translocation to Na1, a second Na+ to vacated Na1″ and then to Na2, and substrate to S1; (ii) rotation of Phe253 aromatic group to seclude the substrate from the EC region; and (iii) concerted tilting of TM1b and TM6a toward TM3 and TM8 to close the EC vestibule.

Interplay between arginine methylation and ubiquitylation regulates KLF4-mediated genome stability and carcinogenesis

KLF4 is an important regulator of cell-fate decision, including DNA damage response and apoptosis. We identify a novel interplay between protein modifications in regulating KLF4 function. Here we show that arginine methylation of KLF4 by PRMT5 inhibits KLF4 ubiquitylation by VHL and thereby reduces KLF4 turnover, resulting in the elevation of KLF4 protein levels concomitant with increased transcription of KLF4-dependent p21 and reduced expression of KLF4-repressed Bax. Structure-based modelling and simulations provide insight into the molecular mechanisms of KLF4 recognition and catalysis by PRMT5. Following genotoxic stress, disruption of PRMT5-mediated KLF4 methylation leads to abrogation of KLF4 accumulation, which, in turn, attenuates cell cycle arrest. Mutating KLF4 methylation sites suppresses breast tumour initiation and progression, and immunohistochemical stain shows increased levels of both KLF4 and PRMT5 in breast cancer tissues. Taken together, our results point to a critical role for aberrant KLF4 regulation by PRMT5 in genome stability and breast carcinogenesis.

Computational Design of New Peptide Inhibitors for Amyloid Beta (Aβ) Aggregation in Alzheimer's Disease: Application of a Novel Methodology

Alzheimers disease is the most common form of dementia. It is a neurodegenerative and incurable disease that is associated with the tight packing of amyloid fibrils. This packing is facilitated by the compatibility of the ridges and grooves on the amyloid surface. The GxMxG motif is the major factor creating the compatibility between two amyloid surfaces, making it an important target for the design of amyloid aggregation inhibitors. In this study, a peptide, experimentally proven to bind Aβ40 fibrils at the GxMxG motif, was mutated by a novel methodology that systematically replaces amino acids with residues that share similar chemical characteristics and subsequently assesses the energetic favorability of these mutations by docking. Successive mutations are combined and reassessed via docking to a desired level of refinement. This methodology is both fast and efficient in providing potential inhibitors. Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically. The binding free energies of the experimentally studied reference peptide and its three top scoring derivatives were evaluated as a final assessment/valuation. The potential of mean forces (PMFs) were calculated by applying the Jarzynski‚s equality to results of steered molecular dynamics simulations. For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.

Energy landscape of LeuT from molecular simulations

The bacterial sodium-coupled leucine transporter (LeuT) has been broadly used as a structural model for understanding the structure-dynamics-function of mammalian neurotransmitter transporters as well as other solute carriers that share the same fold (LeuT fold), as the first member of the family crystallographically resolved in multiple states: outward-facing open, outward-facing occluded, and inward-facing open. Yet, a complete picture of the energy landscape of (sub)states visited along the LeuT transport cycle has been elusive. In an attempt to visualize the conformational spectrum of LeuT, we performed extensive simulations of LeuT dimer dynamics in the presence of substrate (Ala or Leu) and co-transported Na(+) ions, in explicit membrane and water. We used both conventional molecular dynamics (MD) simulations (with Anton supercomputing machine) and a recently introduced method, collective MD, that takes advantage of collective modes of motions predicted by the anisotropic network model. Free energy landscapes constructed based on ∼40 μs trajectories reveal multiple substates occluded to the extracellular (EC) and/or intracellular (IC) media, varying in the levels of exposure of LeuT to EC or IC vestibules. The IC-facing transmembrane (TM) helical segment TM1a shows an opening, albeit to a smaller extent and in a slightly different direction than that observed in the inward-facing open crystal structure. The study provides insights into the spectrum of conformational substates and paths accessible to LeuT and highlights the differences between Ala- and Leu-bound substates.

Statistical thermodynamics of residue fluctuations in native proteins

Statistical thermodynamics of residue fluctuations of native proteins in a temperature, pressure, and force reservoir is formulated. The general theory is discussed in terms of harmonic and anharmonic fluctuations of residues. The two elastic network models based on the harmonic approximation, the anisotropic network and the Gaussian network models are discussed as the limiting cases of the general theory. The heat capacity and the correlations between the energy fluctuations and residue fluctuations are obtained for the harmonic approximation. The formulation is extended to large fluctuations of residues in order to account for effects of anharmonicity. The fluctuation probability function is constructed for this purpose as a tensorial Hermite series expansion with higher order moments of fluctuations as coefficients. Evaluation of the higher order moments using the proposed statistical thermodynamics model is explained. The formulation is applied to a hexapeptide and the fluctuations of residues obtained by molecular dynamics simulations are characterized in the framework of the model developed. In particular, coupling of two different modes in the nonlinear model is discussed in detail.

Quasi-harmonic analysis of mode coupling in fluctuating native proteins.

Mode coupling and anharmonicity in a native fluctuating protein are investigated in modal space by projecting the motion along the eigenvectors of the fluctuation correlation matrix. The probability distribution of mode fluctuations is expressed in terms of tensorial Hermite polynomials. Molecular dynamics trajectories of Crambin are generated and used to evaluate the terms of the polynomials and to obtain the modal energies. The energies of a few modes exhibit large deviations from the harmonic energy of kT/2 per mode, resulting from coupling to the surroundings, or to another specific mode or to several other modes. Slowest modes have energies that are below that of the harmonic, and a few fast modes have energies significantly larger than the harmonic. Detailed analysis of the coupling of these modes to others is presented in terms of the lowest order two-mode coupling terms. Finally, the effects of mode coupling on conformational properties of the protein are investigated.